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The Future Of Investing In The Outdoor Industry Mel Strong made a meaningful impression during her first appearance on the podcast, and we've got her back on the podcast again to demystify how brands can raise capital, how to speak to boards and VCs, and to answer the all-important question...should we have our own venture fund? Show Notes: Mel Strong: https://www.linkedin.com/in/melanie-strong/ Mel's First Second Nature Episode: https://www.youtube.com/watch?v=q2V0nDHyQRw Next Ventures: https://www.nextventures.com/ TRE: https://www.therunningevent.com/ Nike ACG: http://nikeacg.com/ Oura: https://ouraring.com/ Trial Library: https://www.triallibrary.com/ Eternal: https://eternal.co/ Trucks (VC): https://www.trucks.vc/ Next Ventures Substack: https://nextventures.substack.com/ Felix Kim: https://www.linkedin.com/in/felixkim93/ Ramble Campgrounds: https://ramble.camp/ BPC - Brand, Product, Content: Ramble Campground: https://ramble.camp/ Path Projects - Basis Tee: https://pathprojects.com/products/basis-tee The Courage To Be Disliked (Book): https://amzn.to/471R716 Join us on LinkedIn: https://www.linkedin.com/company/second-nature-media Meet us on Slack: https://www.launchpass.com/second-nature Follow us on Instagram: https://www.instagram.com/secondnature.media Subscribe to our newsletter: https://www.secondnature.media Subscribe to the YouTube channel: https://www.youtube.com/@secondnaturemedia
Morgan Keim, founder of Ocean Ridge Capital, raised over $400 million in venture capital before he turned 35. One of his companies alone pulled in over $300 million pre-revenue—convincing pension funds and VCs to invest hundreds of millions in a company that hadn't made a single dollar yet. On a recent Sales Gravy podcast, he broke down exactly how he did it. The surprising truth? It had almost nothing to do with the pitch itself. “Your single biggest tools in your toolkit are going to be your eyes and ears,” Morgan said. “It’s about listening and seeing where your prospect is and what they really want. That might be different than the words they use.” Consider this: only 7% of communication comes from actual words. Another 38% comes from tone, and the remaining 55% shows up in body language and nonverbal cues. If you're in high-ticket sales, you're probably spending most of your time perfecting that 7%, while missing the other 93% of what your prospect is really telling you. What You’re Missing in Every Conversation Most salespeople obsess over crafting the perfect email. They rehearse their pitch until it's flawless. They tweak their value proposition endlessly. All of that lives in the 7% of communication that comes from words. Meanwhile, prospects are giving away everything you need to know through their tone, body language, and the questions they ask—or avoid. Morgan learned this quickly when raising capital for a food tech startup. Different investors wanted completely different things, even when they all said they cared about “returns.” One investor cared deeply about sustainability and environmental impact. Another focused purely on velocity of capital and exit timelines. A third had unusual mandates that weren't apparent until Morgan listened carefully in person. “It all comes down to having a real understanding of the emotion that person’s feeling, the desired state of where they want to be,” Morgan explained. “Living in that reality of who they are and what they want.” High-ticket sales often fall apart here. Salespeople treat follow-up like a broadcasting exercise: same message, same pitch, same value proposition to everyone because it's “efficient.” Efficiency without effectiveness is wasted motion. The Language Barrier Costing You Deals There's a language of entrepreneurial speak, a language of corporate speak, and a completely different language people use at home. You might communicate seamlessly with colleagues, but explaining your day to your spouse can feel like speaking a foreign language. The same disconnect happens between you and your prospects. Most sellers speak “sales language,” while their buyers speak business or personal language. Top salespeople code-switch naturally. They pick up on how prospects talk, the patterns they use, and the words that matter to them—and mirror that style back. In high-ticket sales, you're asking someone to make a significant investment. They need to feel understood before they'll trust you with that decision. Take an HR leader versus a marketing leader in the same organization: HR cares about employee retention, engagement, and compliance. Marketing focuses on campaign ROI, conversions, and brand lift. The same pitch to both? One will check out halfway through the first sentence. Understanding Their Desired State Make the prospect the hero of the story. Put your ego aside. Stop thinking about your quota. Focus entirely on their desired outcome. Morgan never leads with what Ocean Ridge Capital offers. He starts by understanding their situation: Are they trying to create passive cash flow? Looking for tax efficiency after selling a business? Building generational wealth for grandchildren? Each scenario requires completely different emotional framing. A person focused on legacy thinks about family and long-term impact, while a recent entrepreneur selling for eight figures cares about protecting capital and deploying it efficiently. Same product, completely different language. Send the same follow-up email to both, and you're solving the wrong problem for one of them. How This Changes Your Follow-Up Strategy Once you realize that 93% of your communication lives outside words, your follow-up strategy has to change. Morgan uses multiple channels: Video messages let him read facial expressions and body language. Phone calls provide tone, pacing, and emphasis that email strips away. Handwritten notes show he's willing to slow down in a world that automates everything. Educational content positions him as a resource, not just a seller. He runs A/B/C testing across messaging angles because he can't assume he knows what a prospect wants. When someone doesn't respond to initial outreach, he shifts to “passive value creation”—delivering insight, education, and context—while still prospecting actively through multiple channels. Every touchpoint adds value. Every channel gives a new way to read the prospect, learn their language, and adjust. What to Do on Your Very Next Call Here's your homework. Not next week. Not when you have time. On your very next sales call: Spend five minutes reading the room before you pitch anything. Notice: When their energy shifts. Words they repeat. Moments they lean in or check out. Mirror it back. If they say, “We're building something sustainable,” don't respond with, “Our solution drives ROI.” Stay in their language. Stay in their world. Try a different channel. Been emailing for weeks with no response? Pick up the phone. Send a 60-second video. Mail a personalized note. The mechanics haven't changed. You still need multiple touches. But if you ignore tone, body language, and emotional state, you're having a completely different conversation than your prospect is. Why This Approach Wins High-ticket sales are about human connection more than polished words. Prospects respond to feeling understood, recognized, and respected. The words you say matter far less than how you convey empathy, awareness, and relevance. Morgan's results speak for themselves: reading the unspoken signals and adapting builds trust, shortens sales cycles, and secures investments that others can't reach. High-ticket sales aren't only about what you say—they're about what you see. Pay attention, and everything changes. – Take your follow-up strategy to the next level. Download the FREE ACED Buyer Style Playbook and learn how to read what your prospects really want.
Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade
On this episode of Practical Pivots, host Steve Pockross rewinds the sharpest go-to-market lessons from the show's most insightful guests to help founders navigate a world where software is cheap, AI is everywhere, and attention is scarce. Drawing on 12 hard-won insights from operators, VCs, and AI leaders, Steve breaks down why being more human is the real competitive edge, why distribution now beats product, how to define product-market fit in plain English, and why clarity and focus will outlast every stunt and channel hack. If you're stuck on plateaus, over-investing in tactics, or wondering where AI truly belongs in your GTM motion, this highlight reel gives you a crisp playbook for building trust, proving demand, and scaling what actually works in 2026.
This week on Swimming with Allocators, Marcia Mitchell joins Earnest and Alexa to trace her path from FF Venture Capital to New York Ventures and now Mesa Lane Capital, a GP-seeding fund focused on emerging managers. She shares how her time in government shaped a broader, more responsible view of innovation and capital allocation, and discusses the increasingly crowded emerging manager landscape and where capital is still being overlooked. Marcia also breaks Mesa Lane's differentiated model of large anchor checks, follow-on commitments, co-invest pools, no carry at the FoF level, and hands-on support, positioning the firm as a true co-builder. The conversation closes with how parenthood reshaped her approach to focus, boundaries, and investing in people who energize her. Highlights from this week's conversation include: Welcoming Marcia Mitchell to the Show (0:22) Moving Into Public Sector Allocations at New York Ventures (3:39) Are We Capped Out on Emerging Managers in Today's Market? (7:33) How Mesa Lane Differentiates Its Fund of Funds Model (9:49) Facilitating Direct Relationships Between GPs and LPs (12:07) How Engaged Are LPs With Direct Deals and Co‑Investments? (13:22) Radical Transparency and Hands‑On Support in Diligence (14:42) Shifts in Founder Boards, Equity, and Employment Terms (17:54) Power Dynamics and “Prenup” Mindset in Founder–Investor Negotiations (19:46) Drafting Around Founder Entrenchment and Board Deadlock (20:57) Why Rebecca Joined Sidley and the Firm's Venture Platform (22:14) What a Mesa Lane GP Looks Like (24:16) Industry Maturation, Hedge Fund Parallels, and Co‑Opetition in Venture (26:07) Back Office Platform, Service Provider Discounts, and AI in Operations (28:46) How Parenting Changed Marcia's Perspective and Boundaries as an Investor (30:42) Prioritization, Structure at Home, and Investing in Energizing People (33:11) Who Mesa Lane Wants to Hear From: Ideal Fund Size and Stage of GPs (35:46) Sector Focus, Crypto Caveats, and Thoughts on Solo GPs (37:10) Mesa Lane Capital is a $300M emerging manager investment platform backing early-stage VCs. The firm makes $20M anchor-style fund commitments and offers operational support across legal, tax, admin, and HR functions. Mesa Lane is not a traditional FoF: they offer access to their LP network and prioritize transparency and value-add. Founded by Scott Sherman (ex-Blackstone, Tiger) and Mark Friedman (hedge fund builder), they blend Wall Street rigor with venture approachability. Sidley Austin LLP is a premier global law firm with a dedicated Venture Funds practice, advising top venture capital firms, institutional investors, and private equity sponsors on fund formation, investment structuring, and regulatory compliance. With deep expertise across private markets, Sidley provides strategic legal counsel to help funds scale effectively. Learn more at sidley.com. Swimming with Allocators is a podcast that dives into the intriguing world of Venture Capital from an LP (Limited Partner) perspective. Hosts Alexa Binns and Earnest Sweat are seasoned professionals who have donned various hats in the VC ecosystem. Each episode, we explore where the future opportunities lie in the VC landscape with insights from top LPs on their investment strategies and industry experts shedding light on emerging trends and technologies. The information provided on this podcast does not, and is not intended to, constitute legal advice; instead, all information, content, and materials available on this podcast are for general informational purposes only. Learn more about your ad choices. Visit megaphone.fm/adchoices
Neil Tanna's early fundraising mistake: he could articulate the hero perfectly. But he couldn't explain the villain.As founder of Howbout (6 million users, backed by VCs and the Sidemen with 300 million followers), Neil learned the hard way that the hero makes no sense without the villain.Investors don't care if you can describe your solution. They need to understand the problem you're solving - viscerally.What you'll hear:Why early Howbout messaging failed. They focused on the solution (social planning app) without making the problem (losing touch with friends) crystal clear. They were brilliant at the hero. Terrible at the villain.How the villain evolved as users actually used the product. Initially: scheduling pain, the back-and-forth of group chat. But users weren't just planning events - they were putting their entire lives in the calendar. Everything. The real villain became "losing touch with friends in a world pushing you toward creators over actual connection."What to do when users redefine your product. Howbout positioned as "social planner." Users turned it into a "platform to share time." Gen Z were adding when they're on their period, when they have dates, everything. Why? Because they're digital natives who share their live location with 5-15 friends. Time is the same.How to pitch the same business to different audiences. US VCs: "Why are we talking about monetisation?" European VCs: "Why are we talking about anything else?" At seed, 10x more monetisation talk. At Series A, barely mentioned it. You have to evolve your story based on who's listening.Why you need to define your ethos, not just vision/mission. What is the emotional reason someone uses your product? Why do they share it? Why do they pay for it? Everyone in your business should articulate this in a couple sentences. This is your right to win.The CFO growth hack. Every friend group has a Chief Friendship Officer - the Type A planner, the micro-influencer. Neil targeted them through Instagram memes. Why focusing on everyone means no one. Howbout only focused on UK 18-22 year olds initially. Then proved US growth before Series A. If you try to be everything to everyone, your messaging becomes mud.The insight:Listen to find out
"What does it actually take to get a family office to back you? In this episode, Prashant sits down with Slava Darkhaev, a family office investor based in Cyprus who deploys into emerging VC managers and direct deals across the US market.Slava breaks down how he evaluates first-time fund managers, what a real competitive edge looks like versus a rehearsed pitch, and why network quality matters far more than network size. They also get into portfolio construction, co-investment strategy, the emerging markets opportunity, and the biggest mistakes fund managers make when fundraising.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comTopics covered:— What "right to exist" really means for a fund manager— How to evaluate GPs before they have a track record— Why the VC power law makes network everything— LP book vs. direct co-investments — how to run both— Diversification as upside management, not downside protection— India, Southeast Asia & Latin America — the emerging market thesis— The #1 fundraising mistake GPs make repeatedly"If you're a GP raising your first or second fund — or an LP trying to build a smarter allocation strategy — this one is for you.TIMESTAMPS(00:00) - Episode Highlights(00:51) - Introduction to Slava Darkhaev & the Episode(02:19) - The 'Right to Exist' for VCs vs. Founders(05:02) - How to Identify and Back Top-Tier GPs(07:11) - Benchmarking Emerging Managers: The Insider Approach(08:42) - The #1 Trait Separating Top GPs from the Rest(11:05) - Strategy for Direct Investments vs. LP Investments(12:43) - Securing Co-Investment and Pro-Rata Rights(13:51) - A Different Take on Diversification in Venture Capital(16:07) - Investing Thesis on Emerging Trends and Macro Cycles(17:27) - Due Diligence for a Manager's Subsequent Fund(19:22) - Family Office Asset Allocation to Venture Capital(20:02) - Investing in 'Unproven' First-Time Managers(21:29) - Approach to Investing in Global Emerging Markets(24:58) - Key Advice for Fund Managers: The Power of Storytelling(25:46) - Common Mistakes Fund Managers Make When Fundraising(26:46) - Rapid Fire Round(27:51) - Conclusion & How to Connect with SlavaLINKSSlava Darkhaev - https://www.linkedin.com/in/slava-darkhaev/Prashant Choubey - https://www.linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comSubscribe on YouTube - https://youtube.com/@VC10X Subscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQVC10X website - https://vc10x.comFor sponsorship queries, reach out to prashantchoubey3@gmail.comSubscribe for more conversations at the intersection of family office investing, private markets, and emerging trends in wealth management.
How can founders increase the value of their business before selling—and keep more of the proceeds after the exit? In this episode of the Grow & Learn Podcast by Grownlearn, host Zorina Dimitrova speaks with Marc Adams, strategy mentor and founder of Acquisitions4You, about how entrepreneurs can increase company valuation and prepare for a smarter, more tax-efficient exit. Marc works with founders, investors, and family offices to help businesses grow enterprise value within 12–24 months, often without giving up equity or signing personal guarantees. His approach focuses on strategic acquisitions, consolidation of fragmented markets, and positioning businesses for higher valuation multiples before a sale. Marc shares insights from his “Double & Keep It” framework, which helps business owners grow valuation while avoiding the common trap where founders lose 30–50% of their sale proceeds through taxes, fees, and poorly structured deals. In this conversation we discuss: • Why most business owners are not prepared to sell their company • How acquisitions can dramatically increase enterprise value • How founders can structure tax-efficient exits • Why exit planning should begin years before selling • How family office capital can support strategic growth Marc also shares how a life-changing stage-4 cancer diagnosis during COVID reshaped his perspective on risk, legacy, and helping founders protect the value they build. If you are a founder, entrepreneur, investor, or business owner considering scaling or eventually exiting your company, this episode offers practical insights on business valuation, strategic acquisitions, and exit preparation. ________________________________________
Melissa Theiss, Head of People Ops at Kit, joined us on The Modern People Leader to break down how HR leaders can build real business acumen using practical frameworks like Track-Racehorse-Jockey, her PeopleOps maturity diagnostic, and a 90-in-90 listening tour. We also walked through how to turn employee feedback into an actionable backlog and use it to shape a people strategy that supports the business first while staying people-centric.---- Downloadable PDF with top takeaways: https://modernpeopleleader.kit.com/episode285Sponsor Links:
This special episode is an inside look at AI music from three very different vantage points: the builder, the investor, and the industry insider.Andreas is joined by Sundar Arvind, CEO & Co-Founder at Mozart AI, building a collaborative generative audio workstation; Daniel Waterhouse, General Partner at Balderton Capital; and Ash Pournouri, Co-Founder of Belong, entrepreneur, producer, and former manager of Avicii.Together, they unpack how AI is reshaping music creation, how serious investors underwrite risk in a litigious industry, why “one-click songs” miss the point, and whether AI expands creativity or commoditizes it.If you want a grounded view of where the real fault lines are — rights, training data, authorship, collaboration, and the psychology of creativity — this is it.ShareWhat's covered:00:40 Mozart AI's vision: a collaborative generative audio workstation05:10 DAWs, EDM, and why tech has always expanded music creation06:35 Why “one-prompt songs” optimise for quantity, not craft09:20 Underwriting AI music: how VCs think about billion-dollar incumbents13:00 Is this a new instrument or a 100x larger market?18:45 Are professional artists already using AI tools?21:00 Copyright, training data, and legal diligence in AI music25:15 Philosophically: what are “rights” when machines learn from music?33:40 Diffusion models explained simply: how AI generates sound36:30 The return of the band? Multiplayer music creation40:00 Ash Pournouri joins: the industry's instinct is protection44:10 “You can't stop development”: why demand always wins48:50 Packaging matters: AI as tool vs AI as replacement51:20 Lowering thresholds and democratization across decades56:30 Five-year predictions? We're on the vertical part of the curve58:10 The “vibe coding” moment for music
Feeling financially successful on paper but trapped in real life can change everything. In this episode, C-suite executive and board director, Leilani Latimer, shares how unintentionally becoming house poor while living in Italy as a young adult forced her to confront anxiety, control and independence. When she sold the house, those lessons ultimately set the foundation for her to achieve a healthier, more balanced relationship with money. Leilani is a global C-suite executive and NACD Certified Board Director who leads companies through critical inflection points. She drives growth, connects strategy to execution and builds operating models designed for scale and resilience. Her track record spans B2B, SaaS, Marketplace, AI/ML and Enterprise Technology companies across public, PE-backed and venture-backed organizations. She has held executive roles in sales, marketing, commercial operations, product and customer success, bringing a comprehensive understanding of how these functions integrate to drive performance. She is currently a strategic advisor to growth-stage technology companies, partnering with Founders, CEOs, VCs and PEs to shape business models, strengthen go-to-market execution and design the teams and structures required to scale. She has led early-stage companies in supply chain, retail and medtech through transformational growth, building commercial and marketing engines from startup through acquisition, delivering significant revenue growth and improved forecasting. Leilani’s deep technology expertise includes 25 years with Sabre Inc. (NASDAQ: SABR), a global leader in travel, hospitality and transportation technology. In leadership roles spanning sales, product, marketing, strategy and sustainability across North America and Europe, key achievements include repositioning the hospitality business for IPO, developing award-winning enterprise sustainability systems and products, restructuring global product investment plans and helping build the Southern European division from inception to 15% market share. Leilani currently serves as an Independent Board Director at Black Diamond Group (TSE: BDI), Sedex and Narratize, and as an Advisory Board Member at Fiutur and FoodMesh. Her board contributions span governance, strategic capital allocation, compensation and risk oversight. Her unique perspective on corporate risk and reputation is shaped by her expertise in sustainability, over 15 years of leadership in European markets and extensive experience across multiple industries. Based in San Francisco, she is a dual US and Italian citizen. Independence, Investing and Intentional Choice Leilani's story reminds us that financial independence is not a fixed destination but an evolution. From navigating cross-border careers and complex benefits systems to rethinking what fairness means in partnership, she shows how money can either create anxiety or expand possibility. Today, her focus on teaching her children to invest early, supporting female founders and building values-aligned portfolios reflects a deeper truth: wealth is a tool for choice. The freedom to decide where you live, what you support and how you show up in the world is the ultimate return on investment. If you are considering board service, navigating career transitions or thinking more intentionally about how and where you invest, an Aspiriant advisor can help you align your wealth with your values and design a strategy that supports both independence and impact. Follow Money Tales on Spotify, Apple Podcasts or YouTube Music for more real stories that inspire smarter, more intentional decisions with your money.
Who dares to make predictions in the current landscape? We do! Our Predictions are back. Will our track-record continue on a high or will we be fundamentally wrong? Listen in to our Predictions for 2026 Navigation: Intro What will 2026 be all about? AI, AI and … more AI The big Hardware movements Of Start-ups and VCs Regulatory & Geopolitical Headwinds… and the Wars Fintech, Crypto and Frontier Tech Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand Schmitt Introduction Welcome to Tech Deciphered Episode 74. That would be an episode about some predictions about 2026. What will be 2026 all about? I guess this year is probably starting with a bang. We saw the acquisition of xAI by SpaceX. We saw an acquisition from Grok by NVIDIA. What’s your take about what would be the big themes in 2026? I guess it would be for sure about AI and space. Nuno Goncalves Pedro What will 2026 be all about? Yeah. I predict a year that will be a little bit more of a year of reckoning in some way. There will be a lot of things that I think we’ll start seeing through. The fact that we are in the midst of an amazing transformational era for technology, the use of AI, but at the same time, obviously, a ridiculous bubble that is going alongside it as we’ve discussed in previous episodes. I think that we’ll start seeing some early reckonings of that, companies that might start failing, floundering, maybe a couple of frauds along the way, etc. I’ll tell you what I will not make many predictions about today, which is geopolitics. Geopolitics, I will not make predictions at all. Who the hell knows what’s going to happen to the world this year in 2026? I don’t dare making any predictions on that. Back to things where I would make predictions. I think on AI, we’ll have a little bit of reckoning. We’ll talk about it a little bit more in detail during this episode. Interesting elements around the hardware and physical space. Physical space, we just dedicated a full episode to it. We won’t go into a lot of details on that, but definitely on the hardware side, we’ll talk a little bit more about it. The VC landscape is going through an incredible transformation. We’ll talk about it today as well and some of our predictions for this year. What will happen to the asset class? It seems to be transforming itself dramatically. Obviously, that has a very direct impact on startups, so we’ll talk about that as well. And then to close a little bit the chapter on this, we will address some regulatory and geopolitical, let’s call it, headwinds without making maybe too many complex predictions. We shall see. Maybe by that time of the episode, we will be making some predictions. You guys should stay and listen to us, and maybe we will actually make some predictions about the geopolitical transformations that we will see this year in the world. Then last but not the least, we’ll talk about fintech, crypto, frontier tech, and a couple of other areas before concluding the episode. A classic predictions’ episode. We normally have a pretty good track record on some of these, but right now, the world is going a bit interesting, not to say insane. Bertrand Schmitt Yes, and going back to some news, Groq technically was not acquired, but, practically, it’s as if it got acquired. I’m talking about Groq, G-R-O-Q. The AI semiconductor company focused on inference AI, and it was late December. It was a way to end the year. This year, we started again with an acquisition of xAI by its sister company, SpaceX. I guess that’s where we are starting. AI, AI and … more AI We are going to start on AI. That’s definitely the big stuff. Everything these days, I guess, is about AI or has to have some connection with AI, or it doesn’t matter. I think every company in the world has seen that. You have to have the absolute minimum on AI strategy. You better execute on this strategy and show results, I would say. For the companies that were not AI native, you truly have to have a way to transform yourself. I guess at some point, the stretch might be too much, and it’s not really reasonable. Then you maybe better stay on what you are doing, especially if you’re in tech, you better be moving faster to AI. Nuno Goncalves Pedro Just to highlight, and I think throughout the episode, you’ll see that there’re obviously a lot of implications that would manifest themselves into capital markets. I mean, we’ll specifically talk about VCs and startups later on. But the fact that everything needs to be AI, the fact that there’s so much innovation happening right now, in my opinion, and this is maybe the first pre-topic to AI, is we’ll see a tremendous increase in M&A activity this year across the board. I mean, we’ve seen already some big acquihires we mentioned in some of our previous episodes, but we’ll see a lot more activity on M&A this year. Normally, that’s a precursor to the opening of capital markets. I predict also that there will be a reopening of the IPO market that never really reopened last year, to be honest. M&A, a lot more, reopening of the IPO market. Normally, it happens in the second or third quarter of the year. That’s what my M&A friends tell me. First quarter of year, everyone’s figuring out stuff. Then last quarter of the year, things should be more or less closed. Maybe the third quarter is the big quarter. We shall see. But definitely, as a precursor to our conversation today, I think we’ll see a lot of M&A, and we’ll see reopening of the IPO mark. Bertrand Schmitt I guess last year was not as big as you could expect on M&A given the tariff situation announced in April and May. I mean, it became quite tough to do IPO in such market conditions. Definitely, we can hope for something dramatically different in 2026. I guess talking about public markets and IPO, I guess the big one everyone is waiting for is SpaceX. SpaceX getting even more interesting with its xAI acquisition. Nuno Goncalves Pedro Do you think that because of the acquisition, it’s more likely that it will happen this year, or because of the acquisition, it’s less likely that it will happen this year? Bertrand Schmitt That’s a good question. My guess is the acquisition of xAI is all about xAI needing more financing and cheaper financing. This acquisition is a pathway to that. SpaceX being a much bigger company, a company that is also making much more revenues. I could bet that there is higher probability that, actually, SpaceX will go public in order to finance itself. At the same time, will it have enough time to prepare itself for the IPO given this acquisition just happened? Can they do that in 6 months? I mean, if anyone can do it, I guess it’s Elon Musk. It’s a strategy to present an even more attractive company with an even more interesting story, a story of vertical integration from AI to space. I guess the story as it’s presented itself right now, it’s one about having your AI data centers in space. Because in space, you have much better solar energy production with solar panels. You have a perfect cooling situation because you are in space. Thanks to Starlink, you have the mean to communicate between the satellites and with Earth itself. I think if someone can pull up a story like AI data center in space, I guess Elon Musk can. There is, of course, a lot of questions about is it practical? Is it economical? Yes. I certainly agree. I’m not clear on the mass, and can you make it work? Again, I mean, Elon Musk single-handedly, with SpaceX, managed to transform the space market on its head. I mean, they are the biggest satellite launching company in the world. They have the most satellites in the world. I mean, I’m not sure I would bet against him, and I guess I would probably believe that he could pull up something. Time frames, different story. The 2-3 years data center in space for AI as cheap as on Earth, I have more trouble with that one. I mean, it’s a usual suspect with Elon Musk. You promise something unachievable in a few years, but, ultimately, you still manage to reach it in 5 or 10. Again, I would not bet against the strategy. Nuno Goncalves Pedro Yeah. I’ve talked to a couple of space experts, people that have launched rockets, and have worked JPL, NASA, and a couple of other places, etc. For what it’s worth, their feedback is, “No way in hell, and we’re decades away.” We’ll see. I mean, to your point, Elon has pulled very dramatic stuff. Not as fast as he normally says he’s going to pull it, but within a time span that we all see it. Difficult to bet against him. In terms of actually the prediction, maybe to respond to the prediction as well, will SpaceX IPO? I’m going to make a prediction that has a very high likelihood of missing the mark, but I think Tesla’s going to buy and merge them both into it. It’s going to become a public company through Tesla. That’s my hypothesis. Bertrand Schmitt No. That’s supposed to be it. That’s how you solve that. Nuno Goncalves Pedro And Elon controls the whole universe. X, xAI, Tesla, SpaceX, all under one umbrella beautifully run. And SolarCity is well in there, of course, so wonderful. Bertrand Schmitt That’s possible. Certainly, you are not the only one thinking Tesla will acquire or merge with SpaceX. To remind everyone, Tesla is around 1.3, 1.5 trillion market cap. Depending on the day, SpaceX seems to be valued at similar range, 1.2, 1.3 trillion. It looks like it’s the most valued private company at this stage. These are companies of similar size, so that’s one piece of the puzzle. When you think about the combined company, we could be talking about a 3 trillion entity. Playing right here with the biggest companies in the marketplace today. Nuno Goncalves Pedro With a couple of tweets from Elon, it will rapidly get to 4 to 5 trillion. Bertrand Schmitt That’s so tricky. Nuno Goncalves Pedro Yes. On AI and back to AI, one thing I think that we’re about to see is this will probably be the year of agentic AI. Obviously, we predict a lot of growth on that side of the fence, in particular on the enterprise B2B side. We see a lot of opportunities coming through. From our perspective, at least at Chamaeleon, we generally believe that there’s going to be a lot of movements on agentic AI. It’s also going to be probably the year of the first big fails of agentic AI that will be newsworthy. There will be some elements about that loop and how it gets closed that will happen. I think we might see some scandals already. We’re already seeing the social network of bots talking to bots. We will see other scandals going on this year even in the consumer space and in the bot to bot space, which we now can talk about or in the AI agent to AI agent space. My prediction is we will see some move forwards. There’ll be some dramatic funding rounds along the way. We’ll see a couple of really cool things out of the gates coming out that are really impressive, but we’ll also see the first big misses of the technology stack. I don’t think we’ll go fully mainstream yet this year, so it’s probably maybe something more for 2027 along the way. That would be my prediction again. I think enterprise will lead the way. We’ll definitely see a lot of stuff on consumer as well that is cool. Then we’ll all have our own personal assistance in our hands, basically, literally in our phones. Bertrand Schmitt Going back to agentic AI, we also started the year with some pretty dramatic move. I mean, the launch of Clawdbot, renamed OpenClaw. I mean, this stuff took fire in like a week or 2. It was coded by just one person who actually didn’t even code the product but used AI to build the product, 100% used AI, proposing some new ways also to leverage AI to do coding. He has a pretty unique approach. It’s not vibe coding. I would say it’s a better way to do that. Then the surprising evolution with the launch of a social network for AI agents, Moltbook. I mean, this stuff, probably there is some fake in it. But at the same time, I think it’s quite impressive because it’s the first time we see truly 100,000 plus agents communicating directly to each other. Yeah. I mean, that’s the first time we see surfacing the possibility of some sort of hive mind on the Internet. It’s pretty surprising. Right now, all of this is a hack done in a few days. By end of year, by 2 years, 3 years, we might discover that, actually, the best approach to AI might not be the AI assistant like we are doing today, but a combination of hundreds of thousands of AI working closely together. We might be witnessing the first sign of new intelligence in a way. Nuno Goncalves Pedro Things like this social network might either be Skynet, the beginning of Skynet. They might be the beginning of Her, or they might just be a fad and nothing really happens. It’s just interesting to see what these agents are doing. Bertrand Schmitt Totally. Nuno Goncalves Pedro Obviously, there are real and clear and present dangers of some of the integrations of AI we’re seeing in the market. Interesting enough, and I’ll ask you for your prediction a bit, Bertrand. I think we’ll probably see the first big mishap of AI being used in some infrastructural decision in the age of AI. I mean, we’ve seen AI issues in the past and software issues in the past. We talked in previous episodes about that as well. Mishaps of software that have led to people dying. But I think probably the first big mishap will happen this year as well. Very public mishap of the use of AI and serve its interactions with infrastructure or something that’s very platform related, etc, that will have big impact that everyone will notice. That’s my prediction for the year as well. We’ll have the first big oops moment, as I would call it, for AI in this new age of full on AI. Bertrand Schmitt I would say first some perspective. I think today, people are not using AI directly for life and death decision, at least not that I’m aware. We’re not going to let AI fly a plane, for instance, tomorrow so you can be, reassured. At the same time, given there is such a race to AI, there definitely might be some mistakes. We were talking about the social network for AI agents, Moltbook. Apparently, all the keys used to secure the AI were shared by mistake because it was not properly locked down. We can see that indirectly, mistakes will be made for sure. Two, it’s highly probable that some people will trust AI too much to do some stuff, and this stuff might not work and might have some grave consequence. Hopefully, there is not so much of this. Hopefully, it’s mostly AI used for the good. But you’re right. I mean, at some point, the more we use the technology, the more there would be issue. I mean, it’s highly probable. Nuno Goncalves Pedro That will lead me to another prediction, which is, and we’ll talk about more of it later, but it probably will lead to the first significant movement in terms of regulatory environment certainly in the US at some point if it happens in the US in particular, where there will be some movement that will be like, “Hey, you guys can’t do this anymore.” Because this will probably emerge from mismanaged interfaces. From systems having access to stuff that they shouldn’t have access to in the first place. Talking a little bit more about what’s happening in AI. You’ve already mentioned some of the issues that relate actually to security and cybersecurity. We keep talking about AI. We keep talking about all these infrastructure pieces and platforms that are being built. I think we’ll have a lot more incidents like the one you just mentioned where things will be shared that shouldn’t have been shared, where people will break systems and get into it, etc. Let’s see where that takes us, which is a little bit ironic because, obviously, with AI, the promise is that cybersecurity becomes more robust as well because there’re agents working on our behalf on the cybersecurity side. There’s also agents working on the other side. Bertrand Schmitt It’s a constant race. It’s the attackers, defenders. Each time you have new technology, you have a new race to who is going to attack or defend the best. Each new wave of technology, it’s an opportunity to challenge the status quo. Nuno Goncalves Pedro The attackers have been winning, and I feel they’ll continue winning in 2026. I think it’s going to still be a year of attack. We’ll see more and more breaches, more and more stuff that will happen. Bertrand Schmitt I don’t know if they will win. I mean, it’s normal that they win once in a while. For sure, some infrastructure is not updated as it should. Some stuff are not managed as it should, so there will always be breaches. I don’t know if things are dramatically going to change because, again, everyone who cares who is going to update his infrastructure with AI for defense. There is no question that you have no choice. We will see. That I don’t know. For sure, AI will be used to attack directly with AI. Maybe you’re able to do bigger, larger scale attack. Or thanks to AI, you are simply able to create new type of attacks more easily. AI can be used behind the scene as a way to prepare and organise new type of attacks, even if it’s not used directly live in the battle. Nuno Goncalves Pedro One topic that we’ll come back to later is the geopolitics of everything, but maybe more broadly. On the geopolitics of AI, it’s very clear that we have an arms race going on. Obviously, the US on the one hand, China on the other hand is the two extremes, putting tremendous amount of capital into data centers just at the base of that infrastructure. Chipset development, chipset access, a huge theme in terms of the export restrictions, etc, that are being forced by the US. I think it will continue. From a European standpoint, obviously, they’re stuck between a rock and a hard place, to be very honest. Let’s see what happens on that side of the fence. My view of the world is that certainly from a US and China perspective, we’re going to see a lot more movements in 2026, like big movements. The Chinese movements we always see in delay. It takes us a couple of months, sometimes even more than that to understand exactly what’s going on. I think we’re going to see some huge moves this year in terms of the States, the United States of America, and China really pouring capital into the creation of the next big winners around AI. I think the US is obviously more visible. We see a lot of these companies. We’ve just discussed xAI and its acquisition by SpaceX or merger. I don’t know what they’re calling it exactly. Effectively, on the China side, the movements I think are already very big. As I said, it will take a while to figure out exactly what those moves are. One thing that I propose is that at some point, China will have very little dependency on chipsets from the US. I’m not sure it’s going to happen this year, but I think the writing is on the wall. Irrespective of any other geopolitical issues that is coming to the fore at this moment in time. That’s one of the key areas or in arenas of fight. Bertrand Schmitt It makes sense. If you are China, you will look at what happened. You would think that you cannot just depend on the largest of one country. It makes rational sense, the same way it makes rational sense for the US to limit exports to China because there is value to delay some peer pressure that could use these technologies for good but also for bad. If you were an ally of the US, that would be one thing. But when you are not an ally of the US, that certainly should be a different perspective. Maybe one last point concerning agents, I think there will be a lot that will revolve around coding. We can see OpenAI with Codex. We can see Cloud with code. There was, of course, [inaudible 00:18:28] that was trying to be big on agentic coding. I think agentic coding was one of the big transformation in 2025 and is going to get bigger in 2026. I think for a lot of people who do coding, there was a radical transformation in terms of what you can achieve, what you can do, how much you can trust AI to help you code. I start to think we might see this year, the replacement of not just one AI replace one coder, but one AI replace a full team because of the new ability to manage that at scale. Coding might be a common activity where you are going to think about outcomes, think about objective, think about how you organise, but not really coding by itself anymore. A big change, like you used to code, directly your hand on the stuff, but step by step, everyone is going to become a manager of agent. I think in one year, we saw enough transformation to think that in the coming year, the transformation can be even more dramatic. Nuno Goncalves Pedro The big Hardware movements Now switching gears to hardware. Obviously, a lot of movements in 2025 and over the last few years. One piece of thesis that we’ve had long-standing at Chamaeleon is that we will see the emergence of AI devices. Some of them have been tremendous failures as we discussed in the past. I predict that we’ll have a couple of really interesting full stack AI devices in the market this year. Why does that matter? Because, as many of you know, obviously, there’s compute that can happen in data centers and cloud infrastructure all over the world, but also there’s compute that can happen at the edges. The more you can move to the edges and the more you can create devices that actually allow you to have user experiences that are very distinctive at the edge, the more powerful some of these devices might become. I predict Apple will not be the first to launch anything on this. I predict probably OpenAI, after the acquisition of IO, will maybe not launch something this year, but will announce something this year. I’ll step back on that prediction. They’ll announce something this year, but maybe not launch. But we’ll start seeing some devices that have some interesting value in the market, probably devices that are AI devices, but they are very focused on very specific user flows, and so very much adequate to specific activities. I won’t make a prediction on that, but I think areas that would make sense for that to happen would be obviously around fitness, health, et cetera, et cetera, where we already have the ascendancy of products like Oura Ring and others out there. Definitely, that’s one area that might have quite a lot of developments. I think AI-first devices, devices that are very focused on compute at the edges, providing user flows that are AI-enabled to end users, we’ll see a lot more of that and a lot more activity this year. Again, I don’t think Apple will be necessarily ahead of the game. Again, maybe OpenAI will give us something to at least think about and look forward to. Bertrand Schmitt First, I’m not sure it will be that transformational because if it’s not in your phone, in your pocket, there is only so much you can do with it, and there is only so much computing power you will have. I’m doubtful it would be really impactful this year. Nuno Goncalves Pedro I feel we’ve been discussing this shift of paradigm in input and output. For me, some of these devices could lead to that shift. Because, again, a mobile phone is not a great long-term paradigm for the usage that we have because it’s really constrained by the screen. The screen is really what takes most of the battery life away. If we didn’t have that screen, what could we do? If we have the block that is as big as a mobile phone, and it didn’t have a screen, it was just compute, that’s a mini computer, a microcomputer. Bertrand Schmitt That’s a fair point, but I don’t see that transformation this year. That’s really more my point. I can see that you can have AI-enabled smart glasses, and it’s clear there is a race to AI-enabled smart glasses. My point is more to go beyond the gadget, it would take quite a while. It would need to have cameras. It would need to analyse what you see. It would need to hear what you hear. Again, it might come, but then at some point, it would be okay, what do you do with it? We have the example of the movie Her. That’s showing Her what it could be. There are definitely possibilities. It’s clear that if you take the big VR headset like the Apple Vision Pro, there is a failure from that perspective in the sense that I think it’s a great, amazing device. The big problem is that it’s doing way more that makes sense. I think there will be a clearer separation between your smart AR glasses that has to be light, that has to be always unconnected, and that’s primarily there to help you make sense of the world around you. The true VR headset that doesn’t really require much in terms of AI, and it’s just there to immerse you in a different world. For this, we know, unfortunately, in some ways, that there is not a lot of demand for it. Maybe there is little demand because you are too hidden in your own world. The technology is not working well enough yet. There are a lot of reasons. But I think Apple trying to do both at the same time, AR and VR, with the Vision Pro, was a pretty grave structural mistake. I think we would see a clearer line of separation between the two. There is bigger market opportunity for AR glasses. That, I certainly agree. There is opportunity to connect that to a computing device. As you talk about, your glasses are your screen, your phone becomes something in your pocket connected to your glasses. Nuno Goncalves Pedro For me, Apple has their way of doing things. From the perspective of what you said, they normally really plan their devices. Even if it’s a big shift in terms of a new area, like they tried with the Vision Pro, and we criticised them for launching it as a device that should have been more of a dev device that they really launched as a full-on device, but that’s their playbook, classically. I think Apple needs to change how they put products out and how they experiment with those products, et cetera. I think they have enough money to be doing everything all the time and figuring it out. If they don’t want to put it out, then they need to do a lot more hell of testing internally with their silos, but they should be playing across all these arenas, VR, AR, everything. They just should put devices out that are either ready for prime time, or they should call it something else. They should call it like this is a dev device or whatever it is. Bertrand Schmitt I agree with you. My complaint is more that it was marketed as a consumer device when it was not. It was a true developer device. Two, they tried to mix the two at once, and it made no sense. No one is going to walk in their home or in the street with their Vision Pro on their head. You have to be deranged, quite frankly, to have use cases like this. I think that for me is a crazy mistake from a company like Apple that prides itself in pure UI, pure user interface, very well-designed device for one specific use case, not mixing the two use cases. We still don’t have Macs with a touchscreen, you know? We still don’t have an iPad with a good OS that makes use of this great hardware. For some strange reason, they decided to mix everything in the Vision Pro with a device that weighs a ton on your head and is so uncomfortable. That’s why, for me, I’m like, “Guys, what is wrong? Why did you let this team run crazy?” I hope at some point, Apple will go back to the drawing board. My understanding is that that’s what they are doing. They are going to have two devices, one smart glasses, an evolution of the Vision Pro, just focus on VR. They might actually abandon the concept of the pure VR-oriented headset. Because, from a market size perspective, it might not be big enough for Apple, quite frankly. Nuno Goncalves Pedro I read on all of the above, and people at this point was like, “Why are then players like Samsung and others not doing it. LG, et cetera?” Because those players historically have not invented new categories. They’re amazing at catching up once the category is invented, and then they scale the hell out of it, and that’s what these companies have been exceptional at. I wouldn’t see a dramatic innovation, I think, in terms of devices coming from any of the big ones on that side of the fence. Not to disrespect them in any way, but I think that’s not been their playbook ever. Again, if the origination doesn’t come from a start-up or from an Apple, I don’t see those guys going after it. My bet is that we’ll see some start-up activity and, again, hopefully, some announcement from IO now within the OpenAI world. Bertrand Schmitt I would slightly disagree with you. I see where you are coming from. But take the Samsung Galaxy Note, that sudden much bigger headphone that no one was doing that was launched by Samsung, at some point, it forced Apple to launch an iPhone Max. Let’s look at the Z Fold that Samsung launched 7 years ago, copied by everyone. Now Samsung launching a trifold. Apple has still not launched their foldable phone. I think there is a mix, actually, of sometimes- Nuno Goncalves Pedro For me, that’s not a proper new category. It’s still a mobile phone. It just happens to have a screen that folds in half. Bertrand Schmitt The iPhone was still a mobile phone, you could argue. Nuno Goncalves Pedro No. I think the iPhone was… I could actually agree with you on that point. Maybe Apple is not as innovative in that case. I think what Steve Jobs was exceptionally good at in terms of his ability as this master product manager was to be an exceptional curator of user flows and user experiences, and creating incredible experiences from devices based on that. That was his secret sauce. Could you say, “Wasn’t all of this stuff already around?” It was. You just put it all together very neatly and very nicely. But if you’re talking about significant shifts in how a category is done, the iPhone was a significant shift in how the category was done. The Fold is still an interesting device. I actually have a Fold right now in front of me. The 7 that you highly recommended to me that we both got, the Z Fold 7. I think they do amazing devices. I don’t think they normally are the most innovative players. Then, when they come to innovation, it comes from technology edges. Obviously, they have Samsung Display, there’s a bunch of other things. They had the ability to do foldable screens in-house themselves. Bertrand Schmitt I don’t disagree with you. I think there is an interesting situation where some companies have some strengths, another one has some strengths. My worry with Apple is that this was not demonstrated with the Vision Pro. The Vision Pro was a hot pot of technologies barely integrated together, with use cases absolutely not well-defined and certainly not something that makes sense for most of us. There is a question of has Apple lost it? While Samsung actually keeps doing their own stuff, that, yes, might be more minor improvements, but at least they are doing it. Because it looks like Apple is missing the train on even the minor improvements. By the way, you might not be aware, but Samsung launched its Vision Pro competitor. Interestingly enough, it might be a better product in some ways, being much lighter and much more comfortable. Nuno Goncalves Pedro We should play around with that and report back to our listeners. Of Start-ups and VCs Moving to venture capital and the startup ecosystem and what’s happening there, I think it is very much a bifurcated environment, and it’s bifurcated for both VCs and for startups. If you’re a startup in the AI space, and you have the hottest team since sliced bread, and you can create FOMO at the speed of light, you can raise ridiculous rounds. Five hundred million at the $3 billion, or $4 billion, or $5 billion valuation, and you still haven’t really even started. First round, you can raise 500 million. That’s back to the whole discussion on Bubble and where are we, et cetera. Some of these companies might actually become huge, some of them might not. But definitely, we are seeing really the haves and have-nots on the startup ecosystem with incredible teams raising a lot of money very, very early on or mid-stage if they’ve already existed for a while, and then the rest not being able to raise. We see a lot of non-necessarily AI sectors, some of the areas of SaaS that don’t necessarily have AI in it, or fintech, or the consumer space that are really, really struggling. If you don’t have an AI story for your startup right now, it’s extremely difficult to raise money unless your numbers are just the best numbers ever. That’s, I think, the first part of the element of bifurcation that we’re seeing today. The second element of bifurcation that we’re seeing today in terms of fundraising is for VCs themselves, and really propelled by the large VC firms raising more and more capital in recent orbits, announcing 15 billion across funds raised. Lightspeed, I think, had made an announcement a couple of weeks ago as well. They’ve raised a bunch of money as well. The big guys are all raising a lot of money. At some point in time, the question some of you might ask is, “These VCs are redeploying more and more money if they have a couple of billion for a VC fund. How does that look like? Is that still VC?” My perspective, I’ve shared before in some of our previous episodes, is that that’s no longer venture capital. At that point in time, we’re talking about something else. Private equity hedge funds, if you want to call them, maybe funds that are really driven by growth investment or late-stage investment. If you have a couple of billion under management, you’re not going to make your returns by writing a $3 million check in a series seed and leading that round. That has implications for everyone in the ecosystem. It has implications for smaller funds that obviously have a lot more difficulty in raising capital. It’s difficult to differentiate. Last but not least, also for startups that really continue searching for that capital that is out there. Andreessen Horowitz, for example, runs Speedrun, which is a great program for companies around consumer in particular. Initially, it was a lot for gaming. But at some point in time, Andreessen Horowitz could decide that they don’t want to invest more in you. They just put money from Speedrun, which is obviously a very small check compared to the very large checks they could write mid to late stage and that will have an effect on you as a startup. What happens at that point in time if Andreessen Horowitz is not backing you up in later stages? More than that, what happens if I can’t get these big funds interested in me? Are the small funds still valuable to me? Punchline, my view is yes. Obviously, we’re a smaller fund, so there’s parochial interest in what I’m saying. Small funds can still create a ton of value for you, also in terms of credibility, ability to accompany you in those first stages of investment, and the ability to bring other larger investors later down the road as well. There’s definitely a big movement happening in terms of the fundraising for VC funds, which we shouldn’t neglect, which is the big guys are raising a lot more capital and are therefore emptying the market to smaller funds that are having more and more difficult raising at this point in time. We had discussed that there would be a need for concentration in the industry, that micro funds would need to concentrate, and we didn’t have the space for so many micro funds as we had around. But the way it’s happening is extremely dramatic at this moment in time. I think it will continue through 2026. Bertrand Schmitt Remember a few years ago, with the rise of AI, there was more and more of the question about, “What’s the point of SaaS at this stage?” Because SaaS was around for 15 years. Basically, how do you come up with something new that was not already tested, validated by the market? How do you bring something new? We say this was reinforced to the power of 10. If your product is not clearly built from the ground up for a new use case enabled by AI, anyone could then might have built your product 5, 10 years ago, and therefore, why now has no clear answer, and it’s a big problem. I’m still surprised myself to still see some entrepreneurs where you talk to them about AI because you don’t see them in the deck, and they explain to you, “It’s not yet there,” and you’re like, “What’s wrong with you guys?” Fine. Do whatever you want. Do a small business and whatever, but don’t think you can come up pitch and raise without an AI story. The second category is people who come with an AI story, but you can feel very quickly, I guess you saw that many times, Nuno, where just a story layered on top with little credibility. It’s not better. It’s not enough to just have a story. Your business needs to be radically built differently or radically proposing some brand-new use cases that were impossible to solve 5 years ago. Nuno Goncalves Pedro To stack up on that, absolutely in agreement. If you’re just adding to the story, and it’s an afterthought, and you’re just trying to make the story somehow gel, once you go into one or two layers of due diligence, your investors will very quickly realise that you’re not really AI-first or dramatically AI-enabled or whatever. It’s just you’re sort of stacking something on top of another thesis. It needs to make sense from the product onwards. It’s not just, let’s just put it together with chewing gum, and magically, people will give you money. It was true also if we remember the good old crypto blockchain days, where everyone’s investing in crypto. A lot of stories that didn’t make much sense. In that sense, it’s not very different. I would go one step further. I think in the world of the VC winter that we’re a little bit in, where it’s more and more difficult if you’re a smaller fund to raise your fund at this moment in time, there’s a lot of sources of distinctiveness still talked about, like proprietary networks, access to deal flow, fast track record, all that stuff that really, really matters. But our bet continues at Chamaeleon continues being that you need to be AI-first as a VC fund yourself. You need to have core advantages in using not only readily-available AI tools or third-party available AI tools, data sources, technology stacks, but actually building your own stack over time, which is what we did with Mantis at Chamaeleon. Again, just to reinforce that, I think we’re at the beginning of that stage. We, Chamaeleon, are ahead of the game, but we think that the rest of the market will have to move towards that as well. Still, to be honest, very surprising to me to see that many significant large players are doing very little still around some of these spaces. They have data scientists. They’re running some tools. They’re running some analysis and all that stuff, but it’s still, again, back to the point I was making for startups, all glued up with chewing gum. It doesn’t all come together nicely, which it does need to from a platform standpoint. Bertrand Schmitt It’s quite surprising. I agree with you that some VC funds might think that they can do business as usual in that brand-new world. It’s difficult to believe. Nuno Goncalves Pedro Maybe moving a little bit toward the capital formation piece. We already discussed the M&A space really accelerating. We’ve also discussed the IPO market and some predictions on that. Secondaries, there’s obviously a lot of liquidity coming from secondaries from mid to late stage. I think it will continue throughout the rest of 2026. A lot of activity in buying, selling in secondaries as some asset managers are becoming more distressed, as some very high net worth individuals and family offices are becoming more distressed as well, at the same time, where there’s a lot of opportunities to potentially arbitrage around some investments. I believe a lot of money will be made and lost this year by decisions made this year, just to be very, very clear in terms of equity, purchases, et cetera. Exciting year ahead of us. Definitely a very, very interesting market ahead of us. Secondaries, M&A, growth, and late-stage investing, also, early-stage investing will continue just for those that were wondering. Last but not least, the public markets, the IPO market as well. Bertrand Schmitt One of the big questions for the IPO market would be, will SpaceX go public? Would it be good for the startup ecosystem? Because suddenly that they go public, it would be to raise money. If they raise money, will there be any money left for anybody else? That would be an interesting test of the market. For sure, it would be proof that market are risk on financing a new IPO like this one. Or as you said, maybe there is no IPO, and it’s a merger with Tesla. Time will tell. Nuno Goncalves Pedro Regulatory & Geopolitical Headwinds… and the Wars Moving maybe to our topic of regulation and geopolitical headwinds, as we’re seeing … definitely not tailwinds. The Google antitrust verdict and, obviously, the remedies are expected to come forward now, and a lot of people are saying, “There are some risks of structural separation.” What do you think? Is it cool, but nothing will happen in the end dramatically? Alphabet or Google? I’m not sure, actually. It’s Google LLC. I think that’s the case. It’s The United States versus Google LLC. Bertrand Schmitt I’m not sure. Personally, I’m not a big fan. I think there needs to be a better way to manage some anticompetitive behavior. I’m not a big fan. There was this temptation to do that for Microsoft 25 years ago. Look at what happened. No one needed to buy Microsoft to leave space for others. I see the same with Google, and I guess they are happy to not be the number 1 in AI today, but to have an open AI in front of them. Even if they are doing a great job, by the way, to move forward and go faster and faster. Personally, quite impressed now with some of what they have released. Gemini 3 is doing great from my perspective. I’m not a big fan of this. I think to be clear, it’s important that bigger companies don’t behave anticompetitively, but at the same time, we need to find the right approach where it’s not about breaking these companies, and it’s also not about forbidding them to do acquisitions. Because then you end up with what NVIDIA just did with a $20 billion acquihire IP licensing type of acquisition, because they didn’t want to have the uncertainties. They didn’t want to wait 1–2 years in order to acquire the people and the technology, so they organised it in a different way. But I don’t like that. I think they should be able to acquire companies without facing so much uncertainty. To be clear, it’s not new. Uncertainty when you are Google, NVIDIA, or others, it happens. It has happened for a decade plus, 2 decades. I think there needs to be, for sure, some safety valves. At the same time, we want an efficient capital market. An efficient capital market need companies that can acquire other companies. If you don’t do that efficiently, it will be worse for the entrepreneurs, it will be worse for the investors, it will be worse for everybody. I think we have not reached a good equilibrium from my perspective. We need more efficient acquisition process. And at the same time, we need to also enforce faster anticompetitive behavior. Because what you talk about concerning Google, this is a case that was what? That is 10 years old. You see what I mean? This is way too long. If you’re a startup, you are dead by then. It’s like the story of Netscape facing Microsoft. They were dead long after the fact. I think we need a different approach. I’m not sure the best answer. I’m not sure we’ll get a better approach. There are probably too many vested interest. My hope is that it will get better with this current administration because, certainly, the past administration was very anti acquisition and efficient markets. Nuno Goncalves Pedro We’ve talked about the European Union AI Act a bunch of times, so I don’t want to spend too many cycles on that. The only effect that I would say is we are seeing in very slow motion the splitting of the Internet. I once had Tim Berners-Lee, by the way, shouting at me that we were going to break the Internet when we were applying for the .mobi top-level domain. I was part of that consortium that eventually did get the .mobi top-level domain, and I had him shouting at us. But, apparently, this is going to split the Internet, Tim. So in case you’re listening. Because it will create all these different rules. If your data is relating to consumers there, then it’s treated in a different way, and The US is… Well, obviously, we have the case of California with its own rules and laws. I don’t know. I feel we’re having a moment of siloing that goes beyond economic and geopolitical siloing. It will also apply to the digital world, and we’ll start having different landscapes around it. We’ll see how this affects global expansion of services, for example, around AI, particularly for consumer, but I don’t foresee anything dramatically positive. Recently, we had the whole deal around TikTok finally having a solution for their US problem where there’s now a US conglomerate magically that owns it. The conglomerate doesn’t magically own it, they just straight up own it for the US. But it was driven by many of these concerns around data ownership. Where’s the data? Where is it based? I think a lot of other concerns that have to do with the geopolitics of China, obviously, being the basis of ByteDance, the owner of TikTok, that still is a significant owner, by the way, in TikTok in US. Then also the interest in the economics of making money out of something as powerful as TikTok, to be honest, in The US. Just to be clear, I don’t think this was all about the best interests of consumers. It was also about money. Just follow the money. Bertrand Schmitt There are for sure, some powerful interest at play. But let’s be clear. I think one is data, as you rightfully said, but the other one is algorithm. It’s not as if China is authorising any competitor on its territory. They have blocked access to most of the Internet platforms from the US, either finding new rules or just trade blocking them. So I don’t think it’s fair competition. You don’t want some of that data in China about the US or European consumer. Three, it’s about the algorithm. If suddenly, you are a foreign power, and you can as we know in China, you better follow what’s required of you from the Chinese Communist Party. You cannot take a chance with influencing other stuff like elections in other countries. It’s fair from the US perspective. One could even argue it’s fair from a Chinese perspective to want that. I think the only one in the middle who doesn’t really know what they want is Europe because on one side, they want to benefit from American platforms, on the other end, they want to have some controls. On the other end, they don’t create the environment for startups to flourish. So in that weird situation where they have to accept some control by the big US providers and either provider of underlying infrastructure or provider of consumer business facing services. Then they try to regulate them. But I think they are misunderstanding the power relationship, and I think some of this regulation would get some blowback, at least by the current administration. Just, I believe, this morning, there was some news around X being under a criminal investigation in France. This is not going to end well for the French startup and VC ecosystem. This is not going to end well for France and Europe when you depend so much from your American friends. Nuno Goncalves Pedro Regulation will be weaponised. Regulation constraints around exports, all of this will be weaponised geopolitically, and the bigger guys will normally win. I think that’s normally what we’ve seen. Just on TikTok just to… And you guys, if you’re listening to us, just see if you see a pattern here, but obviously, 19.9% still owned by ByteDance of the TikTok entity in the US. It was initially said that 80% of the TikTok entity is owned by non-Chinese investors. Initially, people were saying US investors, and then they changed it to non-Chinese because MGX, I think, has 15% of it. MGX is based in the UAE, connected obviously to Mubadala, the Abu Dhabi sovereign wealth fund. Silver Lake is in there, I think, with 15% as well. Oracle as well with 15%. Those three are the big bucket owners together, 45%. Silver Lake having collaborated with MGX before, and I’m sure a lot of connectivity there. Then you still see a pattern in this in terms of shareholders. If you don’t, then just Google it. Dell Family Office, Vastmir Strategic Investments, which is owned by billionaire Jeff Yass, Alpha Wave Partners, obviously involved with a bunch of things like SpaceX and Klarna, Virgoli, Revolution, which is Steve Case’s, a former founder of AOL, is also in there. Meritway, which is managed by partners, I think, of Dragonair. Vinova from General Atlantic, an affiliate of General Atlantic. Also, NJJ Capital, which I believe is Xavier Nil, the French billionaire that founded Iliad. Mostly American, I think, if the math is correct. 80% non-Chinese, which was what mattered, I think, in many cases. But do see if you saw a pattern in most of those investors. I won’t say anything more than that. Maybe moving to other topics, maybe just to finalise on regulation and geopolitics. In geopolitics, we should talk about wars if we predict anything. Not that we are nasty and one want to be negative, but what the hell is going on? Will we have ending to the wars we already have ongoing or not? But before that, the struggles on the App Stores, I think, will continue both for Apple and for Google Play Store. The writing’s on the wall, the EU keeps pushing it dramatically and Apple keeps just doing stuff. I’m on the board of an App Store company. Apple just creates all these things that basically make you not really… It doesn’t work. You can’t provision then an App Store on Apple devices. On iPhones, et cetera. We’ll see how that will continue going, but I feel the writing’s on the wall. Both Apple and Google will have to open up a bit more of their platforms. I’m not sure it will have a huge impact in the medium to long term, but definitely we need to see more openness in access to apps as given by the two big platform owners, Apple and Google, out there. Bertrand Schmitt Let’s be clear. Google is way more open than Apple. We both have Android devices. You can install alternative app stores. It’s a different ballgame by very far. Nuno Goncalves Pedro Google does other nasty stuff. It’s public. You can check which board I’m a part of. You can see what that company has done towards Google over time. But to your point, yes. It is true that Google has been more open than Apple, but Google has done their own things. Just to be very clear, so I’ll just leave that caveat bracketed there for people to think about it and maybe read a little bit about it as well. Bertrand Schmitt I can say that, me, from my perspective, that path of total control that Apple has been going through on all their devices, that includes macOS, pushed me to, over the past 2, 3 years, to completely live and abandon the Apple ecosystem. I just couldn’t accept that level of control, that golden handcuff approach of the Apple ecosystem, each their own obviously, they are golden, their handcuffs, but they are still handcuffs. Personally, that pushed me way more to Linux, Android, Windows, back to Windows after all these years. I just couldn’t stand it anymore. I want to pick my devices. I want to pick what I install on them, and I don’t want to be controlled like this by just one entity for all my tech devices. For me, at some point, it was just not acceptable anymore. It’s still very warm, very golden handcuffs, but for me, they were just handcuffs at this stage. Yes, what they are doing with the App Store is very typical of that mindset. I think it’s quite sad because I think it started with good intention in some ways. “We need a new computing paradigm, we need to make things smoother and safer,” but it has really become a way to control your clients. For me, it has reached a point where it’s just way too much. Nuno Goncalves Pedro There’s obviously the great power comes great responsibility that uncle Ben told Spider-Man or Peter Parker. But there’s also with great power comes shitload of money, and control. So it’s like, “Yeah. Should we open the server? Do we want to delay opening it up?” “Yeah.” Anyway, it is what it is. Maybe let’s end on the more difficult note of the episode, which is going to be around wars. What’s our prediction? Will we have an end to the Gaza situation with Israel? Will we have an end to Ukraine and, obviously, Russia? What will happen in Iran? Those are the three big, big conflicts right now. Then, obviously, if we want to add just bonus points, what’s going to happen to Greenland, and what’s going to happen to Taiwan, and what’s going to happen to Venezuela? Let’s throw the whole basket in there. We’ve never had like… Let’s talk about all these territories and all these countries. At some point in time, I’m saying this in a light manner, but it’s obviously more tragic than it should be light, and people are dying, and there’s a lot of implications of all of that that is happening right now. Do you have any predictions, Bertrand, for this year? Bertrand Schmitt No. It’s tough to predict on an individual basis. I think on a more bigger picture basis is on one side, obviously, the rise of China on one side. You have also the rise of other countries like India, while very indirectly connected to some of these conflicts are still part of the game, buying oil from Russia, for instance. At the same time, I think overall, the US is more clear about with the sheriff in town. I think it’s good because in some ways, you cannot pay for the goods, you cannot have such a massive advantage versus nearly every other country on earth and just not be clear about who is the boss in some ways. As a result, what are the rules of the game and how it should be played? The US is not alone, obviously, you have China, you have Russia, you have India, you have Europe. You have different other countries. But at some point, it’s not good when countries are not rational and are not clear. I think I prefer the current situation where things are more clear and where you have to assume responsibilities about what you are doing. It’s time to be rational again about how the world behave. Yes, the concept of power and balance of power. I think there has been that dream, maybe mostly coming from Europe, about the end of history. I think that’s simply not the case. It’s not the end of history. It’s still about the balance of power. It has always been about the balance of power. If you are dumb enough to think it was not about that anymore, I just have a bridge to nowhere to sell you. I don’t have specific prediction, but I think it’s clear there is a new sheriff in town. There is a new doctrine about the Western Hemisphere that has been in some ways resurrected on the [inaudible 00:51:35] train, and I think we’ll see more of it. I think at this point, the biggest question is for the Europeans. What do they want to do? Because right now, their position of being a dwarf militarily while being a pretty big giant economically, I don’t think it works. Nuno Goncalves Pedro I agreed on everything that you said. I do have predictions. I’ll stick a flag on the ground just with my predictions. Bertrand Schmitt Good luck. Nuno Goncalves Pedro They are mostly positive. I do think we’ll see an end or, for the most, end to the two big conflicts, the one in Gaza and the one in Ukraine. I think Ukraine will end up in readjustment of territory and splitting between Russia and the Ukraine, but the end of hostilities, I think that we will see an end to the conflict in Gaza also with a readjustment on what that will mean for the Palestinian territories and the Palestinians in general. That I’m not sure, but I feel that there will be an end to those two big conflicts. Iran, I have no clue. I will not put a stick on the ground that I have no clue. There are so many things that could go wrong there. I’ve been reading some really interesting thoughts about even some aggressive thoughts that this might be the time to really change regimes in Iran and for the US to have a bit more of an aggressive stance. I really don’t have a perspective. Obviously, there’s a lot at stake there. Then, if we talk about the other parts, Greenland, I will not opine too much on. Maybe we’re done for now. Maybe there’ll be some other concessions to the US that weren’t already there in the ’50s. Taiwan, I won’t bet either. I’m sad to say I think it might happen at some point in time, but I’m not sure when and what would drive it. Last but not the least, Venezuela is my only really negative prediction. I feel it will continue to be a significant dictatorship as it was before managed enough by other people with the difference now that it has a tax to be paid to the US in the form of oil of some sort, etcetera, and maybe gas, maybe other things as well that it didn’t have before. That’s probably my most negative prediction for the coming year on the geopolitical side. Bertrand Schmitt Without going into detail, I would mostly agree with what you shared. At least that makes sense. But as we know, it’s not always what makes sense, but what might happen. I can tell you 100% I would not have guessed this operation against Maduro. This was so well done, well executed, and shocking at the same time that it’s… I think it shows that it’s hard to guess some of this stuff because there are certainly some new ways to wage limited war, for instance. So it’s certainly interesting, and we certainly need to get used to pretty bombastic statements. But for Venezuela, I don’t think it can be worse than what it was before. I’m probably more optimistic that gradually it can get better. Nuno Goncalves Pedro Just to put perspective on why we’re not making predictions on some of these elements, I think this is a funny story, but I was in Madeira. Actually, first time I was in Madeira, although I’m originally from Portugal. I’ve never been to the islands. Obviously, as you guys know, or some of you might know, there’s a lot of connection between Madeira and Venezuela. There’s a lot of immigration from Madeira Islands to Venezuela. One of my Uber or Bolt drivers there in Madeira was Venezuelan. Was born in Venezuela, but Portuguese descent, et cetera. He was telling me this was still last year. Late last year. Because I told him I lived in US, et cetera, and he was like, “Oh, hopefully, Trump will get Maduro out of there.” In my mind, I was like, “Dude.” No disrespect to the gentleman, but it’s like, “Okay. Mike, your perspective on geopolitics is maybe a little bit exaggerated.” And a couple of days later, we know what happened. When geopolitical decisions are better predicted by some probably very astute Uber drivers, you’re like, “Maybe I shouldn’t make a bet. I have no clue what’s going to happen, no clue what’s going to happen in Greenland, et cetera.” Anyway, a couple of predictions on that element. Bertrand Schmitt That’s why it’s so right. You have to be careful with the prediction, but it doesn’t remove the fact that I think nations and companies that have to play a global game have to understand in some ways what is the game, what are the powers in place, what could happen potentially, but also be realistic. Not be about wish and dreams, but more about, what’s the power relationship? Who has the money? Who has the means? Who has the capacity to do this or that? Because if you start that way, at least the scope of what’s possible, what’s reasonable is more and more clear more quickly. Some stuff like happened with Maduro, I would never have predicted, but for sure, if there’s one country that can do this sort of stuff, it’s the US. I’m not sure anyone has a technology and the means in terms of support infrastructure to do something like this. It’s tough to predict what will happen a year from now for any specific country, but I think that even trying to get a better understanding about the forces in play and their capacity and understanding and accepting that at some point, it’s all about real politic and relationship of power, the more your eyes would be wide open about what’s possible versus simple, wishful thinking. Nuno Goncalves Pedro Fintech, Crypto and Frontier Tech Moving maybe to our last section around fintech, crypto, and frontier tech. For me, just two very quick predictions, views of the world. I think on the frontier tech side, I won’t make a prediction. I will just tell you all to go and listen to our episodes, the one on infrastructure, which is immediately prior to this one, and the episodes that we’ve had around a couple of other topics including AI, what’s the future of your children, because I think they illustrate a lot of the points that we’re seeing and manifesting themselves over the next year and over the next 2 or 3 years as well beyond that. I feel those tomes are complete in and out of themselves, so you can just go and listen to them. Then my second comment is on crypto. I feel crypto has become of the essence, particularly under the current administration in the US, very favored. Obviously, we are now in a world where crypto is just part of the economic system, and I think we’ll see more and more of that emerging, and in some ways, crypto is becoming mainstream. Question is what blockchains will be the blockchains of the future? Obviously, there’s a bunch of bets put out there. We, ourselves, as Chamaeleon, have one investment in one of the significant bets in the space. But besides that, who’s going to win or not, we feel that we’re past the crypto winter. It’s now mainstream days, and we’ll see a lot more activity in there. Bertrand Schmitt I must say with crypto, I’m a bit confused. As you say, we are past the crypto winter. There is much less uncertainty in regul
The reception to our recent post on Code Reviews has been strong. Catch up!Amid a maelstrom of discussion on whether or not AI is killing SaaS, one of the top publicly listed SaaS companies in the world has just reported record revenues, clearing well over $1.1B in ARR for the first time with a 28% margin. As we comment on the pod, Aaron Levie is the rare public company CEO equally at home in both worlds of Silicon Valley and Wall Street/Main Street, by day helping 70% of the Fortune 500 with their Enterprise Advanced Suite, and yet by night is often found in the basements of early startups and tweeting viral insights about the future of agents.Now that both Cursor, Cloudflare, Perplexity, Anthropic and more have made Filesystems and Sandboxes and various forms of “Just Give the Agent a Box” cool (not just cool; it is now one of the single hottest areas in AI infrastructure growing 100% MoM), we find it a delightfully appropriate time to do the episode with the OG CEO who has been giving humans and computers Boxes since he was a college dropout pitching VCs at a Michael Arrington house party.Enjoy our special pod, with fan favorite returning guest/guest cohost Jeff Huber!Note: We didn't directly discuss the AI vs SaaS debate - Aaron has done many, many, many other podcasts on that, and you should read his definitive essay on it. Most commentators do not understand SaaS businesses because they have never scaled one themselves, and deeply reflected on what the true value proposition of SaaS is.We also discuss Your Company is a Filesystem:We also shoutout CTO Ben Kus' and the AI team, who talked about the technical architecture and will return for AIE WF 2026.Full Video EpisodeTimestamps* 00:00 Adapting Work for Agents* 01:29 Why Every Agent Needs a Box* 04:38 Agent Governance and Identity* 11:28 Why Coding Agents Took Off First* 21:42 Context Engineering and Search Limits* 31:29 Inside Agent Evals* 33:23 Industries and Datasets* 35:22 Building the Agent Team* 38:50 Read Write Agent Workflows* 41:54 Docs Graphs and Founder Mode* 55:38 Token FOMO Culture* 56:31 Production Function Secrets* 01:01:08 Film Roots to Box* 01:03:38 AI Future of Movies* 01:06:47 Media DevRel and EngineeringTranscriptAdapting Work for AgentsAaron Levie: Like you don't write code, you talk to an agent and it goes and does it for you, and you may be at best review it. That's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work.We basically adapted to how the agent works. All of the economy has to go through that exact same evolution. Right now, it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this ‘cause you'll see compounding returns. But that's just gonna take a while for most companies to actually go and get this deployed.swyx: Welcome to the Lane Space Pod. We're back in the chroma studio with uh, chroma, CEO, Jeff Hoover. Welcome returning guest now guest host.Aaron Levie: It's a pleasure. Wow. How'd you get upgraded to, uh, to that?swyx: Because he's like the perfect guy to be guest those for you.Aaron Levie: That makes sense actually, for We love context. We, we both really love context le we really do.We really do.swyx: Uh, and we're here with, uh, Aaron Levy. Welcome.Aaron Levie: Thank you. Good to, uh, good to be [00:01:00] here.swyx: Uh, yeah. So we've all met offline and like chatted a little bit, but like, it's always nice to get these things in person and conversation. Yeah. You just started off with so much energy. You're, you're super excited about agents.I loveAaron Levie: agents.swyx: Yeah. Open claw. Just got by, got bought by OpenAI. No, not bought, but you know, you know what I mean?Aaron Levie: Some, some, you know, acquihire. Executiveswyx: hire.Aaron Levie: Executive hire. Okay. Executive hire. Say,swyx: hey, that's my term. Okay. Um, what are you pounding the table on on agents? You have so many insightful tweets.Why Every Agent Needs a BoxAaron Levie: Well, the thing that, that we get super excited by that I think is probably, you know, should be relatively obvious is we've, we've built a platform to help enterprises manage their files and their, their corporate files and the permissions of who has access to those files and the sharing collaboration of those files.All of those files contain really, really important information for the enterprise. It might have your contracts, it might have your research materials, it might have marketing information, it might have your memos. All that data obviously has, you know, predominantly been used by humans. [00:02:00] But there's been one really interesting problem, which is that, you know, humans only really work with their files during an active engagement with them, and they kind of go away and you don't really see them for a long time.And all of a sudden, uh, with the power of AI and AI agents, all of that data becomes extremely relevant as this ongoing source of, of answers to new questions of data that will transform into, into something else that, that produces value in your organization. It, it contains the answer to the new employee that's onboarding, that needs to ramp up on a project.Um, it contains the answer to the right thing to sell a customer when you're having a conversation to them, with them contains the roadmap information that's gonna produce the next feature. So all that data. That previously we've been just sort of storing and, and you know, occasionally forgetting about, ‘cause we're only working on the new active stuff.All of that information becomes valuable to the enterprise and it's gonna become extremely valuable to end users because now they can have agents go find what they're looking for and produce new, new [00:03:00] value and new data on that information. And it's gonna become incredibly valuable to agents because agents can roam around and do a bunch of work and they're gonna need access to that data as well.And um, and you know, sometimes that will be an agent that is sort of working on behalf of, of, of you and, and effectively as you as and, and they are kind of accessing all of the same information that you have access to and, and operating as you in the system. And then sometimes there's gonna be agents that are just.Effectively autonomous and kind of run on their own and, and you're gonna collaborate and work with them kind of like you did another person. Open Claw being the most recent and maybe first real sort of, you know, kind of, you know, up updating everybody's, you know, views of this landscape version of, of what that could look like, which is, okay, I have an agent.It's on its own system, it's on its own computer, it has access to its own tools. I probably don't give it access to my entire life. I probably communicate with it like I would an assistant or a colleague and then it, it sort of has this sandbox environment. So all of that has massive implications for a platform that manage that [00:04:00] enterprise data.We think it's gonna just transform how we work with all of the enterprise content that we work with, and we just have to make sure we're building the right platform to support that.swyx: The sort of shorthand I put it is as people build agents, everybody's just realizing that every agent needs a box. Yes.And it's nice to be called box and just give everyone a box.Aaron Levie: Hey, I if I, you know, if we can make that go viral, uh, like I, I think that that terminology, I, that's theswyx: tagline. Every agentAaron Levie: needs a box. Every agent needs a box. If we can make that the headline of this, I'm fine with this. And that's the billboard I wanna like Yeah, exactly.Every agent needs a box. Um, I like it. Can we ship this? Like,swyx: okay, let's do it. Yeah.Aaron Levie: Uh, my work here is done and I got the value I needed outta this podcast Drinks.swyx: Yeah.Agent Governance and IdentityAaron Levie: But, but, um, but, but, you know, so the thing that we, we kind of think about is, um, is, you know, whether you think the number 10 x or a hundred x or whatever the number is, we're gonna have some order of magnitude more agents than people.That's inevitable. It has to happen. So then the question is, what is the infrastructure that's needed to make all those agents effective in the enterprise? Make sure that they are well governed. Make sure they're only doing [00:05:00] safe things on your information. Make sure that they're not getting exposed. The data that they shouldn't have access to.There's gonna be just incredibly spectacularly crazy security incidents that will happen with agents because you'll prompt, inject an agent and sort of find your way through the CRM system and pull out data that you shouldn't have access to. Oh, weJeff Huber: have God,Aaron Levie: right? I mean, that's just gonna happen all over the place, right?So, so then the thing is, is how do you make sure you have the right security, the permissions, the access controls, the data governance. Um, we actually don't yet exactly know in many cases how we're gonna regulate some of these agents, right? If you think about an agent in financial services, does it have the exact same financial sort of, uh, requirements that a human did?Or is it, is the risk fully on the human that was interacting or created the agent? All open questions, but no matter what, there's gonna need to be a layer that manages the, the data they have access to, the workflows that they're involved in, pulling up data from multiple systems. This is the new infrastructure opportunity in the era of agents.swyx: You have a piece on agent identities, [00:06:00] which I think was today, um, which I think a lot of breaking news, the security, security people are talking about, right? Like you basically, I, I always think of this as like, well you need the human you and then there you need the agent. YouAaron Levie: Yes.swyx: And uh, well, I don't know if it's that simple, but is box going to have an opinion on that or you're just gonna be like, well we're just the sort of the, the source layer.Yeah. Let's Okta of zero handle that.Aaron Levie: I think we're gonna have an opinion and we will work with generally wherever the contours of the market end up. Um, and the reason that we're gonna have an opinion more than other topics probably is because one of the biggest use cases for why your agent might need it, an identity is for file system access.So thus we have to kind of think about this pretty deeply. And I think, uh, unless you're like in our world thinking about this particular problem all day long, it might be, you know, like, why is this such a big deal? And the reason why it's a really big deal is because sometimes sort of say, well just give the agent an, an account on the system and it just treats, treat it like every other type of user on the system.The [00:07:00] problem is, is that I as Aaron don't really have any responsibility over anybody else's box account in our organization. I can't see the box account of any other employee that I work with. I am not liable for anything that they do. And they have, I have, I have, you know, strict privacy requirements on everything that they're able to, you know, that, that, that they work on.Agents don't have that, you know, don't have those properties. The person who creates the agent probably is gonna, for the foreseeable future, take on a lot of the liability of what that agent does. That agent doesn't deserve any privacy because, because it's, you know, it can't fully be autonomously operated and it doesn't have any legal, you know, kind of, you know, responsibility.So thus you can't just be like, oh, well I'll just create a bunch of accounts and then I'll, I'll kind of work with that agent and I'll talk to it occasionally. Like you need oversight of that. And so then the question is, how do you have a world where the agent, sometimes you have oversight of, but what if that agent goes and works with other people?That person over there is collaborating with the agent on something you shouldn't have [00:08:00] access to what they're doing. So we have all of these new boundaries that we're gonna have to figure out of, of, you know, it's really, really easy. So far we've been in, in easy mode. We've hit the easy button with ai, which is the agent just is you.And when you're in quad code and you're in cursor, and you're in Codex, you're just, the agent is you. You're offing into your services. It can do everything you can do. That's the easy mode. The hard mode is agents are kind of running on their own. People check in with them occasionally, they're doing things autonomously.How do you give them access to resources in the enterprise and not dramatically increased the security risk and the risk that you might expose the wrong thing to somebody. These are all the new problems that we have to get solved. I like the identity layer and, and identity vendors as being a solution to that, but we'll, we'll need some opinions as well because so many of the use cases are these collaborative file system use cases, which is how do I give it an agent, a subset of my data?Give it its own workspace as well. ‘cause it's gonna need to store off its own information that would be relevant for it. And how do I have the right oversight into that? [00:09:00]Jeff Huber: One thing, which, um, I think is kind interesting, think about is that you know, how humans work, right? Like I may not also just like give you access to the whole file.I might like sit next to you and like scroll to this like one part of the file and just show you that like one part and like, you know,swyx: partial file access.Jeff Huber: I'm just saying I think like our, like RA does seem to be dead, right? Like you wanna say something is dead uhhuh probably RA is dead. And uh, like the auth story to me seems like incredibly unsolved and unaddressed by like the existing state of like AI vendors.ButAaron Levie: yeah, I think, um, we're, I mean you're taking obviously really to level limit that we probably need to solve for. Yeah. And we built an access control system that was, was kind of like, you know, its own little world for, for a long time. And um, and the idea was this, it's a many to many collaboration system where I can give you any part of the file system.And it's a waterfall model. So if I give you higher up in the, in the, in the system, you get everything below. And that, that kind of created immense flexibility because I can kind of point you to any layer in the, in the tree, but then you're gonna get access to everything kind of below it. And that [00:10:00] mostly is, is working in this, in this world.But you do have to manage this issue, which is how do I create an agent that has access to some of my stuff and somebody else's stuff as well. Mm-hmm. And which parts do I get to look at as the creator of the agent? And, and these are just brand new problems? Yeah. Crazy. And humans, when there was a human there that was really easy to do.Like, like if the three of us were all sharing, there'd be a Venn diagram where we'd have an overlapping set of things we've shared, but then we'd have our own ways that we shared with each other. In an agent world, somebody needs to take responsibility for what that agent has access to and what they're working on.These are like the, some of the most probably, you know, boring problems for 98% of people on, on the internet, but they will be the problems that are the difference between can you actually have autonomous agents in an enterprise contextswyx: Yeah.Aaron Levie: That are not leaking your data constantly.swyx: No. Like, I mean, you know, I run a very, very small company for my conference and like we already have data sensitivity issues.Yes. And some of my team members cannot see Yes. Uh, the others and like, I can't imagine what it's like to run a Fortune 500 and like, you have to [00:11:00] worry about this. I'm just kinda curious, like you, you talked to a lot like, like 70, 80% of your cus uh, of the Fortune 500, your customers.Aaron Levie: Yep. 67%. Just so we're being verySEswyx: precise.So Yeah. I'm notAaron Levie: Okay. Okay.swyx: Something I'm rounding up. Yes. Round up. I'm projecting to, forAaron Levie: the government.swyx: I'm projecting to the end of the year.Aaron Levie: Okay.swyx: There you go.Aaron Levie: You do make it sound like, like we, we, well we've gotta be on this. Like we're, we're taking way too long to get to 80%. Well,swyx: no, I mean, so like. How are they approaching it?Right? Because you're, you don't have a, you don't have a final answer yet.Why Coding Agents Took Off FirstAaron Levie: Well, okay, so, so this is actually, this is the stark reality that like, unfortunately is the kinda like pouring the water on the party a little bit.swyx: Yes.Aaron Levie: We all in Silicon Valley are like, have the absolute best conditions possible for AI ever.And I think we all saw the dke, you know, kind of Dario podcast and this idea of AI coding. Why is that taken off? And, and we're not yet fully seeing it everywhere else. Well, look, if you just like enumerated the list of properties that AI coding has and then compared it to other [00:12:00] knowledge work, let's just, let's just go through a few of them.Generally speaking, you bring on a new engineer, they have access to a large swath of the code base. Like, there's like very, like you, just, like new engineer comes on, they can just go and find the, the, the stuff that they, they need to work with. It's a fully text in text out. Medium. It's only, it's just gonna be text at the end of the day.So it's like really great from a, from just a, uh, you know, kinda what the agent can work with. Obviously the models are super trained on that dataset. The labs themselves have a really strong, kind of self-reinforcing positive flywheel of why they need to do, you know, agent coding deeply. So then you get just better tooling, better services.The actual developers of the AI are daily users of the, of the thing that they're we're working on versus like the, you know, probably there's only like seven Claude Cowork legal plugin users at Anthropic any given day, but there's like a couple thousand Claude code and you know, users every single day.So just like, think about which one are they getting more feedback on. All day long. So you just go through this list. You have a, you know, everybody who's a [00:13:00] developer by definition is technical so they can go install the latest thing. We're all generally online, or at least, you know, kinda the weird ones are, and we're all talking to each other, sharing best practices, like that's like already eight differences.Versus the rest of the economy. Every other part of the economy has like, like six to seven headwinds relative to that list. You go into a company, you're a banker in financial services, you have access to like a, a tiny little subset of the total data that's gonna be relevant to do your job. And you're have to start to go and talk to a bunch of people to get the right data to do your job because Sally didn't add you to that deal room, you know, folder.And that that, you know, the information is actually in a completely different organization that you now have to go in and, and sort of run into. And it's like you have this endless list of access controls and security. As, as you talked about, you have a medium, which is not, it's not just text, right? You have, you have a zoom call that, that you're getting all of the requirements from the customer.You have a lot of in-person conversations and you're doing in-person sales and like how do you ever [00:14:00] digitize all of that information? Um, you know, I think a lot of people got upset with this idea that the code base has all the context, um, that I don't know if you follow, you know, did you follow some of that conversation that that went viral?Is like, you know, it's not that simple that, that the code base doesn't have all the knowledge, but like it's a lot, you're a lot better off than you are with other areas of knowledge work. Like you, we like, we like have documentation practices, you write specifications. Those things don't exist for like 80% of work that happens in the enterprise.That's the divide that we have, which is, which is AI coding has, has just fully, you know, where we've reached escape velocity of how powerful this stuff is, and then we're gonna have to find a way to bring that same energy and momentum, but to all these other areas of knowledge work. Where the tools aren't there, the data's not set up to be there.The access controls don't make it that easy. The context engineering is an incredibly hard problem because again, you have access control challenges, you have different data formats. You have end users that are gonna need to kind of be kind of trained through this as opposed to their adopting [00:15:00] these tools in their free time.That's where the Fortune 500 is. And so we, I think, you know, have to be prepared as an industry where we are gonna be on a multi-year march to, to be able to bring agents to the enterprise for these workflows. And I think probably the, the thing that we've learned most in coding that, that the rest of the world is not yet, I think ready for, I mean, we're, they'll, they'll have to be ready for it because it's just gonna inevitably happen is I think in coding.What, what's interesting is if you think about the practice of coding today versus two years ago. It's probably the most changed workflow in maybe the history of time from the amount of time it's changed, right? Yeah. Like, like has any, has any workflow in the entire economy changed that quickly in terms of the amount of change?I just, you know, at least in any knowledge worker workflow, there's like very rarely been an event where one piece of technology and work practice has so fundamentally, you know, changed, changed what you do. Like you don't write code, you talk to an agent and it goes and [00:16:00] does it for you, and you may be at best review it.And even that's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work. We basically adapted to how the agent works. Mm-hmm. All of the economy has to go through that exact same evolution.The rest of the economy is gonna have to update its workflows to make agents effective. And to give agents the context that they need and to actually figure out what kind of prompting works and to figure out how do you ensure that the agent has the right access to information to be able to execute on its work.I, you know, this is not the panacea that people were hoping for, of the agent drops in, just automates your life. Like you have to basically re-engineer your workflow to get the most out of agents and, uh, and that, that's just gonna take, you know, multiple years across the economy. Right now it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this.‘cause [00:17:00] you'll see compounding returns, but that's just gonna take a while for most companies to actually go and get this deployed.swyx: I love, I love pushing back. I think that. That is what a lot of technology consultants love to hear this sort of thing, right? Yeah, yeah, yeah. First to, to embrace the ai. Yes. To get to the promised land, you must pay me so much money to a hundred percent to adopt the prescribed way of, uh, conforming to the agents.Yes. And I worry that you will be eclipsed by someone else who says, no, come as you are.Aaron Levie: Yeah.swyx: And we'll meet you where you are.Aaron Levie: And, and, and and what was the thing that went viral a week ago? OpenAI probably, uh, is hiring F Dees. Yeah. Uh, to go into the enterprise. Yeah. Yeah. And then philanthropic is embedded at Goldman Sachs.Yeah. So if the labs are having to do this, if, if the labs have decided that they need to hire FDE and professional services, then I think that's a pretty clear indication that this, there's no easy mode of workflow transformation. Yeah. Yeah. So, so to your point, I think actually this is a market opportunity for, you know, new professional services and consulting [00:18:00] firms that are like Agent Build and they, and they kind of, you know, go into organizations and they figure out how to re-engineer your workflows to make them more agent ready and get your data into the right format and, you know, reconstruct your business process.So you're, you're not doing most of the work. You're telling agents how to do the work and then you're reviewing it. But I haven't seen the thing that can just drop in and, and kinda let you not go through those changes.swyx: I don't know how that kind of sales pitch goes over. Yeah. You know, you're, you're saying things like, well, in my sort of nice beautiful walled garden, here's, there's, uh, because here's this, here's this beautiful box account that has everything.Yes. And I'm like, well, most, most real life is extremely messy. Sure. And like, poorly named and there duplicate this outdated s**tAaron Levie: a hundred percent. And so No, no, a hundred percent. And so this is actually No. So, so this is, I mean, we agree that, that getting to the beautiful garden is gonna be tough.swyx: Yeah.Aaron Levie: There's also the other end of the spectrum where I, I just like, it's a technical impossibility to solve. The agent is, is truly cannot get enough context to make the right decision in, in the, in the incredibly messy land. Like there's [00:19:00] no a GI that will solve that. So, so we're gonna have to kind of land in somewhere in between, which is like we all collectively get better at.Documentation practices and, and having authoritative relatively up-to-date information and putting it in the right place like agents will, will certainly cause us to be much better organized around how we work with our information, simply because the severity of the agent pulling the wrong data will be too high and the productivity gain of that you'll miss out on by not doing this will be too high as well, that you, that your competition will just do it and they'll just have higher velocity.So, uh, and, and we, we see this a lot firsthand. So we, we build a series of agents internally that they can kind of have access to your full box account and go off and you give it a task and it can go find whatever information you're looking for and work with. And, you know, thank God for the model progress, but like, if, if you gave that task to an agent.Nine months ago, you're just gonna get lots of bogus answers because it's gonna, it's gonna say, Hey, here's, here are fi [00:20:00] five, you know, documents that all kind of smell like the right thing. And I'm gonna, but I, but you're, you're putting me on the clock. ‘cause my assistant prompt says like, you know, be pretty smart, but also try and respond to the user and it's gonna respond.And it's like, ah, it got the wrong document. And then you do that once or twice as a knowledge worker and you're just neverswyx: again,Aaron Levie: never again. You're just like done with the system.swyx: Yeah. It doesn't work.Aaron Levie: It doesn't work. And so, you know, Opus four six and Gemini three one Pro and you know, whatever the latest five 3G BT will be, like, those things are getting better and better and it's using better judgment.And this sort of like the, all of these updates to the agentic tool and search systems are, are, we're seeing, we're seeing very real progress where the agent. Kind of can, can almost smell some things a little bit fishy when it's getting, you know, we, we have this process where we, we have it go fan out, do a bunch of searches, pull up a bunch of data, and then it has to sort of do its own ranking of, you know, what are the right documents that, that it should be working with.And again, like, you know, the intelligence level of a model six months ago, [00:21:00] it'd be just throwing a dart at like, I'm just, I'm gonna grab these seven files and I, I pray, I hope that that's the right answer. And something like an opus first four five, and now four six is like, oh, it's like, no, that one doesn't seem right relative to this question because I'm seeing some signal that is making that, you know, that's contradicting the document where it would normally be in the tree and who should have access.Like it's doing all of that kind of work for you. But like, it still doesn't work if you just have a total wasteland of data. Like, it's just not, it's just not possible. Partly ‘cause a human wouldn't even be able to do it. So basically if a, if a really, really smart human. Could not do that task in five or 10 minutes for a search retrieval type task.Look, you know, your agent's not gonna be able to do it any better. You see this all day long. SoContext Engineering and Search Limitsswyx: this touches on a thing that just passionate about it was just context engineering. I, I'm just gonna let you ramble or riff on, on context engineering. If, if, if there's anything like he, he did really good work on context fraud, which has really taken over as like the term that people use and the referenceAaron Levie: a hundred percent.We, we all we think about is, is the context rob problem. [00:22:00]Jeff Huber: Yeah, there's certainly a lot of like ranking considerations. Gentech surgery think is incredibly promising. Um, yeah, I was trying to generate a question though. I think I have a question right now. Swyx.Aaron Levie: Yeah, no, but like, like I think there was this moment, um, you know, like, I don't know, two years ago before, before we knew like where the, the gotchas were gonna be in ai and I think someone was like, was like, well, infinite context windows will just solve all of these problems and ‘cause you'll just, you'll just give the context window like all the data and.It's just like, okay, I mean, maybe in 2035, like this is a viable solution. First of all, it, it would just, it would just simply cost too much. Like we just can't give the model like the 5,000 documents that might be relevant and it's gonna read them all. And I've seen enough to, to start believing in crazy stuff.So like, I'm willing to just say, sure. Like in, in 10 years from now,swyx: never say, never, never.Aaron Levie: In, in 10 years from now, we'll have infinite context windows at, at a thousandth of the price of today. Like, let's just like believe that that's possible, but Right. We're in reality today. So today we have a context engineering [00:23:00] problem, which is, I got, I got, you know, 200,000 tokens that I can work with, or prob, I don't even know what the latest graph is before, like massive degradation.16. Okay. I have 60,000 tokens that I get to work with where I'm gonna get accurate information. That's not a lot of tokens for a corpus of 10 million documents that a knowledge worker might have across all of the teams and all the projects and all the people they work with. I have, I have 10 million documents.Which, you know, maybe is times five pages per document or something like that. I'm at 50 million pages of information and I have 60,000 tokens. Like, holy s**t. Yeah. This is like, how do I bridge the 50 million pages of information with, you know, the couple hundred that I get to work with in that, in that token window.Yeah. This is like, this is like such an interesting problem and that's why actually so much work is actually like, just like search systems and the databases and that layer has to just get so locked in, but models getting better and importantly [00:24:00] knowing when they've done a search, they found the wrong thing, they go back, they check their work, they, they find a way to balance sort of appeasing the user versus double checking.We have this one, we have this one test case where we ask the agent to go find. 10 pieces of information.swyx: Is this the complex work eval?Aaron Levie: Uh, this is actually not in the eval. This is, this is sort of just like we have a bunch of different, we have a bunch of internal benchmark kind of scenarios. Every time we, we update our agent, we have one, which is, I ask it to find all of our office addresses, and I give it the list of 10 offices that we have.And there's not one document that has this, maybe there should be, that would be a great example of the kind of thing that like maybe over time companies start to, you know, have these sort of like, what are the canonical, you know, kind of key areas of knowledge that we need to have. We don't seem to have this one document that says, here are all of our offices.We have a bunch of documents that have like, here's the New York office and whatever. So you task this agent and you, you get, you say, I need the addresses for these 10 offices. Okay. And by the way, if you do this on any, you know, [00:25:00] public chat model, the same outcome is gonna happen. But for a different kind of query, you give it, you say, I need these 10 addresses.How many times should the agent go and do its search before it decides whether or not, there's just no answer to this question. Often, and especially the, the, let's say lower tier models, it'll come back and it'll give you six of the 10 addresses. And it'll, and I'll just say I couldn't find the otherswyx: four.It, it doesn't know what It doesn't know. ItAaron Levie: doesn't know what It doesn't know. Yeah. So the model is just like, like when should it stop? When should it stop doing? Like should it, should it do that task for literally an hour and just keep cranking through? Maybe I actually made up an office location and it doesn't know that I made it up and I didn't even know that I made it up.Like, should it just keep, re should it read every single file in your entire box account until it, until it should exhaust every single piece of information.swyx: Expensive.Aaron Levie: These are the new problems that we have. So, you know, something like, let's say a new opus model is sort of like, okay, I'm gonna try these types of queries.I didn't get exactly what I wanted. I'm gonna try again. I'm gonna, at [00:26:00] some point I'm gonna stop searching. ‘cause I've determined that that no amount of searching is gonna solve this problem. I'm just not able to do it. And that judgment is like a really new thing that the model needs to be able to have.It's like, when should it give up on a task? ‘cause, ‘cause you just don't, it's a can't find the thing. That's the real world of knowledge, work problems. And this is the stuff that the coding agents don't have to deal with. Because they, it just doesn't like, like you're not usually asking it about, you're, you're always creating net new information coming right outta the model for the most part.Obviously it has to know about your code base and your specs and your documentation, but, but when you deploy an agent on all of your data that now you have all of these new problems that you're dealing withJeff Huber: our, uh, follow follow-up research to context ride is actually on a genetic search. Ah. Um, and we've like right, sort of stress tested like frontier models and their ability to search.Um, and they're not actually that good at searching. Right. Uh, so you're sort of highlighting this like explore, exploit.swyx: You're just say, Debbie, Donna say everything doesn't work. Like,Aaron Levie: well,Jeff Huber: somebody has to be,Aaron Levie: um, can I just throw out one more thing? Yeah. That is different from coding and, and the rest [00:27:00] of the knowledge work that I, I failed to mention.So one other kind of key point is, is that, you know, at the end of the day. Whether you believe we're in a slop apocalypse or, or whatever. At the end of the day, if you, if you build a working product at the end of, if you, if you've built a working solution that is ultimately what the customer is paying for, like whether I have a lot of slop, a little slop or whatever, I'm sure there's lots of code bases we could go into in enterprise software companies where it's like just crazy slop that humans did over a 20 year period, but the end customer just gets this little interface.They can, they can type into it, it does its thing. Knowledge work, uh, doesn't have that property. If I have an AI model, go generate a contract and I generate a contract 20 times and, you know, all 20 times it's just 3% different and like that I, that, that kind of lop introduces all new kinds of risk for my organization that the code version of that LOP didn't, didn't introduce.These are, and so like, so how do you constrain these models to just the part that you want [00:28:00] them to work on and just do the thing that you want them to do? And, and, you know, in engineering, we don't, you can't be disbarred as an engineer, but you could be disbarred as a lawyer. Like you can do the wrong medical thing In healthcare, you, there's no, there's no equivalent to that of engineering.Like, doswyx: you want there to be, because I've considered softwareJeff Huber: engineer. What's that? Civil engineering there is, right? NotAaron Levie: software civil engineer. Sure. Oh yeah, for sure. But like in any of our companies, you like, you know, you'll be forgiven if you took down the site and, and we, we will do a rollback and you'll, you'll be in a meeting, but you have not been disbarred as an engineer.We don't, we don't change your, you know, your computer science, uh, blameJeff Huber: degree, this postmortem.Aaron Levie: Yeah, exactly. Exactly. So, so, uh, now maybe we collectively as an industry need to figure out like, what are you liable for? Not legally, but like in a, in a management sense, uh, of these agents. All sorts of interesting problems that, that, that, uh, that have to come out.But in knowledge work, that's the real hostile environments that we're operating in. Hmm.swyx: I do think like, uh, a lot of the last year's, 2025 story was the rise of coding agents and I think [00:29:00] 2026 story is definitely knowledge work agents. Yes. A hundredAaron Levie: percent.swyx: Right. Like that would, and I think open claw core work are just the beginning.Yes. Like it's, the next one's gonna just gonna be absolute craziness.Aaron Levie: It it is. And, and, uh, and it's gonna be, I mean, again, like this is gonna be this, this wave where we, we are gonna try and bring as many of the practices from coding because that, that will clearly be the forefront, which is tell an agent to go do something and has an access to a set of resources.You need to be responsible for reviewing it at the end of the process. That to me is the, is the kind of template that I just think goes across knowledge, work and odd. Cowork is a great example. Open Closet's a great example. You can kind of, sort of see what Codex could become over time. These are some, some really interesting kind of platforms that are emerging.swyx: Okay. Um, I wanted to, we touched on evals a little bit. You had, you had the report that you're gonna go bring up and then I was gonna go into like, uh, boxes, evals, but uh, go ahead. Talk about your genetic search thing.Jeff Huber: Yeah. Mostly I think kinda a few of the insights. It's like number one frontier model is not good at search.Humans have this [00:30:00] natural explore, exploit trade off where we kinda understand like when to stop doing something. Also, humans are pretty good at like forgetting actually, and like pruning their own context, whereas agents are not, and actually an agent in their kind of context history, if they knew something was bad and they even, you could see in the trace the reason you trace, Hey, that probably wasn't a good idea.If it's still in the trace, still in the context, they'll still do it again. Uhhuh. Uh, and so like, I think pruning is also gonna be like, really, it's already becoming a thing, right? But like, letting self prune the con windowsswyx: be a big deal. Yeah. So, so don't leave the mistake. Don't leave the mistake in there.Cut out the mistake but tell it that you made a mistake in the past and so it doesn't repeat it.Jeff Huber: Yeah. But like cut it out so it doesn't get like distracted by it again. ‘cause really, you know, what is so, so it will repeat its mistake just because it's been, it's inswyx: theJeff Huber: context. It'sAaron Levie: in the context so much.That's a few shot example. Even if it, yeah.Jeff Huber: It's like oh thisAaron Levie: is a great thing to go try even ifJeff Huber: it didn't work.Aaron Levie: Yeah,Jeff Huber: exactly.Aaron Levie: SoJeff Huber: there's like a bunch of stuff there. JustAaron Levie: Groundhogs Day inside these models. Yeah. I'm gonna go keep doing the same wrongJeff Huber: thing. Covering sense. I feel like, you know, some creator analogy you're trying like fit a manifold in latent space, which kind is doing break program synthesis, which is kinda one we think about we're doing right.Like, you know, certain [00:31:00] facts might be like sort of overly pitting it. There are certain, you know, sec sectors of latent space and so like plug clean space. Yeah. And, uh, andswyx: so we have a bell, our editor as a bell every time you say that. SoJeff Huber: you have, you have to like remove those, likeswyx: you shoulda a gong like TPN or something.IfJeff Huber: we gong, you either remove those links to like kinda give it the freedom, kind of do what you need to do. So, but yeah. We'll, we'll release more soon. That'sAaron Levie: awesome.Jeff Huber: That'll, that'll be cool.swyx: We're a cerebral podcast that people listen to us and, and sort of think really deep. So yeah, we try to keep it subtle.Okay. We try to keep it.Aaron Levie: Okay, fine.Inside Agent Evalsswyx: Um, you, you guys do, you guys do have EVs, you talked about your, your office thing, but, uh, you've been also promoting APEX agents and complex work. Uh, yeah, whatever you, wherever you wanna take this just Yeah. How youAaron Levie: Apex is, is obviously me, core's, uh, uh, kind of, um, agent eval.We, we supported that by sort of. Opening up some data for them around how we kind of see these, um, data workspaces in, in the, you know, kind of regular economy. So how do lawyers have a workspace? How do investment bankers have a workspace? What kind of data goes into those? And so we, [00:32:00] we partner with them on their, their apex eval.Our own, um, eval is, it's actually relatively straightforward. We have a, a set of, of documents in a, in a range of industries. We give the agent previously did this as a one shot test of just purely the model. And then we just realized we, we need to, based on where everything's going, it's just gotta be more agentic.So now it's a bit more of a test of both our harness and the model. And we have a rubric of a set of things that has to get right and we score it. Um, and you're just seeing, you know, these incredible jumps in almost every single model in its own family of, you know, opus four, um, you know, sonnet four six versus sonnet four five.swyx: Yeah. We have this up on screen.Aaron Levie: Okay, cool. So some, you're seeing it somewhere like. I, I forget the to, it was like 15 point jump, I think on the main, on the overall,swyx: yes.Aaron Levie: And it's just like, you know, these incredible leaps that, that are starting to happen. Um,swyx: and OP doesn't know any, like any, it's completely held out from op.Aaron Levie: This is not in any, there's no public data which has, you know, Ben benefits and this is just a private eval that we [00:33:00] do, and then we just happen to show it to, to the world. Hmm. So you can't, you can't train against it. And I think it's just as representative of. It's obviously reasoning capabilities, what it's doing at, at, you know, kind of test time, compute capabilities, thinking levels, all like the context rot issues.So many interesting, you know, kind of, uh, uh, capabilities that are, that are now improvingswyx: one sector that you have. That's interesting.Industries and Datasetsswyx: Uh, people are roughly familiar with healthcare and legal, but you have public sector in there.Aaron Levie: Yeah.swyx: Uh, what's that? Like, what, what, what is that?Aaron Levie: Yeah, and, and we actually test against, I dunno, maybe 10 industries.We, we end up usually just cutting a few that we think have interesting gains. All extras, won a lot of like government type documents. Um,swyx: what is that? What is it? Government type documents?Aaron Levie: Government filings. Like a taxswyx: return, likeAaron Levie: a probably not tax returns. It would be more of what would go the government be using, uh, as data.So, okay. Um, so think about research that, that type of, of, of data sets. And then we have financial services for things like data rooms and what would be in an investment prospectus. Uhhuh,swyx: that one you can dog food.Aaron Levie: Yeah, exactly. Exactly. Yes. Yes. [00:34:00] So, uh, so we, we run the models, um, in now, you know, more of an agent mode, but, but still with, with kinda limited capacity and just try and see like on a, like, for like basis, what are the improvements?And, and again, we just continue to be blown away by. How, how good these models are getting.swyx: Yeah, I mean, I think every serious AI company needs something like that where like, well, this is the work we do. Here's our company eval. Yeah. And if you don't have it, well, you're not a serious AI company.Aaron Levie: There's two dimensions, right?So there's, there's like, how are the models improving? And so which models should you either recommend a customer use, which one should you adopt? But then every single day, we're making changes to our agents. And you need to knowswyx: if you regressed,Aaron Levie: if you know. Yeah. You know, I've been fully convinced that the whole agent observability and eval space is gonna be a massive space.Um, super excited for what Braintrust is doing, excited for, you know, Lang Smith, all the things. And I think what you're going to, I mean, this is like every enter like literally every enterprise right now. It's like the AI companies are the customers of these tools. Every enterprise will have this. Yeah, you'll just [00:35:00] have to have an eval.Of all of your work and like, we'll, you'll have an eval of your RFP generation, you'll have an eval of your sales material creation. You'll have an eval of your, uh, invoice processing. And, and as you, you know, buy or use new agentic systems, you are gonna need to know like, what's the quality of your, of your pipeline.swyx: Yeah.Aaron Levie: Um, so huge, huge market with agent evals.swyx: Yeah.Building the Agent Teamswyx: And, and you know, I'm gonna shout out your, your team a bit, uh, your CTO, Ben, uh, did a great talk with us last year. Awesome. And he's gonna come back again. Oh, cool. For World's Fair.Aaron Levie: Yep.swyx: Just talk about your team, like brag a little bit. I think I, I think people take these eval numbers in pretty charts for granted, but No, there, I mean, there's, there's lots of really smart people at work during all this.Aaron Levie: Biggest shout out, uh, is we have a, we have a couple folks at Dya, uh, Sidarth, uh, that, that kind of run this. They're like a, you know, kind of tag tag team duo on our evals, Ben, our CTO, heavily involved Yasha, head of ai, uh, you know, a bunch of folks. And, um, evals is one part of the story. And then just like the full, you know, kind of AI.An agent team [00:36:00] is, uh, is a, is a pretty, you know, is core to this whole effort. So there's probably, I don't know, like maybe a few dozen people that are like the epicenter. And then you just have like layers and layers of, of kind of concentric circles of okay, then there's a search team that supports them and an infrastructure team that supports them.And it's starting to ripple through the entire company. But there's that kind of core agent team, um, that's a pretty, pretty close, uh, close knit group.swyx: The search team is separate from the infra team.Aaron Levie: I mean, we have like every, every layer of the stack we have to kind of do, except for just pure public cloud.Um, but um, you know, we, we store, I don't even know what our public numbers are in, you know, but like, you can just think about it as like a lot of data is, is stored in box. And so we have, and you have every layer of the, of the stack of, you know, how do you manage the data, the file system, the metadata system, the search system, just all of those components.And then they all are having to understand that now you've got this new customer. Which is the agent, and they've been building for two types of customers in the past. They've been building for users and they've been building for like applications. [00:37:00] And now you've got this new agent user, and it comes in with a difference of it, of property sometimes, like, hey, maybe sometimes we should do embeddings, an embedding based, you know, kind of search versus, you know, your, your typical semantic search.Like, it's just like you have to build the, the capabilities to support all of this. And we're testing stuff, throwing things away, something doesn't work and, and not relevant. It's like just, you know, total chaos. But all of those teams are supporting the agent team that is kind of coming up with its requirements of what, what do we need?swyx: Yeah. No, uh, we just came from, uh, fireside chat where you did, and you, you talked about how you're doing this. It's, it's kind of like an internal startup. Yeah. Within the broader company. The broader company's like 3000 people. Yeah. But you know, there's, there's a, this is a core team of like, well, here's the innovation center.Aaron Levie: Yeah.swyx: And like that every company kind of is run this way.Aaron Levie: Yeah. I wanna be sensitive. I don't call it the innovation center. Yeah. Only because I think everybody has to do innovation. Um, there, there's a part of the, the, the company that is, is sort of do or die for the agent wave.swyx: Yeah.Aaron Levie: And it only happens to be more of my focus simply because it's existential that [00:38:00] we get it right.swyx: Yeah.Aaron Levie: All of the supporting systems are necessary. All of the surrounding adjacent capabilities are necessary. Like the only reason we get to be a platform where you'd run an agent is because we have a security feature or a compliance feature, or a governance feature that, that some team is working on.But that's not gonna be the make or break of, of whether we get agents right. Like that already exists and we need to keep innovating there. I don't know what the right, exact precise number is, but it's not a thousand people and it's not 10 people. There's a number of people that are like the, the kind of like, you know, startup within the company that are the make or break on everything related to AI agents, you know, leveraging our platform and letting you work with your data.And that's where I spend a lot of my time, and Ben and Yosh and Diego and Teri, you know, these are just, you know, people that, that, you know, kind of across the team. Are working.swyx: Yeah. Amazing.Read Write Agent WorkflowsJeff Huber: How do you, how do you think about, I mean, you talked a lot about like kinda read workflows over your box data. Yep.Right. You know, gen search questions, queries, et cetera. But like, what about like, write or like authoring workflows?Aaron Levie: Yes. I've [00:39:00] already probably revealed too much actually now that I think about it. So, um, I've talked about whatever,Jeff Huber: whatever you can.Aaron Levie: Okay. It's just us. It's just us. Yeah. Okay. Of course, of course.So I, I guess I would just, uh, I'll make it a little bit conceptual, uh, because again, I've already, I've already said things that are not even ga but, but we've, we've kinda like danced around it publicly, so I, yeah, yeah. Okay. Just like, hopefully nobody watches this, um, episode. No.swyx: It's tidbits for the Heidi engaged to go figure out like what exactly, um, you know, is, is your sort of line of thinking.Sure. They can connect the dots.Aaron Levie: Yeah. So, so I would say that, that, uh, we, you know, as a, as a place where you have your enterprise content, there's a use case where I want to, you know, have an agent read that data and answer questions for me. And then there's a use case where I want the agent to create something.And use the file system to create something or store off data that it's working on, or be able to have, you know, various files that it's writing to about the work it's doing. So we do see it as a total read write. The harder problem has so far been the read only because, because again, you have that kind of like 10 [00:40:00] million to one ratio problem, whereas rights are a lot of, that's just gonna come from the model and, and we just like, we'll just put it in the file system and kinda use it.So it's a little bit of a technically easier problem, but the only part that's like, not necessarily technically hard, it is just like it's not yet perfected in the state of the ecosystem is, you know, building a beautiful PowerPoint presentation. It's still a hard problem for these models. Like, like we still, you know, like, like these formats are just, we're not built for.They'reswyx: working on it.Aaron Levie: They're, they're working on it. Everybody's working on it.swyx: Every launch is like, well, we do PowerPoint now.Aaron Levie: We're getting, yeah, getting a lot, getting a lot of better each time. But then you'll do this thing where you'll ask the update one slide and all of a sudden, like the fonts will be just like a little bit different, you know, on two of the slides, or it moved, you know, some shape over to the left a little bit.And again, these are the kind of things that, like in code, obviously you could really care about if you really care about, you know, how beautiful is the code, but at the end, user doesn't notice all those problems and file creation, the end user instantly sees it. You're [00:41:00] like, ah, like paragraph three, like, you literally just changed the font on me.Like it's a totally different font and like midway through the document. Mm-hmm. Those are the kind of things that you run into a lot of in the, in the content creation side. So, mm-hmm. We are gonna have native agents. That do all of those things, they'll be powered by the leading kind of models and labs.But the thing that I think is, is probably gonna be a much bigger idea over time is any agent on any system, again, using Box as a file system for its work, and in that kind of scenario, we don't necessarily care what it's putting in the file system. It could put its memory files, it could put its, you know, specification, you know, documents.It could put, you know, whatever its markdown files are, or it could, you know, generate PDFs. It's just like, it's a workspace that is, is sort of sandboxed off for its work. People can collaborate into it, it can share with other people. And, and so we, we were thinking a lot about what's the right, you know, kind of way to, to deliver that at scale.Docs Graphs and Founder Modeswyx: I wanted to come into sort of the sort of AI transformation or AI sort of, uh, operations things. [00:42:00] Um, one of the tweets that you, that you wanted to talk about, this is just me going through your tweets, by the way. Oh, okay. I mean, like, this is, you readAaron Levie: one by one,swyx: you're the, you're the easiest guest to prep for because you, you already have like, this is the, this is what I'm interested in.I'm like, okay, well, areAaron Levie: we gonna get to like, like February, January or something? Where are we in the, in the timelines? How far back are we going?swyx: Can you, can you describe boxes? A set of skills? Right? Like that, that's like, that's like one of the extremes of like, well if you, you just turn everything into a markdown file.Yeah. Then your agent can run your company. Uh, like you just have to write, find the right sequence of words toAaron Levie: Yes.swyx: To do it.Aaron Levie: Sorry, isthatswyx: the question? So I think the question is like, what if we documented everything? Yes. The way that you exactly said like,Aaron Levie: yes.swyx: Um, let's get all the Fortune five hundreds, uh, prepared for agents.Yes. And like, you know, everything's in golden and, and nicely filed away and everything. Yes. What's missing? Like, what's left, right? LikeAaron Levie: Yeah.swyx: You've, you've run your company for a decade. LikeAaron Levie: Yeah. I think the challenge is that, that that information changes a week later. And because something happened in the market for that [00:43:00] customer, or us as a company that now has to go get updated, and so these systems are living and breathing and they have to experience reality and updates to reality, which right now is probably gonna be humans, you know, kinda giving those, giving them the updates.And, you know, there is this piece about context graphs as as, uh, that kinda went very viral. Yeah. And I, I, I was like a, i, I, I thought it was super provocative. I agreed with many parts of it. I disagree with a few parts around. You know, it's not gonna be as easy as as just if we just had the agent traces, then we can finally do that work because there's just like, there's so much more other stuff that that's happening that, that we haven't been able to capture and digitize.And I think they actually represented that in the piece to be clear. But like there's just a lot of work, you know, that that has to, you just can't have only skills files, you know, for your company because it's just gonna be like, there's gonna be a lot of other stuff that happens. Yeah. Change over time.Yeah. Most companies are practically apprenticeships.swyx: Most companies are practically apprenticeships. LikeJeff Huber: every new employee who joins the team, [00:44:00] like you span one to three months. Like ramping them up.Aaron Levie: Yes. AllJeff Huber: that tat knowledgeAaron Levie: isJeff Huber: not written down.Aaron Levie: Yes.Jeff Huber: But like, it would have to be if you wanted to like give it to an Asian.Right. And so like that seems to me like to beAaron Levie: one is I think you're gonna see again a premium on companies that can document this. Mm-hmm. Much. There'll be a huge premium on that because, because you know, can you shorten that three month ramp cycle to a two week ramp cycle? That's an instant productivity gain.Can you re dramatically reduce rework in the organization because you've documented where all the stuff is and where the answers are. Can you make your average employee as good as your 90th percentile employee because you've captured the knowledge that's sort of in the heads of, of those top employees and make that available.So like you can see some very clear productivity benefits. Mm-hmm. If you had a company culture of making sure you know your information was captured, digitized, put in a format that was agent ready and then made available to agents to work with, and then you just, again, have this reality of like add a 10,000 person [00:45:00] company.Mapping that to the, you know, access structure of the company is just a hard problem. Is like, is like, yeah, well, you just, not every piece of information that's digitized can be shared to everybody. And so now you have to organize that in a way that actually works. There was a pretty good piece, um, this, this, uh, this piece called your company as a file is a file system.I, did you see that one?swyx: Nope.Aaron Levie: Uh, yes. You saw it. Yeah. And, and, uh, I actually be curious your thoughts on it. Um, like, like an interesting kind of like, we, we agree with it because, because that's how we see the world and, uh,swyx: okay. We, we have it up on screen. Oh,Aaron Levie: okay. Yeah. But, but it's all about basically like, you know, we've already, we, we, we already organized in this kind of like, you know, permission structure way.Uh, and, and these are the kind of, you know, natural ways that, that agents can now work with data. So it's kind of like this, this, you know, kind of interesting metaphor, but I do think companies will have to start to think about how they start to digitize more, more of that data. What was your take?Jeff Huber: Yeah, I mean, like the company's probably like an acid compliant file system.Aaron Levie: Uh,Jeff Huber: yeah. Which I'm guessing boxes, right? So, yeah. Yes.swyx: Yeah. [00:46:00]Jeff Huber: Which you have a great piece on, but,swyx: uh, yeah. Well, uh, I, I, my, my, my direction is a little bit like, I wanna rewind a little bit to the graph word you said that there, that's a magic trigger word for us. I always ask what's your take on knowledge graphs?Yeah. Uh, ‘cause every, especially at every data database person, I just wanna see what they think. There's been knowledge graphs, hype cycles, and you've seen it all. So.Aaron Levie: Hmm. I actually am not the expert in knowledge graphs, so, so that you might need toswyx: research, you don't need to be an expert. Yeah. I think it's just like, well, how, how seriously do people take it?Yeah. Like, is is, is there a lot of potential in the, in the HOVI?Aaron Levie: Uh, well, can I, can I, uh, understand first if it's, um, is this a loaded question in the sense of are you super pro, super con, super anti medium? Iswyx: see pro, I see pros and cons. Okay. Uh, but I, I think your opinion should be independent of mine.Aaron Levie: Yeah. No, no, totally. Yeah. I just want to see what I'm stepping into.swyx: No, I know. It's a, and it's a huge trigger word for a lot of people out Yeah. In our audience. And they're, they're trying to figure out why is that? Because whyAaron Levie: is this such aswyx: hot item for them? Because a lot of people get graph religion.And they're like, everything's a graph. Of course you have to represent it as a graph. Well, [00:47:00] how do you solve your knowledge? Um, changing over time? Well, it's a graph.Aaron Levie: Yeah.swyx: And, and I think there, there's that line of work and then there's, there's a lot of people who are like, well, you don't need it. And both are right.Aaron Levie: Yeah. And what do the people who say you don't need it, what are theyswyx: arguing for Mark down files. Oh, sure, sure. Simplicity.Aaron Levie: Yeah.swyx: Versus it's, it's structure versus less structure. Right. That's, that's all what it is. I do.Aaron Levie: I think the tricky thing is, um, is, is again, when this gets met with real humans, they're just going to their computer.They're just working with some people on Slack or teams. They're just sharing some data through a collaborative file system and Google Docs or Box or whatever. I certainly like the vision of most, most knowledge graph, you know, kind of futuristic kind of ways of thinking about it. Uh, it's just like, you know, it's 2026.We haven't seen it yet. Kind of play out as as, I mean, I remember. Do you remember the, um, in like, actually I don't, I don't even know how old you guys are, but I'll for, for to show my age. I remember 17 years ago, everybody thought enterprises would just run on [00:48:00] Wikis. Yeah. And, uh, confluence and, and not even, I mean, confluence actually took off for engineering for sure.Like unquestionably. But like, this was like everything would be in the w. And I think based on our, uh, our, uh, general style of, of, of what we were building, like we were just like, I don't know, people just like wanna workspace. They're gonna collaborate with other people.swyx: Exactly. Yeah. So you were, you were anti-knowledge graph.Aaron Levie: Not anti, not anti. Soswyx: not nonAaron Levie: I'm not, I'm not anti. ‘cause I think, I think your search system, I just think these are two systems that probably, but like, I'm, I'm not in any religious war. I don't want to be in anybody's YouTube comments on this. There's not a fight for me.swyx: We, we love YouTube comments. We're, we're, we're get into comments.Aaron Levie: Okay. Uh, but like, but I, I, it's mostly just a virtue of what we built. Yeah. And we just continued down that path. Yeah.swyx: Yeah.Aaron Levie: And, um, and that, that was what we pursued. But I'm not, this is not a, you know, kind of, this is not a, uh, it'sswyx: not existential for you. Great.Aaron Levie: We're happy to plug into somebody else's graph.We're happy to feed data into it. We're happy for [00:49:00] agents to, to talk to multiple systems. Not, not our fight.swyx: Yeah.Aaron Levie: But I need your answer. Yeah. Graphs or nerd Snipes is very effective nerd.swyx: See this is, this is one, one opinion and then I've,Jeff Huber: and I think that the actual graph structure is emergent in the mind of the agent.Ah, in the same way it is in the mind of the human. And that's a more powerful graph ‘cause it actually involved over time.swyx: So don't tell me how to graph. I'll, I'll figure it out myself. Exactly. Okay. All right. AndJeff Huber: what's yours?swyx: I like the, the Wiki approach. Uh, my, I'm actually
Last month, the US AI giant Anthropic released a new Claude tool for the legal industry, triggering a sell-off in publicly listed firms like Salesforce and reigniting concerns that AI-native startups could wipe out traditional SaaS giants.So will Europe's VC-backed SaaS giants survive the AI area? And what about the VCs who've heavily backed them?In this episode of the Sifted Podcast, host Amy Lewin is joined by senior reporters Freya Pratty and Anne Sraders to unpack what the rise of AI means for Europe's VC-backed software companies — and the investors who've poured billions into them.Read more here: https://sifted.eu/articles/european-vc-saaspocalypse
Rodolfo Elias Dieck | Managing Partner | Proeza Ventures What does today's exit market really look like from the investor's seat? In this Investor's Corner episode of the TechExits Podcast, Rodolfo Elias Dieck shares how venture investors think about exits in today's market—why most venture‑backed outcomes still happen through strategic M&A, how founders should prepare years in advance, and where valuation expectations often break down. Rodolfo also discusses the growing role of secondaries, how boards and investors navigate misalignment, and what founders need to understand about building relationships with potential acquirers early. A practical, grounded conversation for founders, operators, and investors navigating the next wave of tech exits. Key Takeaways Why most venture‑backed exits still happen through M&A How investors help founders prepare long before a sale Where valuation misalignment between founders and VCs comes from Why secondaries matter—but aren't a silver bullet yet 00:00 – Introduction & Proeza Ventures' investment focus 01:50 – Why tech exits are picking up again 04:30 – How investors prepare founders for exits 07:05 – M&A vs IPOs and the role of secondaries 09:10 – Inbound interest vs running a formal M&A process 12:45 – What buyers value that founders often overlook 19:20 – Will the exit wave continue? Advice for founders
Bill Gurley is a Wall Street and Silicon Valley legend. He's the analyst who led the Amazon IPO and went on to become one of the most successful VCs of all time and an early investor in Uber, Zillow, and GrubHub. Today, he joins Nicole to answer the biggest questions on investors' minds right now. Bill doesn't mince words: yes, we're in an AI bubble— and he explains exactly why, from circular spending deals that smell like Enron to the speculative behavior that always follows a real wave of innovation. He breaks down why the IPO system is rigged against retail investors, what tokenization could do to fix it, and what a SpaceX IPO would actually mean for everyday investors. He also shares the one market sector he thinks is quietly becoming a buy, and the specific Chinese battery stock he personally owns. Then the conversation shifts to Bill's new book, Runnin' Down a Dream, and his surprisingly personal framework for building a career you actually love. He shares the question he asked himself twice that changed the entire course of his life, his research on career regret, and why chasing passion is a competitive advantage. Check out Nicole's financial literacy course The Money School Find a Financial Advisor or Financial Coach from Nicole's company Private Wealth Collective Watch video clips from the pod on Money Rehab's Instagram and Nicole Lapin's Instagram Get Bill's book Runnin' Down a Dream Here's what Nicole covers with Bill: 00:00 Are You Ready for Some Money Rehab? 01:12 SpaceX + xAI: What Elon's Deal Really Means 03:18 Why Retail Investors Keep Getting Shut Out of the Best Companies 05:55 The IPO System Is Rigged 08:36 Inside the Amazon IPO 10:40 Are We in an AI Bubble? 16:30 AI vs. the Dot-Com Bubble 21:15 Which AI Tools Bill Actually Uses 22:00 Bill's Take on AGI Hype 23:30 Where Bill Sees Opportunity Outside of Tech 27:30 The Chinese Battery Stock Bill Personally Owns 28:45 How to Evaluate Stock Options as an Employee 31:50 The Hidden Value of Joining a Fast-Growing Company 33:15 Buy Side vs. Sell Side Analysts 35:40 The Question That Changed Bill's Career Twice 38:00 Why Following Your Passion Is a Competitive Advantage 42:00 How Tito's Vodka Started with a Blank Sheet of Paper 45:20 Bill's Next Chapter: A Policy Institute 48:00 Nuclear Energy, Healthcare, and the Issues Bill Wants to Fix 51:06 Bill Gurley's Tip You Can Take Straight to the Bank All investing involves the risk of loss, including loss of principal. This podcast is for informational purposes only and does not constitute financial, investment, or legal advice. Always do your own research and consult a licensed financial advisor before making any financial decisions.
Iñaki wants to save the planet AND save companies money on their electricity bills. Can this outdoorsman convince the VCs there's a big earnings in big savings? This is The Pitch for Climatta. Featuring investors Elizabeth Yin, Jesse Middleton, Laura Lucas, and Mike Ma. Watch Iñaki's pitch uncut on Patreon (@ThePitch) Join us for the Season 16 taping in Tampa Subscribe to our email newsletter: insider.pitch.show Learn more about The Pitch Fund: thepitch.fund *Disclaimer: No offer to invest in Climatta is being made to or solicited from the listening audience on today's show. The information provided on this show is not intended to be investment advice and should not be relied upon as such. The investors on today's episode are providing their opinions based on their own assessment of the business presented. Those opinions should not be considered professional investment advice. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Europe does not have a deep tech problem. It has a commercialisation problem.The last European companies to reach €100B+ market caps were SAP and ASML, both founded 40–50 years ago. If Europe wants a new generation of deep tech champions, venture capital alone won't get us there. Customers have to step in.In this episode, Andreas Munk Holm is joined by Martin Schilling, former operator, investor, and founder of Deep Tech Momentum, to unpack why Europe excels at funding breakthroughs, but consistently fails to industrialise them.This is a conversation about:why enterprise buyers are the missing link in European deep techwhat corporates are doing wrong (and how they can fix it)how founders actually win large customers in complex, regulated marketsand why courage — not grants — is Europe's real constraintShare
In the inaugural Family Office Roundtable at VC10X, host Prashant sits down with Ronald Diamond, Founder & Chairman of Diamond Wealth, and Wendy Craft, CEO of Elle Family Office, for a candid conversation on what's really happening inside family offices today.From AI tools that are already replacing analysts, to the private equity liquidity crisis, to the $124 trillion wealth transfer heading to the next generation.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comWhat we cover:- How AI is transforming deal flow, due diligence & the analyst role- Where family offices are allocating right now — and what's broken in private equity- Why after-tax returns are the only number that matters- The rise of ETFs and tax-loss harvesting as game changers for families- SFO vs. MFO — and why 85-90% of family offices shouldn't exist- Next gen wealth transfer & why most families are failing at it- The role of family office capital in solving real-world problemsTimestamps:(00:00) - Introduction: The Future of Family Offices(01:26) - Welcoming Guests: Ronald Diamond & Wendy Craft(02:18) - The Role of AI in Family Offices(03:40) - A Cautious Approach to AI Investment(04:52) - How AI is Disrupting Due Diligence(07:43) - Replacing Analysts with AI to Cut Costs(09:42) - AI Efficiency vs. The Need for Human Oversight(11:17) - Case Study: How Large Families Use AI for Efficiency(13:12) - Can AI Handle Proactive Deal Sourcing?(14:16) - The Importance of Human Networks in Deal Flow(15:58) - Portfolio Construction: Public vs. Private Markets(17:52) - The Problem with Private Equity's Long Lock-up Periods(19:57) - Contrasting Private Equity with the Family Office Model(22:30) - The Tax Angle: Liquidity vs. Long-Term Investment(24:10) - The Growing Focus on After-Tax Returns(27:00) - The Emergence of ETFs for Tax Efficiency(29:13) - Venture Capital Investing Styles for Family Offices(31:28) - Why Inexperienced Family Offices Should Outsource VC(34:26) - The Rise of OCIOs for Next-Generation Wealth Management(35:54) - The Future: Outsourcing to MFOs and OCIOs(38:22) - MFOs vs. OCIOs: What's the Difference?(41:28) - Educating and Including the Next Generation(44:20) - How the Next Generation's Investment Interests Differ(45:00) - The Philanthropic Potential of Family Offices(48:01) - Youth's Belief in AI to Solve Societal Issues(49:23) - The Negative Impact of Technology on Mental Health(54:55) - Portfolio Hedges: Gold, Silver, and Bitcoin(56:31) - The Evolution of Cryptocurrency as an Asset Class(58:13) - Skepticism and Risks in the Crypto Market(01:02:43) - Interest in Gold, Silver, and Critical Minerals(01:03:23) - Parting Advice for Family Offices(01:03:54) - Ron's Advice: Run it Like a Business or Outsource(01:04:56) - Wendy's Advice: The Efficiency of MFOs for Most Families--Guests:
Think your 75% EBITDA margins look impressive? Unless you're running a drug cartel, Alex Rubalcava says you're probably just showing a lack of financial sophistication.In this episode of the Demo Day podcast, we sit down with Alex Rubalcava, Managing Partner of Amplify LA, to deconstruct the "delusional" financial modeling that keeps most founders from getting funded. Alex shares why grounded, realistic forecasts are the ultimate signal of a sophisticated founder and why many pitch decks are rejected before the first meeting even ends.As a veteran in the Los Angeles venture capital scene, Alex has seen thousands of pitch decks. He explains the nuance between ambitious growth and impossible math, helping entrepreneurs understand what venture capital firms actually look for in a business model. We dive deep into the mechanics of startup fundraising, the importance of unit economics, and how to build a financial model that builds trust rather than destroying it.We cover why "Mafia-level" margins are a massive red flag for VCs and the difference between financial optimism and a lack of sophistication. Alex breaks down how to present a forecast that stands up to VC due diligence and shares his current outlook on founder success in 2026. Whether you are a first-time founder preparing your seed round or a seasoned entrepreneur looking to sharpen your Series A pitch, Alex's insights on financial reality will change how you view your startup's data.Key Highlights:The "Cartel Margin" trap: Why 75% margins are a red flag.How to signal financial sophistication to investors.The current state of venture capital and startup valuation.Why your fundraising strategy needs a reality check.Lessons from Amplify LA on what makes a pitch deck stand out.
Six newly-created accounts made a profit of $1 million by correctly betting that the U.S. would strike Iran by February 28. TechCrunch spoke with VCs to learn what investors aren't looking for in AI SaaS startups anymore. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Retrouvez l'épisode en version française ici : https://www.gdiy.fr/podcast/alice-bentinck-vf/ She might be the most underrated founder in Europe.Alice Bentinck has no massive press coverage.Just 15 billion dollars worth of companies built quietly over 10 years.Alice is the co-founder of Entrepreneurs First, the talent investor that finds founders before they have a company, before they have an idea, sometimes before they even know they want to be a founder.The model sounds crazy.VCs have told her it would never work.But Entrepreneurs First has now produced 500 seed-funded companies, counts Reid Hoffman and Patrick Collison among its backers.In this episode, Alice breaks down everything she has learned about co-founders: why breakups kill more startups than bad ideas, how to know in 48 hours if someone is the right partner, why three co-founders is the most expensive mistake you'll make, and why megalomania is not a flaw but a necessity in every great founder.If you've ever struggled to find the right co-founder, or wondered whether the one you have is actually the right one, this episode is for you.You can contact Alice on LinkedIn.If you want to apply to Entrepreneurs First, you can reach Julia and Anastasia at: gdiy@joinef.comTIMELINE:00:00:00 Finding founders before they have a company00:11:37 The co-founder mistake that kills startups00:17:42 The 3-founder trap: The most expensive mistake00:26:22 How to know when to have that hard conversation00:33:23 The Human Algorithm: How Alice spots potential before the idea00:44:26 How to access American capital without losing your European soul00:52:11 Scaling the Unscalable: How EF went from 10 to 100 companies a year01:03:47 The Customer Secret: Why your location defines your speed01:12:05 The 5-Attempt Rule: Why your first company doesn't need to work01:19:53 High Personal Exceptionalism: You must believe you are different to succeed01:35:46 The 996 Reality: Startups are the ultimate negative lifestyle choice01:53:07 Methodical is Slow: Why European founders are focusing on the wrong things02:01:12 The AI Performance Hack: How to manage your health & a $15B portfolio02:08:20 The $1,000-An-Hour Secret: How coaching builds a high-performing teamWe referred to previous GDIY episodes : #487 - VO - Anton Osika - Lovable - Internet, Business, and AI: Nothing Will Ever Be the Same Again#500 - VO - Reid Hoffman - LinkedIn, Paypal - How to master humanity's most powerful invention#429 - Nicolas Dessaigne - Y Combinator - Le berceau des futurs géants de la tech#483 - Carlos Ghosn - Out of the box : masterclass business de l'évadé du siècle#158 Edgar Grospiron - Athlète et conférencier - Avance, fais-toi confiance.A few recent episodes in English : #513 - VO - Jesper Brodin - IKEA - 40 billion in revenue empire with no bank loan#500 - Reid Hoffman - LinkedIn, Paypal - How to master humanity's most powerful invention#487 - VO - Anton Osika - Lovable - Internet, Business, and AI: Nothing Will Ever Be the Same Again#475 - VO - Shane Parrish - Farnam Street - Clear Thinking: The Decision-Making Expert#473 - VO - Brian Chesky - Airbnb - « We're just getting started »#452 - VO - Reid Hoffman - LinkedIn, Paypal - L'humanité 2.0 : Homo technicus plus qu'Homo sapiens#437 - James Dyson - Dyson - “Failure is more exciting than success”#431 - Sean Rad - Tinder - How the swipe fever took over the worldWe spoke about :DuolingoEntrepreneurs first's portfolioY CombinatorOur documentary to understand the American DreamAu Royaume-Uni, l'impopularité du Brexit relance le débat sur les liens avec l'UEOpenAI to remove non-profit control and give Sam Altman equityAztecPolyAIThe 996 working hour systemReading Recommendations :Fierce Conversations, by Susan ScottSuper Founders, by Ali TamasebThe Road Less Travelled, by M.Scott PeckHow to Be a Founder, by Alice BentinckA work in progress, by René RedzepiInterested in sponsoring Generation Do It Yourself or proposing a partnership ? Contact my label Orso Media through this form.Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.
I take Perplexity Computer for its first real spin and test five use cases that founders can use right now to make money and move faster. I connect my Gmail live, let the AI send cold outreach on my behalf, set up daily competitive intelligence monitoring, research 50 VCs for a mock Series A, and kick off a full investment memo on Shopify, all in a single session. By the end, I walk away genuinely impressed and convinced the $200/month Max plan can pay for itself with one closed deal. Timestamps 00:00 – Intro 00:35 – What We're Testing Today 02:35 – Use Case 1: Warm Outbound at Scale 15:31 – Use Case 2: Automated Competitive Intel 25:11 – Use Case 3: Investor Pipeline Research (50 VCs) 26:58 – Use Case 4: Turn a Podcast Into a Content Machine 31:39 – Use Case 5: Live Market Diligence (Shopify Investment Memo) 34:17 – Bonus: Additional Use Cases Worth Trying 36:06 – Closing Thoughts and Takeaways Key Points Perplexity Computer runs multiple research tasks in parallel using sub-agents, skills, and tools — functioning like a virtual analyst working across the open internet. The cold outreach workflow found real email addresses, researched each prospect's recent activity, and drafted hyper-personalized emails that reference specific details — then sent them through a connected Gmail account. Setting up recurring competitive intelligence monitoring (daily reports, weekly sponsor tracking) is where the tool shifts from a one-off assistant to a persistent agent running on autopilot. The VC pipeline research use case demonstrates how founders who lack a warm network can still build a structured, targeted investor list with fund sizes, thesis alignment, and partner contacts. At $200/month on the Max plan, the cost pays for itself if even one sponsorship deal or investor meeting closes from the outreach. The platform already supports connectors for Gmail, Google Drive, Slack, HubSpot, Ahrefs, Reddit, and more — making it a serious contender for centralized founder workflows. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/
What does “smart money” actually mean in beverage — especially in one of the most capital-intensive categories in CPG?In this sponsored episode, we sit down with Karen Xiang, Investment Lead at Btomorrow Ventures, the corporate venture arm backed by British American Tobacco. And we go deep into how corporate venture capital is evolving — and what it really means for founders building functional and full-size beverage brands today.Btomorrow Ventures (BTV) is not a traditional VC fund. With a £150M first fund and a newly launched £200M second fund, BTV is investing across “better brands” and “better habits” — with a particular focus in the U.S. on full-size functional beverages and functional snacks. But capital is only part of the story.Karen explains how BTV's new in-house growth platform is designed to unlock operating leverage — connecting portfolio brands to distribution pilots, commercialization support, data analytics, and internal expertise inside a global FMCG infrastructure.For founders, this episode is an insightful discussion about:• What corporate venture capital (CVC) actually is — and how it differs from traditional VC• What to ask before taking strategic capital• Why beverage remains a difficult category for many VCs — and what that means for your cap table• How to think about partnering with strategics without becoming “the last fry on the truck”Karen also offers a thoughtful framework for avoiding trend-chasing in drinks. In a world of protein pivots and format fads, she argues that fundamentals — consumer clarity, occasion ownership, distribution sequencing — still win over time.For investors, we explore how BTV thinks about co-investing rather than competing — and why having a strategic partner on the cap table can accelerate growth across the entire syndicate.If you're a founder navigating functional beverage, a co-investor evaluating corporate capital, or an operator thinking about long-term category shifts, this episode offers a rare inside look at how one of the industry's more nuanced CVC models is building in the U.S.As always, we focus on the mechanics of growth — not just the headline numbers, but how brands actually scale.Listen in for a grounded, strategic conversation about capital, distribution, and the future of value-add investing in drinks.For the latest updates, follow us:Business of Drinks:Business of Drinks website (sign up for our newsletter!)Business of Drinks YouTubeBusiness of Drinks LinkedInInstagram @bizofdrinksErica Duecy, co-host: Erica Duecy is founder and co-host of Business of Drinks and one of the drinks industry's most accomplished digital and content strategists. She runs the consultancy and advisory arm of Business of Drinks and has built publishing and marketing programs for Drizly, VinePair, SevenFifty, and other hospitality and drinks tech companies.Erica Duecy LinkedInInstagram @ericaduecyScott Rosenbaum, co-host: Scott Rosenbaum is co-host of Business of Drinks and a veteran strategist and analyst with deep experience building drinks portfolios. Most recently, he was the Portfolio Development Director at Distill Ventures. Prior to that, he was the Vice President of T. Edward Wines & Spirits, a New York-based importer and distributor.Scott Rosenbaum LinkedInCaroline Lamb, contributor: Caroline is a producer and on-air contributor at Business of Drinks and a key account sales and marketing specialist at AHD Vintners, a Michigan-based importer and distributor.Caroline Lamb LinkedInInstagram @borkalineIf you enjoyed today's conversation, follow Business of Drinks wherever you're listening, and don't forget to rate and review us. Your support helps us reach new listeners passionate about the drinks industry. Thank you!
There Are Many Scenarios in Fundraising Hello, this is Hall T. Martin with the Startup Funding Espresso -- your daily shot of startup funding and investing. In fundraising, there are many scenarios and strategies a founder can use. Here are several factors that impact which strategy to use: The current market for funding. In up markets, one can raise more funding and at a faster pace. The strength of the startup. Startups with traction and a great team can command greater fundraises. The target growth rate of the company. The higher the growth, the greater the fundraising goal. The type of investor sought. There are angels, venture capitalists, and family offices to consider. Angels can be easier funding to acquire. VCs can invest greater amounts of money. Family offices can be patient money. Throughout the campaign, consider which strategy and scenario to use at each stage. In pitching, be sure not to play out all the options to an investor, as this will be confusing. Choose a scenario and play it out with the investor. Consider these points in choosing the strategy and scenario of your fundraise. Thank you for joining us for the Startup Funding Espresso where we help startups and investors connect for funding. Let's go startup something today. _________________________________________________________ For more episodes from Investor Connect, please visit the site at: http://investorconnect.org Check out our other podcasts here: https://investorconnect.org/ For Investors check out: https://tencapital.group/investor-landing/ For Startups check out: https://tencapital.group/company-landing/ For eGuides check out: https://tencapital.group/education/ For upcoming Events, check out https://tencapital.group/events/ For Feedback please contact info@tencapital.group Please follow, share, and leave a review. Music courtesy of Bensound.
This week on Swimming with Allocators, Earnest and Alexa welcome David Clark, CIO at Vencap, who unpacks the realities of venture capital, emphasizing a data-driven approach to understanding returns, the persistent and intensifying “power law” in VC, and why only a small percentage of funds and companies drive outsized results. The discussion covers the challenges of evaluating new managers versus established firms, the nuances of secondary investments, and the critical importance of consistent, top-tier fund performance. Listeners will gain insight into the pitfalls of confirmation bias, the difficulties facing retail investors, and why strategy, transparency, and adaptability are key for long-term VC success. Also don't miss Rebecca Stuart of Sidley as she explains how unprecedented AI-focused acqui-hires function as talent raids that can bypass standard change-of-control protections. She also outlines legal and structural strategies VCs and startups can use like broadened definitions of change of control, retention and vesting design, and coordinated employment/comp practices, to better protect portfolios and key teams. Highlights from this week's conversation include: Welcoming David to the Show and Previewing Today's Episode (0:18) David's Shift From Traditional LP Diligence to Data-Driven Investing (2:48) How Long Feedback Loops and Unknown Unknowns Shape Venture Outcomes (5:16) Confirmation Bias, Narratives, and Doing Pre-Meeting Homework on Managers (6:55) Pattern Recognition and What World-Class Founders Look Like (8:49) Using Power Laws and Top 1% Companies as the Core LP Filter (10:40) Why Singles and Doubles Rarely Add Up to Great Venture Funds (13:46) AI Acqui-Hires, Talent Raids, and Risks to VC Portfolios (17:20) Deal Structures That Avoid Change of Control and LP Protections (19:04) Retention Tools, Forfeiture for Competition, and Staggered Vesting Cliffs (20:53) Democratization of VC, 401(k) Investors, and the Risk of Disappointment (25:22) Emerging Managers and the Myth of the Middle Class in Venture (30:58) Venture Secondaries, Premium Pricing, and Why Discounts Can Be Misleading (36:04) Scope Creep, Platform Expansion, and When LPs Disengage From Big Firms (42:06) VenCap is one of the longest-running dedicated venture capital fund-of-funds globally, investing in many of the world's leading VC firms for over three decades. The firm's strategy emphasizes long-term consistency, deep relationship networks, and concentrated exposure to top-tier venture capital companies across cycles. Sidley Austin LLP is a premier global law firm with a dedicated Venture Funds practice, advising top venture capital firms, institutional investors, and private equity sponsors on fund formation, investment structuring, and regulatory compliance. With deep expertise across private markets, Sidley provides strategic legal counsel to help funds scale effectively. Learn more at sidley.com. Swimming with Allocators is a podcast that dives into the intriguing world of Venture Capital from an LP (Limited Partner) perspective. Hosts Alexa Binns and Earnest Sweat are seasoned professionals who have donned various hats in the VC ecosystem. Each episode, we explore where the future opportunities lie in the VC landscape with insights from top LPs on their investment strategies and industry experts shedding light on emerging trends and technologies. The information provided on this podcast does not, and is not intended to, constitute legal advice; instead, all information, content, and materials available on this podcast are for general informational purposes only. Learn more about your ad choices. Visit megaphone.fm/adchoices
Most VCs work non-stop and still feel like they're failing. They do 2x the deals of their peers. They're at every event. And they still feel like they're not doing enough.What James Johnson and Freddie Birley reveal in this episode is what VCs won't say publicly: the loneliness, the ambiguity, the constant feeling of underperforming despite objectively crushing it.What drives this?Founders want freedom. VCs want peak performance. When you're optimizing for achievement but venture's ambiguity makes it impossible to define what "good" looks like, you're stuck in perpetual dissatisfaction.In this episode:Why most VCs feel like they're failing even when they're crushing itThe loneliness both founders and investors experience (and why both jobs are more similar than different)What actually drives each group - and why this explains why they talk past each otherHow to shift from outcome obsession (exits - out of your control) to input control (craft mastery - in your hands)For founders: Understanding this changes how you work with your boardFor VCs: This is the validation you didn't know you neededThis is Peer Effect Post Bag - James and Freddie answering your toughest questions.More from James: Connect with James on LinkedIn or at peer-effect.com
Ankur Sethi spent years at two of India's most iconic startups — Swiggy and Paytm — before leaving his operating role to found Winner Capital, a consumer-first, AI-native syndicate investing out of North America.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comIn this episode, we get into:→ Why consumer AI is massively underfunded while enterprise SaaS gets all the attention→ What "durable retention" actually looks like — and the ambassador signal every founder should watch for→ The 0→1, 1→10, 10→100 framework and how your mindset must shift at each stage→ Why unit economics are non-negotiable even at pre-seed→ The one operating principle from Swiggy & Paytm that most founders underestimate until it's too late→ Why launching a fund during a market correction is actually an advantage→ His honest take on India as a market — and when Winner Capital plans to enterIf you're a founder building in consumer tech or AI, or an operator thinking about making the leap into venture, this one is for you.
Startup employees are encouraged to believe in the mission. But IPO timelines now stretch well past a decade — and many never happen at all. In this episode, Ben Black, co-founder and managing director of Akkadian Ventures, explains how tech workers can think more strategically about the equity they've helped create. Drawing on more than 750 secondary transactions, Ben walks through how employees can evaluate a company's liquidity posture before accepting an offer, exercise options intelligently, understand the real value of their shares, and access secondary buyers — whether through structured programs or more proactive approaches. We also dig into the psychological side of selling: when to take money off the table, how to avoid overestimating future upside, and why “loyalty” shouldn't mean ignoring your own financial reality. Ben shares real-world examples of employees using secondaries to fund major life events — and even to bootstrap their own companies so they can retain more ownership and control from day one. Founders and VCs get a lot of attention for the risks they take. This episode is about the people who often take just as much risk with far less margin for error. * Information offered is for educational purposes and should not be considered financial advice. RUNTIME 52:37 BREAKDOWN (2:12) How Ben got into the secondary market and founded Akkadian (5:33) “The vast majority of really good companies now have secondary programs.” (8:39) Secondaries generate “a very significant part of the return of the large funds.” (9:57) Why are most companies still on a four-year vesting cliff? (12:55) Things to consider when you're 25% vested (15:22) Why so many tech workers never exercise their vested options (16:49) A framework for identifying the *right* time to sell (21:26) How to access the secondary market if your company doesn't offer a structured program (30:09) “I do see a lot of bad behavior among employees… using information that they're not supposed to use.” (32:06) Startup employees: cultivate a strong relationship with your CFO (34:08) The #1 reason why employees sell secondaries (and a few edge cases) (38:44) “You have to be really skeptical, and you need to take a lot of shots on goal.” (45:11) How many founders are bootstrapping startups using the secondary market? (48:44) How long does it take to get liquid? LINKS Ben Black Akkadian Venture Capital IPO markets look primed to accelerate in 2026, pwc, 12/12/2025 SUBSCRIBE
Dragonfly raises a $650M Fund IV amid crypto's institutional vs retail sentiment gap, the industry exodus including Kyle Samani's departure from Multicoin, OpenClaw's OpenAI acquisition and crypto Twitter harassment, X402 payment standards for AI agents, Polymarket's controversial 5-minute Bitcoin betting markets, and the brewing federal vs state regulation battle over prediction markets. Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This episode kicks off with major news: Dragonfly just closed their $650 million Fund IV, making them one of the largest crypto VCs not through growth, but because others have downsized. The timing feels surreal — they keep raising right when markets dump, creating the biggest gap between institutional optimism and retail sentiment Haseeb has ever seen. But money flowing in contrasts sharply with talent flowing out. Kyle Samani left Multicoin, Arianna Simpson departed A16z Crypto, and several other crypto veterans are moving on. The crew unpacks what this "great resignation" means for an industry that feels like it's shifted from pioneer phase to settler phase. Then they dive into the OpenClaw saga — the viral AI coding assistant that got acquired by OpenAI, but not before its creator almost deleted it due to harassment from crypto Twitter demanding he launch a token. This leads to a deep discussion on X402 payment standards and why AI agents might prefer crypto over credit cards. Finally, they debate Polymarket's controversial 5-minute Bitcoin betting markets and the brewing legal battle between federal and state regulation of prediction markets. Let's get into it. Listen to the episode on Apple Podcasts, Spotify, Pods, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Show highlights
On this episode of Planet Geo, we welcome Danielle Bennett—a startup operator with a venture capital background (and not a geoscientist by training) who's been talking with tons of geologists, hydrogeologists, and engineers while helping build a geoscience-adjacent mapping company at Deep Earth Tech. Danielle shares how growing up with entrepreneur parents (who ran a groundwater-focused engineering firm) shaped her path, why she started a social-impact company in college, and how she moved from corporate finance to FinTech and then into venture capital for about six years. They dig into what she's learned from working with the geoscience community—friendly, non-confrontational, and highly opinionated—and why geoscientists may be slower to found startups (a strong perfection/excellence culture and highly localized expertise). Danielle breaks down “deep tech” in practical terms (asset-heavy and/or science-and-engineering-driven tech), why capital is moving earlier into deep tech, and how VCs are increasingly pulling innovations from universities and incubators. The conversation also gets into which geoscience-adjacent areas feel investable (like shallow geothermal heating/cooling, critical minerals, and renewables) and why groundwater can be harder to fund due to public-agency buying cycles and complex bureaucracy. Danielle closes by defining key funding terms—bootstrapping, debt financing, private equity, and venture capital—plus what VCs look for (why now, why this team, and scale) and common red flags (unclear messaging, weak grasp of numbers, and unjustified mega-rounds).We hope you enjoy this excellent interview!Download the CampGeo app now at this link. On the app you can get tons of free content, exclusive images, and access to our Geology of National Parks series. You can also learn the basics of geology at the college level in our FREE CampGeo content series - get learning now!Like, Subscribe, and leave us a Rating!——————————————————Instagram: @planetgeocastTwitter: @planetgeocastFacebook: @planetgeocastSupport us: https://planetgeocast.com/support-usEmail: planetgeocast@gmail.comWebsite: https://planetgeocast.com/
What should VCs actually look for in a fund administration partner?In this episode of VC10X, we sit down with Shalin Madan, Co-Founder of Formidium - a global fund administration platform supporting venture capital, private equity, hedge funds, and alternative asset managers with over $33B+ in assets under administration.We go beyond the surface-level checklist and unpack what truly matters when selecting a fund administrator - especially for emerging managers.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comTopics covered:• The most overlooked due diligence question when choosing a fund admin• Why business model sustainability matters more than branding• How technology reflects internal discipline (and why “banning Excel” matters)• The hidden costs of managing operations in-house• Why durability is becoming more important than performance• How LP scrutiny is evolving• Why many funds and companies may not survive the next few yearsInfrastructure is no longer back office — it's strategy.If you're building a fund designed to last 10+ years, this episode will change how you think about operations, risk, and long-term durability.Timestamps:(00:00) - The Hidden Costs of In-House Operations(00:33) - Introduction to Fund Administration and Guest Shaleen Madan(01:49) - Sponsor: Podcast 10X for VCs(02:47) - Critical Due Diligence for Selecting a Fund Administrator(04:16) - How a Tech Stack Signals Quality and Reduces Risk(05:23) - Early Trends in Capital Flows and Investor Behavior(07:39) - The Institutionalization of Family Offices(09:09) - How Emerging Managers Can Handle Future Regulatory Changes(11:12) - In-House vs. Outsourcing: A Former Fund Manager's Perspective(13:54) - The Unique Operational Challenges of Crypto-Native Funds(16:35) - How Back-Office Needs Differ Across Asset Classes(20:09) - How to Properly Vet a Service Provider's Expertise(21:33) - A Contrarian Take on Capital Flows and Market Dynamics(26:56) - The Impact of AI on Pricing Power and Outsourcing(29:18) - Key Questions LPs Should Ask About Operational Infrastructure(31:36) - Lessons Learned from Rapidly Scaling a Business(33:26) - Where to Find Shaleen Madan and FormidiumConnect with Shalin:Website - https://formidium.com/Linkedin - https://www.linkedin.com/in/shalin-madan-caia-b00239/Podcast Links:Prashant Choubey - https://www.linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comSubscribe on YouTube - https://youtube.com/@VC10X Subscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQVC10X website - https://vc10x.comFor sponsorship queries, reach out to prashantchoubey3@gmail.com#VentureCapital #FundAdministration #EmergingManagers #PrivateEquity #VC10X
Most startup advice tells you how to grow, but Brian Lee is here to tell you how to survive. In this episode, the legendary founder of LegalZoom and The Honest Company reveals the "one truth" that separates elite CEOs from those who run out of runway.Whether you're a first-time founder or a seasoned operator, the role of a CEO is often misunderstood. Brian Lee (Managing Partner at BAM Ventures) joins us on Demo Day to strip away the fluff and deliver a masterclass in operational discipline. From his early days building LegalZoom and ShoeDazzle to his current work with Arena Club, Brian has seen the same patterns lead to both billion-dollar exits and total failures.In this episode, we break down "The CEO Playbook," including:The "CE-No" Philosophy: Why your primary job is saying no to good ideas so you can focus on the great ones.The Survival Mandate: Brian's #1 rule for every founder—treat money like gold and never, ever run out.Building Your Inner Circle: Why you must "hire fast and fire faster" to protect the culture of a high-growth startup.Founder Likability: Why being "likable" is actually a strategic superpower for fundraising and leadership.The VC Perspective: What BAM Ventures looks for in the pre-seed and seed stages of consumer tech.Brian also shares deeply personal insights into his transition from operator to venture capitalist, explaining how his time in the trenches allows him to spot "the signal in the noise" better than professional VCs who have never run a company. If you are looking for startup tips, fundraising advice, or a reality check on your founder success metrics, this is the one conversation you cannot afford to miss.
Alice Bentinck discusses how Entrepreneurs First helps someone to go from “no team, no idea” to funded company. EF has helped create companies now collectively worth more than $10,000,000,000 and many participants go from zero to raising $2-15 million from top-tier VCs within months. Bentinck argues that capital is the easiest part of the journey, while co-founder fit, community, and early guidance are what really accelerate success. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
What if failure isn't something to avoid, but a skill to master? This episode breaks down why startups can't be built on certainty—new markets, new products, and new teams mean you're guaranteed to be wrong a lot. The goal isn't to “be right,” it's rapid error correction: make decisions, ship anyway, learn fast, and recover even faster. The conversation covers how avoiding failure leads to paralysis (“steering a parked car”), why indecision compounds in startups, and how to reduce risk by keeping failures small, reversible, and frequent (kill switches, stop rules, and capped losses). They share early personal stories—school fights and a childhood cattle business collapse—to show how overcoming real consequences builds confidence and resilience. Practical examples include choosing an ICP quickly, improving poor conversion rates through iteration, using vesting/cliffs when picking co-founders, and why even top VCs still miss constantly. The key takeaway: the most dangerous competitor is the one who isn't afraid to get hit, recover, and keep coming back—because that's as close to “invincible” as a founder can get.02:01 Failure Isn't the Enemy: Stop Optimizing for Being Right02:59 The Founder Reality: Uncertainty, Rapid Error Correction & the Boxing Analogy03:44 Safety vs Startups: Why Most People Avoid the Risk05:24 ‘Steering a Parked Car': Indecision Kills Startups07:54 Make the Call, Learn Fast: Small Failures, Big Truths09:02 We're Conditioned to Fear Failure (School, Work, Relationships)11:59 Will's Origin Story: Jason Barker and Learning to Beat the Monster14:48 Choosing to Fail on Purpose: Turning Fear into a Superpower17:06 Ryan's First Big Failure: The Farm/Cattle Business Lesson Begins17:45 Cash-Strapped Expansion: Inventory Leverage & a Brutal Winter18:09 When the Side Hustle Needs a Side Hustle (and the Cost of Neglect)18:35 Failing Hard at 12: Losing Animals and Learning to Plan19:51 Founders Don't Win by Being Right—They Win by Taking Hits21:36 Shipping While Wrong: Marketing Experiments, MVPs, and Momentum22:51 Hiring, Co-Founders & Investors: Why Nobody Can Pick Perfectly24:00 The Real Skill: Recovering From Failure (Resilience as a Reflex)30:26 Small Blast Radius, High Frequency: Reversible Bets & Kill Switches31:13 Failure Is Portable: Building a House, Living ‘Why Not,' No RegretsResources:Startup Therapy Podcasthttps://www.startups.com/community/startup-therapyWebsitehttps://www.startups.com/beginLinkedInhttps://www.linkedin.com/company/startups-co/Join our Network of Top FoundersWil Schroterhttps://www.linkedin.com/in/wilschroter/Ryan Rutanhttps://www.linkedin.com/in/ryan-rutan/What to listen for:
Camille Accolas (Founder of TrustExchange, LinkedInCamille Accolas (Founder of TrustExchange, LinkedIn) came on the podcast and we spoke about trust and what becomes possible when we're allowed to show up as full pepole. We spoke of Camilles past in sustainability and biodiversity and how even there being able to bring people together and create containers was key to driving change. What happens when we turn the tables and change the rules of engagement between eg. VCs and Startups? How working with tangible things are more difficult to scale but easier to grasop. How we are worth more as humans than our last paycheck and how creating spaces full of presence with a clear intention has the potential to make us remember. This is a lovely convo. Check out Camilles work and enjoy!
"BDC is powerful in the sense that it can make or break a fund… And a lot of people are trying to close funds right now." In 2022, the federal government commissioned a report asking Canada's VCs what they thought about Crown corporation BDC. The report was effectively forgotten, and the feedback was never actioned. Why? What did the report have to say about Canada's largest venture investor? And with Canadian VC in a multi-year lull, is BDC's "steady hand" approach preferred or simply necessary? BetaKit reporter Madison McLauchlan joins to discuss. Related Links: The feds asked investors for candid feedback on BDC. It was never actioned BDC head says bank pulled back from life sciences "too early" as it preps new VC fund BDC unveils $4-billion defence technology platform Another fund partner leaves BDC "A perfect storm": 2025 was the worst year for Canadian VC fundraising since 2016
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Lars van der Zande, founder and CEO/technical architect of Inkwell Finance, for what Lars describes as his first-ever podcast appearance. The conversation covers a wide range of blockchain infrastructure topics, including Lars's work with Sui and Solana blockchains, the innovative capabilities of Ika's programmatic wallets and blockchain of signatures, and how Inkwell Finance is building revenue-based financing solutions for on-chain entities—from AI agents to protocols. They explore the evolving landscape of crypto regulation, the merging of traditional finance with blockchain technology, the future of decentralized legal systems, and how the user experience barrier is being lowered through technologies that eliminate constant transaction signing. Lars also discusses Inkwell's embedded financing approach and their pre-seed fundraising round.Links mentioned:- Inkwell's website: inkwell.finance- Inkwell on Twitter: @__inkwell- Lars on Twitter: @LMVDZandeTimestamps00:00 Introduction to Inkwell Finance and Technical Architecture02:06 Understanding Sui and Solana: Blockchain Dynamics05:55 The Role of Ika in Inkwell Finance11:51 Leviathan: Revenue Generation and Financing in Crypto17:38 The Future of AI Agents and Programmatic Wallets23:23 Smart Contracts: Legal Implications and Future Directions25:06 The Future of Inqvil Finance25:42 Decentralization and Its Evolution27:32 The Merging of Traditional and Crypto Systems29:33 Global Financial Dynamics and Market Reactions31:48 The Collapse of Traditional Financial Systems32:46 Jurisdictional Shifts in the Crypto World33:59 Legal Systems and Blockchain Integration35:57 On-Chain Credit and Financial Opportunities39:29 The Role of AI in Finance41:30 Learning from Peer-to-Peer Lending History43:14 Disruption in Insurance and Risk Management44:54 On-Chain vs Off-Chain Data46:54 The Evolution of the Internet and Blockchain49:12 Future Subscription Models in BlockchainKey Insights1. Ika's Revolutionary Blockchain Signature Technology: Lars discovered Ika, a blockchain of signatures built on Sui that enables any blockchain transaction to be signed without revealing the underlying message. Using patented 2PC MPC technology, Ika splits key shares across validators and encrypts them in transit, performing complex cryptographic operations that allow smart contracts on Sui to generate signatures for transactions on any other blockchain. This eliminates the need to build separate smart contracts on each blockchain, fundamentally changing how cross-chain interactions work and opening possibilities for truly interoperable decentralized applications.2. Programmatic Wallets vs Traditional Wallets: Traditional wallets like MetaMask require manual user approval for every transaction through a front-end interface, but Ika's D-wallet introduces programmatic wallets with policy-based controls embedded in smart contracts. These wallets can execute transactions based on predetermined conditions checked against on-chain data like Oracle prices, without requiring individual user signatures. For example, a Bitcoin D-wallet can hold native Bitcoin without wrapping or bridging to a custodian, and smart contract policies determine when and how that Bitcoin can be transferred, creating unprecedented security and automation possibilities for decentralized finance.3. Inkwell's Revenue-Based Financing Model: Inkwell Finance is building Leviathan, a revenue-based financing platform for on-chain entities including protocols, AI agents, and individual traders with verifiable track records. Borrowers receive capital based on their on-chain performance metrics like sharp ratio and drawdown, with loan repayment automatically deducted from their revenue stream. The profit split structure allocates approximately 60% to borrowers, 30% to lenders, and 10% split between Inkwell and integrating platforms. This creates a sustainable lending model where flight risk is minimized through D-wallet policy controls that restrict how borrowed capital can be used.4. Wallet-as-a-Protocol and the Future of User Experience: The crypto industry is moving toward embedded wallet solutions that eliminate the friction of traditional wallet management, with Wallet-as-a-Protocol representing the next evolution beyond services like Privy and Dynamic. Unlike current embedded wallets that lock users into specific applications, Wallet-as-a-Protocol enables single sign-on across multiple applications while users maintain control of their keys. Combined with app-sponsored gas fees, this approach allows non-crypto-native users to interact with blockchain applications without knowing they're using crypto, removing the biggest barrier to mainstream adoption and creating web2-like user experiences on web3 infrastructure.5. AI Agents as Financial Entities: AI agents are emerging as revenue-generating entities with on-chain transaction histories that create verifiable track records for creditworthiness assessment. Inkwell Finance is specifically targeting this market, recognizing that AI agents will need wallets and capital to operate effectively. The programmatic nature of D-wallets pairs perfectly with AI agents, as policy controls can restrict agent behavior to specific smart contract interactions, preventing unauthorized fund transfers while allowing automated trading or revenue generation. This creates a new category of borrower that operates 24/7 with completely transparent performance metrics, fundamentally different from traditional loan recipients.6. Cross-Chain Liquidity Without Asset Transfer: Ika's technology enables users to take loans against revenue generated on one blockchain and deploy that capital on entirely different blockchains without moving their original liquidity positions. For instance, someone earning yield on Sui's Fusol protocol could borrow against that revenue stream and deploy capital on Solana opportunities, effectively creating multiple on-chain businesses that generate their own credit scores and revenue to service debt. This ability to read state across different blockchains from within smart contracts opens possibilities for multi-chain strategies that don't require withdrawing capital from productive positions, maximizing capital efficiency across the entire crypto ecosystem.7. The Convergence of Traditional Finance and Crypto Infrastructure: The regulatory landscape is rapidly evolving with initiatives like the Genius Act and Clarity Act creating frameworks where traditional financial systems merge with crypto infrastructure through mechanisms like stablecoins backed by US treasuries. Companies are increasingly establishing entities in the United States to access capital networks and Delaware's established legal framework while issuing tokens through jurisdictions like Switzerland. This hybrid approach, combined with emerging concepts like Gabriel Shapiro's "cybernetic agreements" that make smart contract parameters legally enforceable in traditional courts, suggests the future isn't pure decentralization but rather a sophisticated integration of on-chain and off-chain legal and financial systems.
In this episode of the Grownlearn Podcast, I speak with Sean Tepper — Founder & CEO of Tykr — about what it really takes to invest intelligently and build a scalable fintech company from scratch. Sean started with a simple Excel-based stock rating model. Today, Tykr serves over 13,000 customers across 50+ countries and is raising a $1.3M seed round — after achieving strong product-market fit, improving conversion rates from 25% to 70%, and reducing churn below 5%. We discuss: • Where beginners should actually start with investing • Investing vs trading — and why most people confuse the two • The #1 mistake retail investors make • How to avoid losing money in the stock market • Why fundamentals still matter in a tokenized world • How Tykr outperformed the S&P 500 • What real product-market fit looks like before raising capital • SaaS subscription growth strategies that actually work Sean also shares transparent performance data, marketing insights (including YouTube as a lead engine), and why open-source calculations helped build trust with both users and regulators. If you're a founder, investor, SaaS builder, or simply someone who wants to make smarter long-term financial decisions — this episode delivers clarity.
Tiffany Yeh, MD is the CEO and Co-Founder of Eztia Materials, a climate-tech venture developing energy-efficient cooling materials to protect people from extreme heat. With a mission to advance hard tech solutions at the climate-health nexus, Tiffany draws on her unique background as a physician, engineer, and public health advocate to build technologies that improve global health in a warming world.(01:13) - Dr. Ye's Background & Inspiration (01:52) - The Heat Challenge(05:20) - Singapore and the Power of Cooling(06:32) - Why Construction Has Been Slow to Adapt (07:22) - The Human Factor(08:14) - HydroVolt Technology(09:29) - Business Model, Distribution & Competition(11:19) - Worker Comfort (15:32) - Hidden Productivity Crisis Brewing(18:18) - Feature: Blueprint: The Future of Real Estate 2026 in Vegas on Sep. 22-24 (19:21) - The Secret Sauce Behind HydroVolt (20:31) - Prototyping & Real-World Applications (21:32) - Measuring Impact & ROI (23:34) - Pitching to VCs & Investors(25:31) - Product Roadmap(29:08) - Collaboration Superpower: Lionel Messi
Welcome back to the EUVC Podcast, where we bring you the people and perspectives shaping European venture.In this pitch episode, Andreas Munk Holm sits down with Pedro Ribeiro Santos, Partner at Armilar, to walk LPs through the story, strategy, and succession plan behind Armilar Fund IV — the firm's new pan-European early-stage fund.Armilar is one of Europe's longest-standing independent tech VCs and Portugal's original venture firm. Born inside a bank 25 years ago, spun out almost a decade ago, and now a multi-generational partnership, the firm has backed some of Portugal's most important tech companies and quietly built a track record of dragons (fund-returners), not just unicorns.Fund IV doubles down on what the team knows best: early-stage, tech-intensive companies across data, digitalization, and connectivity, with a strong focus on Portugal & Spain and selective investments across the rest of Europe.ShareHere's what's covered:01:17 | What is “Armilar”?02:30 | Origins & Spinout 03:40 | Why being based in Portugal with almost no local ecosystem 04:50 | From US to Europe, Then Back Home 07:22 | Fund IV in a Nutshell 09:44 | Geography & LP Backbone11:41 | Track Record, DPI & Dragons 13:51 | Selected Portfolio & Staying Power 16:19 | Team & Generational Design 21:38 | Iberia's State of Play (Portugal & Spain) 27:45 | Golden Visa & LP Angle 29:29 | Closing & What LPs Should Care About
Episode 80: Fair Investment Practices by Venture Capital Companies Law Quick hit today to discuss California's new Fair Investment Practices by Venture Capital Companies Law (“California Regulatory Overreach” as I call it), which mandates venture capital firms to collect and report demographic data about the founding teams of the companies they invest in. I outline the requirements, implications, and potential challenges that VCs may face due to this law, and share my concerns about its practicality and the reliability of the data collected. Key Points From This Episode: Who is subject to this new law?What must Covered Entities do to comply?By when must they do all this?My quick takes on this new law.One piece of advice moving forward. Disclaimer: This show is for informational purposes only. Nothing presented here constitutes legal, investment or tax advice. The guests that join us share their considerable fund-related wisdom, but everything they share here is their personal opinion and for educational purposes only. On this show, they are speaking for themselves, and not for their employer or any affiliated entity. Tokens of Wisdom is produced by Dave Rothschild, partner at Cole-Frieman & Mallon LLP headquartered in San Francisco, California. For more information, visit https://colefrieman.com/ Links Mentioned in Today's Episode: Dave Rothschild - https://www.linkedin.com/in/davidcrothschild/Cole-Frieman & Mallon LLP - https://colefrieman.com/Music by Joe Ginsberg - https://www.instagram.com/thejoeginsbergFor any questions or comments, email: tow@colefrieman.com
Infrastructure was passé…uncool. Difficult to get dollars from Private Equity and Growth funds, and almost impossible to get a VC fund interested. Now?! Now, it's cool. Infrastructure seems to be having a Renaissance, a full on Rebirth, not just fueled by commercial interests (e.g. advent of AI), but also by industrial policy and geopolitical considerations. In this episode of Tech Deciphered, we explore what's cool in the infrastructure spaces, including mega trends in semiconductors, energy, networking & connectivity, manufacturing Navigation: Intro We're back to building things Why now: the 5 forces behind the renaissance Semiconductors: compute is the new oil Networking & connectivity: digital highways get rebuilt Energy: rebuilding the power stack (not just renewables) Manufacturing: the return of “atoms + bits” Wrap: what it means for startups, incumbents, and investors Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Gonçalves Pedro Introduction Welcome to episode 73 of Tech Deciphered, Infrastructure, the Rebirth or Renaissance. Infrastructure was passé, it wasn’t cool, but all of a sudden now everyone’s talking about network, talking about compute and semiconductors, talking about logistics, talking about energy. What gives? What’s happened? It was impossible in the past to get any funds, venture capital, even, to be honest, some private equity funds or growth funds interested in some of these areas, but now all of a sudden everyone thinks it’s cool. The infrastructure seems to be having a renaissance, a full-on rebirth. In this episode, we will explore in which cool ways the infrastructure spaces are moving and what’s leading to it. We will deep dive into the forces that are leading us to this. We will deep dive into semiconductors, networking and connectivity, energy, manufacturing, and then we’ll wrap up. Bertrand, so infrastructure is cool now. Bertrand Schmitt We're back to building things Yes. I thought software was going to eat the world. I cannot believe it was then, maybe even 15 years ago, from Andreessen, that quote about software eating the world. I guess it’s an eternal balance. Sometimes you go ahead of yourself, you build a lot of software stack, and at some point, you need the hardware to run this software stack, and there is only so much the bits can do in a world of atoms. Nuno Gonçalves Pedro Obviously, we’ve gone through some of this before. I think what we’re going through right now is AI is eating the world, and because AI is eating the world, it’s driving a lot of this infrastructure building that we need. We don’t have enough energy to be consumed by all these big data centers and hyperscalers. We need to be innovative around network as well because of the consumption in terms of network bandwidth that is linked to that consumption as well. In some ways, it’s not software eating the world, AI is eating the world. Because AI is eating the world, we need to rethink everything around infrastructure and infrastructure becoming cool again. Bertrand Schmitt There is something deeper in this. It’s that the past 10, even 15 years were all about SaaS before AI. SaaS, interestingly enough, was very energy-efficient. When I say SaaS, I mean cloud computing at large. What I mean by energy-efficient is that actually cloud computing help make energy use more efficient because instead of companies having their own separate data centers in many locations, sometimes poorly run from an industrial perspective, replace their own privately run data center with data center run by the super scalers, the hyperscalers of the world. These data centers were run much better in terms of how you manage the coolings, the energy efficiency, the rack density, all of this stuff. Actually, the cloud revolution didn’t increase the use of electricity. The cloud revolution was actually a replacement from your private data center to the hyperscaler data center, which was energy efficient. That’s why we didn’t, even if we are always talking about that growth of cloud computing, we were never feeling the pinch in term of electricity. As you say, we say it all changed because with AI, it was not a simple “Replacement” of locally run infrastructure to a hyperscaler run infrastructure. It was truly adding on top of an existing infrastructure, a new computing infrastructure in a way out of nowhere. Not just any computing infrastructure, an energy infrastructure that was really, really voracious in term of energy use. Nuno Gonçalves Pedro There was one other effect. Obviously, we’ve discussed before, we are in a bubble. We won’t go too much into that today. But the previous big bubble in tech, which is in the late ’90s, there was a lot of infrastructure built. We thought the internet was going to take over back then. It didn’t take over immediately, but there was a lot of network connectivity, bandwidth built back in the day. Companies imploded because of that as well, or had to restructure and go in their chapter 11. A lot of the big telco companies had their own issues back then, etc., but a lot of infrastructure was built back then for this advent of the internet, which would then take a long time to come. In some ways, to your point, there was a lot of latent supply that was built that was around that for a while wasn’t used, but then it was. Now it’s been used, and now we need new stuff. That’s why I feel now we’re having the new moment of infrastructure, new moment of moving forward, aligned a little bit with what you just said around cloud computing and the advent of SaaS, but also around the fact that we had a lot of buildup back in the late ’90s, early ’90s, which we’re now still reaping the benefits on in today’s world. Bertrand Schmitt Yeah, that’s actually a great point because what was built in the late ’90s, there was a lot of fibre that was built. Laying out the fibre either across countries, inside countries. This fibre, interestingly enough, you could just change the computing on both sides of the fibre, the routing, the modems, and upgrade the capacity of the fibre. But the fibre was the same in between. The big investment, CapEx investment, was really lying down that fibre, but then you could really upgrade easily. Even if both ends of the fibre were either using very old infrastructure from the ’90s or were actually dark and not being put to use, step by step, it was being put to use, equipment was replaced, and step by step, you could keep using more and more of this fibre. It was a very interesting development, as you say, because it could be expanded over the years, where if we talk about GPUs, use for AI, GPUs, the interesting part is actually it’s totally the opposite. After a few years, it’s useless. Some like Google, will argue that they can depreciate over 5, 6 years, even some GPUs. But at the end of the day, the difference in perf and energy efficiency of the GPUs means that if you are energy constrained, you just want to replace the old one even as young as three-year-old. You have to look at Nvidia increasing spec, generation after generation. It’s pretty insane. It’s usually at least 3X year over year in term of performance. Nuno Gonçalves Pedro At this moment in time, it’s very clear that it’s happening. Why now: the 5 forces behind the renaissance Maybe let’s deep dive into why it’s happening now. What are the key forces around this? We’ve identified, I think, five forces that are particularly vital that lead to the world we’re in right now. One we’ve already talked about, which is AI, the demand shock and everything that’s happened because of AI. Data centers drive power demand, drive grid upgrades, drive innovative ways of getting energy, drive chips, drive networking, drive cooling, drive manufacturing, drive all the things that we’re going to talk in just a bit. One second element that we could probably highlight in terms of the forces that are behind this is obviously where we are in terms of cost curves around technology. Obviously, a lot of things are becoming much cheaper. The simulation of physical behaviours has become a lot more cheap, which in itself, this becomes almost a vicious cycle in of itself, then drives the adoption of more and more AI and stuff. But anyway, the simulation is becoming more and more accessible, so you can do a lot of simulation with digital twins and other things off the real world before you go into the real world. Robotics itself is becoming, obviously, cheaper. Hardware, a lot of the hardware is becoming cheaper. Computer has become cheaper as well. Obviously, there’s a lot of cost curves that have aligned that, and that’s maybe the second force that I would highlight. Obviously, funds are catching up. We’ll leave that a little bit to the end. We’ll do a wrap-up and talk a little bit about the implications to investors. But there’s a lot of capital out there, some capital related to industrial policy, other capital related to private initiative, private equity, growth funds, even venture capital, to be honest, and a few other elements on that. That would be a third force that I would highlight. Bertrand Schmitt Yes. Interestingly enough, in terms of capital use, and we’ll talk more about this, but some firms, if we are talking about energy investment, it was very difficult to invest if you are not investing in green energy. Now I think more and more firms and banks are willing to invest or support different type of energy infrastructure, not just, “Green energy.” That’s an interesting development because at some point it became near impossible to invest more in gas development, in oil development in the US or in most Western countries. At least in the US, this is dramatically changing the framework. Nuno Gonçalves Pedro Maybe to add the two last forces that I think we see behind the renaissance of what’s happening in infrastructure. They go hand in hand. One is the geopolitics of the world right now. Obviously, the world was global flat, and now it’s becoming increasingly siloed, so people are playing it to their own interests. There’s a lot of replication of infrastructure as well because people want to be autonomous, and they want to drive their own ability to serve end consumers, businesses, etc., in terms of data centers and everything else. That ability has led to things like, for example, chips shortage. The fact that there are semiconductors, there are shortages across the board, like memory shortages, where everything is packed up until 2027 of 2028. A lot of the memory that was being produced is already spoken for, which is shocking. There’s obviously generation of supply chain fragilities, obviously, some of it because of policies, for example, in the US with tariffs, etc, security of energy, etc. Then the last force directly linked to the geopolitics is the opposite of it, which is the policy as an accelerant, so to speak, as something that is accelerating development, where because of those silos, individual countries, as part their industrial policy, then want to put capital behind their local ecosystems, their local companies, so that their local companies and their local systems are for sure the winners, or at least, at the very least, serve their own local markets. I think that’s true of a lot of the things we’re seeing, for example, in the US with the Chips Act, for semiconductors, with IGA, IRA, and other elements of what we’ve seen in terms of practices, policies that have been implemented even in Europe, China, and other parts of the world. Bertrand Schmitt Talking about chips shortages, it’s pretty insane what has been happening with memory. Just the past few weeks, I have seen a close to 3X increase in price in memory prices in a matter of weeks. Apparently, it started with a huge order from OpenAI. Apparently, they have tried to corner the memory market. Interestingly enough, it has flat-footed the entire industry, and that includes Google, that includes Microsoft. There are rumours of their teams now having moved to South Korea, so they are closer to the action in terms of memory factories and memory decision-making. There are rumours of execs who got fired because they didn’t prepare for this type of eventuality or didn’t lock in some of the supply chain because that memory was initially for AI, but obviously, it impacts everything because factories making memories, you have to plan years in advance to build memories. You cannot open new lines of manufacturing like this. All factories that are going to open, we know when they are going to open because they’ve been built up for years. There is no extra capacity suddenly. At the very best, you can change a bit your line of production from one type of memory to another type. But that’s probably about it. Nuno Gonçalves Pedro Just to be clear, all these transformations we’re seeing isn’t to say just hardware is back, right? It’s not just hardware. There’s physicality. The buildings are coming back, right? It’s full stack. Software is here. That’s why everything is happening. Policy is here. Finance is here. It’s a little bit like the name of the movie, right? Everything everywhere all at once. Everything’s happening. It was in some ways driven by the upper stacks, by the app layers, by the platform layers. But now we need new infrastructure. We need more infrastructure. We need it very, very quickly. We need it today. We’re already lacking in it. Semiconductors: compute is the new oil Maybe that’s a good segue into the first piece of the whole infrastructure thing that’s driving now the most valuable company in the world, NVIDIA, which is semiconductors. Semiconductors are driving compute. Semis are the foundation of infrastructure as a compute. Everyone needs it for every thing, for every activity, not just for compute, but even for sensors, for actuators, everything else. That’s the beginning of it all. Semiconductor is one of the key pieces around the infrastructure stack that’s being built at scale at this moment in time. Bertrand Schmitt Yes. What’s interesting is that if we look at the market gap of Semis versus software as a service, cloud companies, there has been a widening gap the past year. I forgot the exact numbers, but we were talking about plus 20, 25% for Semis in term of market gap and minus 5, minus 10 for SaaS companies. That’s another trend that’s happening. Why is this happening? One, because semiconductors are core to the AI build-up, you cannot go around without them. But two, it’s also raising a lot of questions about the durability of the SaaS, a software-as-a-service business model. Because if suddenly we have better AI, and that’s all everyone is talking about to justify the investment in AI, that it keeps getting better, and it keeps improving, and it’s going to replace your engineers, your software engineers. Then maybe all of this moat that software companies built up over the years or decades, sometimes, might unravel under the pressure of newly coded, newly built, cheaper alternatives built from the ground up with AI support. It’s not just that, yes, semiconductors are doing great. It’s also as a result of that AI underlying trend that software is doing worse right now. Nuno Gonçalves Pedro At the end of the day, this foundational piece of infrastructure, semiconductor, is obviously getting manifest to many things, fabrication, manufacturing, packaging, materials, equipment. Everything’s being driven, ASML, etc. There are all these different players around the world that are having skyrocket valuations now, it’s because they’re all part of the value chain. Just to be very, very clear, there’s two elements of this that I think are very important for us to remember at this point in time. One, it’s the entire value chains are being shifted. It’s not just the chips that basically lead to computing in the strict sense of it. It’s like chips, for example, that drive, for example, network switching. We’re going to talk about networking a bit, but you need chips to drive better network switching. That’s getting revolutionised as well. For example, we have an investment in that space, a company called the eridu.ai, and they’re revolutionising one of the pieces around that stack. Second part of the puzzle, so obviously, besides the holistic view of the world that’s changing in terms of value change, the second piece of the puzzle is, as we discussed before, there’s industrial policy. We already mentioned the CHIPS Act, which is something, for example, that has been done in the US, which I think is 52 billion in incentives across a variety of things, grants, loans, and other mechanisms to incentivise players to scale capacity quick and to scale capacity locally in the US. One of the effects of that now is obviously we had the TSMC, US expansion with a factory here in the US. We have other levels of expansion going on with Intel, Samsung, and others that are happening as we speak. Again, it’s this two by two. It’s market forces that drive the need for fundamental shifts in the value chain. On the other industrial policy and actual money put forward by states, by governments, by entities that want to revolutionise their own local markets. Bertrand Schmitt Yes. When you talk about networking, it makes me think about what NVIDIA did more than six years ago when they acquired Mellanox. At the time, it was largest acquisition for NVIDIA in 2019, and it was networking for the data center. Not networking across data center, but inside the data center, and basically making sure that your GPUs, the different computers, can talk as fast as possible between each of them. I think that’s one piece of the puzzle that a lot of companies are missing, by the way, about NVIDIA is that they are truly providing full systems. They are not just providing a GPU. Some of their competitors are just providing GPUs. But NVIDIA can provide you the full rack. Now, they move to liquid-cool computing as well. They design their systems with liquid cooling in mind. They have a very different approach in the industry. It’s a systematic system-level approach to how do you optimize your data center. Quite frankly, that’s a bit hard to beat. Nuno Gonçalves Pedro For those listening, you’d be like, this is all very different. Semiconductors, networking, energy, manufacturing, this is all different. Then all of a sudden, as Bertrand is saying, well, there are some players that are acting across the stack. Then you see in the same sentence, you’re talking about nuclear power in Microsoft or nuclear power in Google, and you’re like, what happened? Why are these guys in the same sentence? It’s like they’re tech companies. Why are they talking about energy? It’s the nature of that. These ecosystems need to go hand in hand. The value chains are very deep. For you to actually reap the benefits of more and more, for example, semiconductor availability, you have to have better and better networking connectivity, and you have to have more and more energy at lower and lower costs, and all of that. All these things are intrinsically linked. That’s why you see all these big tech companies working across stack, NVIDIA being a great example of that in trying to create truly a systems approach to the world, as Bertrand was mentioning. Networking & connectivity: digital highways get rebuilt On the networking and connectivity side, as we said, we had a lot of fibre that was put down, etc, but there’s still more build-out needs to be done. 5G in terms of its densification is still happening. We’re now starting to talk, obviously, about 6G. I’m not sure most telcos are very happy about that because they just have been doing all this CapEx and all this deployment into 5G, and now people already started talking about 6G and what’s next. Obviously, data center interconnect is quite important, and all the hubbing that needs to happen around data centers is very, very important. We are seeing a lot movements around connectivity that are particularly important. Network gear and the emergence of players like Broadcom in terms of the semiconductor side of the fence, obviously, Cisco, Juniper, Arista, and others that are very much present in this space. As I said, we made an investment on the semiconductor side of networking as well, realizing that there’s still a lot of bottlenecks happening there. But obviously, the networking and connectivity stack still needs to be built at all levels within the data centers, outside of the data centers in terms of last mile, across the board in terms of fibre. We’re seeing a lot of movements still around the space. It’s what connects everything. At the end of the day, if there’s too much latency in these systems, if the bandwidths are not high enough, then we’re going to have huge bottlenecks that are going to be put at the table by a networking providers. Obviously, that doesn’t help anyone. If there’s a button like anywhere, it doesn’t work. All of this doesn’t work. Bertrand Schmitt Yes. Interestingly enough, I know we said for this episode, we not talk too much about space, but when you talk about 6G, it make me think about, of course, Starlink. That’s really your last mile delivery that’s being built as well. It’s a massive investment. We’re talking about thousands of satellites that are interconnected between each other through laser system. This is changing dramatically how companies can operate, how individuals can operate. For companies, you can have great connectivity from anywhere in the world. For military, it’s the same. For individuals, suddenly, you won’t have dead space, wide zones. This is also a part of changing how we could do things. It’s quite important even in the development of AI because, yes, you can have AI at the edge, but that interconnect to the rest of the system is quite critical. Having that availability of a network link, high-quality network link from anywhere is a great combo. Nuno Gonçalves Pedro Then you start seeing regions of the world that want to differentiate to attract digital nomads by saying, “We have submarine cables that come and hub through us, and therefore, our connectivity is amazing.” I was just in Madeira, and they were talking about that in Portugal. One of the islands of Portugal. We have some Marine cables. You have great connectivity. We’re getting into that discussion where people are like, I don’t care. I mean, I don’t know. I assume I have decent connectivity. People actually care about decent connectivity. This discussion is not just happening at corporate level, at enterprise level? Etc. Even consumers, even people that want to work remotely or be based somewhere else in the world. It’s like, This is important Where is there a great connectivity for me so that I can have access to the services I need? Etc. Everyone becomes aware of everything. We had a cloud flare mishap more recently that the CEO had to jump online and explain deeply, technically and deeply, what happened. Because we’re in their heads. If Cloudflare goes down, there’s a lot of websites that don’t work. All of this, I think, is now becoming du jour rather than just an afterthought. Maybe we’ll think about that in the future. Bertrand Schmitt Totally. I think your life is being changed for network connectivity, so life of individuals, companies. I mean, everything. Look at airlines and ships and cruise ships. Now is the advent of satellite connectivity. It’s dramatically changing our experience. Nuno Gonçalves Pedro Indeed. Energy: rebuilding the power stack (not just renewables) Moving maybe to energy. We’ve talked about energy quite a bit in the past. Maybe we start with the one that we didn’t talk as much, although we did mention it, which was, let’s call it the fossil infrastructure, what’s happening around there. Everyone was saying, it’s all going to be renewables and green. We’ve had a shift of power, geopolitics. Honestly, I the writing was on the wall that we needed a lot more energy creation. It wasn’t either or. We needed other sources to be as efficient as possible. Obviously, we see a lot of work happening around there that many would have thought, Well, all this infrastructure doesn’t matter anymore. Now we’re seeing LNG terminals, pipelines, petrochemical capacity being pushed up, a lot of stuff happening around markets in terms of export, and not only around export, but also around overall distribution and increases and improvements so that there’s less leakage, distribution of energy, etc. In some ways, people say, it’s controversial, but it’s like we don’t have enough energy to spare. We’re already behind, so we need as much as we can. We need to figure out the way to really extract as much as we can from even natural resources, which In many people’s mind, it’s almost like blasphemous to talk about, but it is where we are. Obviously, there’s a lot of renaissance also happening on the fossil infrastructure basis, so to speak. Bertrand Schmitt Personally, I’m ecstatic that there is a renaissance going regarding what is called fossil infrastructure. Oil and gas, it’s critical to humanity well-being. You never had growth of countries without energy growth and nothing else can come close. Nuclear could come close, but it takes decades to deploy. I think it’s great. It’s great for developed economies so that they do better, they can expand faster. It’s great for third-world countries who have no realistic other choice. I really don’t know what happened the past 10, 15 years and why this was suddenly blasphemous. But I’m glad that, strangely, thanks to AI, we are back to a more rational mindset about energy and making sure we get efficient energy where we can. Obviously, nuclear is getting a second act. Nuno Gonçalves Pedro I know you would be. We’ve been talking about for a long time, and you’ve been talking about it in particular for a very long time. Bertrand Schmitt Yes, definitely. It’s been one area of interest of mine for 25 years. I don’t know. I’ve been shocked about what happened in Europe, that willingness destruction of energy infrastructure, especially in Germany. Just a few months ago, they keep destroying on live TV some nuclear station in perfect working condition and replacing them with coal. I’m not sure there is a better definition of insanity at this stage. It looks like it’s only the Germans going that hardcore for some reason, but at least the French have stopped their program of decommissioning. America, it seems to be doing the same, so it’s great. On top of it, there are new generations that could be put to use. The Chinese are building up a very large nuclear reactor program, more than 100 reactors in construction for the next 10 years. I think everybody has to catch up because at some point, this is the most efficient energy solution. Especially if you don’t build crazy constraints around the construction of these nuclear reactors. If we are rational about permits, about energy, about safety, there are great things we could be doing with nuclear. That might be one of the only solution if we want to be competitive, because when energy prices go down like crazy, like in China, they will do once they have reach delivery of their significant build-up of nuclear reactors, we better be ready to have similar options from a cost perspective. Nuno Gonçalves Pedro From the outside, at the very least, nuclear seems to be probably in the energy one of the areas that’s more being innovated at this moment in time. You have startups in the space, you have a lot really money going into it, not just your classic industrial development. That’s very exciting. Moving maybe to the carbonization and what’s happening. The CCUS, and for those who don’t know what it is, carbon capture, utilization, and storage. There’s a lot of stuff happening around that space. That’s the area that deals with the ability to capture CO₂ emissions from industrial sources and/or the atmosphere and preventing their release. There’s a lot of things happening in that space. There’s also a lot of things happening around hydrogen and geothermal and really creating the ability to storage or to store, rather, energy that then can be put back into the grids at the right time. There’s a lot of interesting pieces happening around this. There’s some startup movement in the space. It’s been a long time coming, the reuse of a lot of these industrial sources. Not sure it’s as much on the news as nuclear, and oil and gas, but certainly there’s a lot of exciting things happening there. Bertrand Schmitt I’m a bit more dubious here, but I think geothermal makes sense if it’s available at reasonable price. I don’t think hydrogen technology has proven its value. Concerning carbon capture, I’m not sure how much it’s really going to provide in terms of energy needs, but why not? Nuno Gonçalves Pedro Fuels niche, again, from the outside, we’re not energy experts, but certainly, there are movements in the space. We’ll see what’s happening. One area where there’s definitely a lot of movement is this notion of grid and storage. On the one hand, that transmission needs to be built out. It needs to be better. We’ve had issues of blackouts in the US. We’ve had issues of blackouts all around the world, almost. Portugal as well, for a significant part of the time. The ability to work around transmission lines, transformers, substations, the modernization of some of this infrastructure, and the move forward of it is pretty critical. But at the other end, there’s the edge. Then, on the edge, you have the ability to store. We should have, better mechanisms to store energy that are less leaky in terms of energy storage. Obviously, there’s a lot of movement around that. Some of it driven just by commercial stuff, like Tesla a lot with their storage stuff, etc. Some of it really driven at scale by energy players that have the interest that, for example, some of the storage starts happening closer to the consumption as well. But there’s a lot of exciting things happening in that space, and that is a transformative space. In some ways, the bottleneck of energy is also around transmission and then ultimately the access to energy by homes, by businesses, by industries, etc. Bertrand Schmitt I would say some of the blackout are truly man-made. If I pick on California, for instance. That’s the logical conclusion of the regulatory system in place in California. On one side, you limit price that energy supplier can sell. The utility company can sell, too. On the other side, you force them to decommission the most energy-efficient and least expensive energy source. That means you cap the revenues, you make the cost increase. What is the result? The result is you cannot invest anymore to support a grid and to support transmission. That’s 100% obvious. That’s what happened, at least in many places. The solution is stop crazy regulations that makes no economic sense whatsoever. Then, strangely enough, you can invest again in transmission, in maintenance, and all I love this stuff. Maybe another piece, if we pick in California, if you authorize building construction in areas where fires are easy, that’s also a very costly to support from utility perspective, because then you are creating more risk. You are forced buy the state to connect these new constructions to the grid. You have more maintenance. If it fails, you can create fire. If you create fire, you have to pay billions of fees. I just want to highlight that some of this is not a technological issue, is not per se an investment issue, but it’s simply the result of very bad regulations. I hope that some will learn, and some change will be made so that utilities can do their job better. Nuno Gonçalves Pedro Then last, but not the least, on the energy side, energy is becoming more and more digitally defined in some ways. It’s like the analogy to networks that they’ve become more, and more software defined, where you have, at the edge is things like smart meters. There’s a lot of things you can do around the key elements of the business model, like dynamic pricing and other elements. Demand response, one of the areas that I invested in, I invest in a company called Omconnect that’s now merged with what used to be Google Nest. Where to deploy that ability to do demand response and also pass it to consumers so that consumers can reduce their consumption at times where is the least price effective or the less green or the less good for the energy companies to produce energy. We have other things that are happening, which are interesting. Obviously, we have a lot more electric vehicles in cars, etc. These are also elements of storage. They don’t look like elements of storage, but the car has electricity in it once you charge it. Once it’s charged, what do you do with it? Could you do something else? Like the whole reverse charging piece that we also see now today in mobile devices and other edge devices, so to speak. That also changes the architecture of what we’re seeing around the space. With AI, there’s a lot of elements that change around the value chain. The ability to do forecasting, the ability to have, for example, virtual power plans because of just designated storage out there, etc. Interesting times happening. Not sure all utilities around the world, all energy providers around the world are innovating at the same pace and in the same way. But certainly just looking at the industry and talking to a lot of players that are CEOs of some of these companies. That are leading innovation for some of these companies, there’s definitely a lot more happening now in the last few years than maybe over the last few decades. Very exciting times. Bertrand Schmitt I think there are two interesting points in what you say. Talking about EVs, for instance, a Cybertruck is able to send electricity back to your home if your home is able to receive electricity from that source. Usually, you have some changes to make to the meter system, to your panel. That’s one great way to potentially use your car battery. Another piece of the puzzle is that, strangely enough, most strangely enough, there has been a big push to EV, but at the same time, there has not been a push to provide more electricity. But if you replace cars that use gasoline by electric vehicles that use electricity, you need to deliver more electricity. It doesn’t require a PhD to get that. But, strangely enough, nothing was done. Nuno Gonçalves Pedro Apparently, it does. Bertrand Schmitt I remember that study in France where they say that, if people were all to switch to EV, we will need 10 more nuclear reactors just on the way from Paris to Nice to the Côte d’Azur, the French Rivière, in order to provide electricity to the cars going there during the summer vacation. But I mean, guess what? No nuclear plant is being built along the way. Good luck charging your vehicles. I think that’s another limit that has been happening to the grid is more electric vehicles that require charging when the related infrastructure has not been upgraded to support more. Actually, it has quite the opposite. In many cases, we had situation of nuclear reactors closing down, so other facilities closing down. Obviously, the end result is an increase in price of electricity, at least in some states and countries that have not sold that fully out. Nuno Gonçalves Pedro Manufacturing: the return of “atoms + bits” Moving to manufacturing and what’s happening around manufacturing, manufacturing technology. There’s maybe the case to be made that manufacturing is getting replatformed, right? It’s getting redefined. Some of it is very obvious, and it’s already been ongoing for a couple of decades, which is the advent of and more and more either robotic augmented factories or just fully roboticized factories, where there’s very little presence of human beings. There’s elements of that. There’s the element of software definition on top of it, like simulation. A lot of automation is going on. A lot of AI has been applied to some lines in terms of vision, safety. We have an investment in a company called Sauter Analytics that is very focused on that from the perspective of employees and when they’re still humans in the loop, so to speak, and the ability to really figure out when people are at risk and other elements of what’s happening occurring from that. But there’s more than that. There’s a little bit of a renaissance in and of itself. Factories are, initially, if we go back a couple of decades ago, factories were, and manufacturing was very much defined from the setup. Now it’s difficult to innovate, it’s difficult to shift the line, it’s difficult to change how things are done in the line. With the advent of new factories that have less legacy, that have more flexible systems, not only in terms of software, but also in terms of hardware and robotics, it allows us to, for example, change and shift lines much more easily to different functions, which will hopefully, over time, not only reduce dramatically the cost of production. But also increase dramatically the yield, it increases dramatically the production itself. A lot of cool stuff happening in that space. Bertrand Schmitt It’s exciting to see that. One thing this current administration in the US has been betting on is not just hoping for construction renaissance. Especially on the factory side, up of factories, but their mindset was two things. One, should I force more companies to build locally because it would be cheaper? Two, increase output and supply of energy so that running factories here in the US would be cheaper than anywhere else. Maybe not cheaper than China, but certainly we get is cheaper than Europe. But three, it’s also the belief that thanks to AI, we will be able to have more efficient factories. There is always that question, do Americans to still keep making clothes, for instance, in factories. That used to be the case maybe 50 years ago, but this move to China, this move to Bangladesh, this move to different places. That’s not the goal. But it can make sense that indeed there is ability, thanks to robots and AI, to have more automated factories, and these factories could be run more efficiently, and as a result, it would be priced-competitive, even if run in the US. When you want to think about it, that has been, for instance, the South Korean playbook. More automated factories, robotics, all of this, because that was the only way to compete against China, which has a near infinite or used to have a near infinite supply of cheaper labour. I think that all of this combined can make a lot of sense. In a way, it’s probably creating a perfect storm. Maybe another piece of the puzzle this administration has been working on pretty hard is simplifying all the permitting process. Because a big chunk of the problem is that if your permitting is very complex, very expensive, what take two years to build become four years, five years, 10 years. The investment mass is not the same in that situation. I think that’s a very important part of the puzzle. It’s use this opportunity to reduce regulatory state, make sure that things are more efficient. Also, things are less at risk of bribery and fraud because all these regulations, there might be ways around. I think it’s quite critical to really be careful about this. Maybe last piece of the puzzle is the way accounting works. There are new rules now in 2026 in the US where you can fully depreciate your CapEx much faster than before. That’s a big win for manufacturing in the US. Suddenly, you can depreciate much faster some of your CapEx investment in manufacturing. Nuno Gonçalves Pedro Just going back to a point you made and then moving it forward, even China, with being now probably the country in the world with the highest rate of innovation and take up of industrial robots. Because of demographic issues a little bit what led Japan the first place to be one of the real big innovators around robots in general. The fact that demographics, you’re having an aging population, less and less children. How are you going to replace all these people? Moving that into big winners, who becomes a big winner in a space where manufacturing is fundamentally changing? Obviously, there’s the big four of robots, which is ABB, FANUC, KUKA, and Yaskawa. Epson, I think, is now in there, although it’s not considered one of the big four. Kawasaki, Denso, Universal Robots. There’s a really big robotics, industrial robotic companies in the space from different origins, FANUC and Yaskawa, and Epson from Japan, KUKA from Germany, ABB from Switzerland, Sweden. A lot of now emerging companies from China, and what’s happening in that space is quite interesting. On the other hand, also, other winners will include players that will be integrators that will build some of the rest of the infrastructure that goes into manufacturing, the Siemens of the world, the Schneider’s, the Rockwell’s that will lead to fundamental industrial automation. Some big winners in there that whose names are well known, so probably not a huge amount of surprises there. There’s movements. As I said, we’re still going to see the big Chinese players emerging in the world. There are startups that are innovating around a lot of the edges that are significant in this space. We’ll see if this is a space that will just be continued to be dominated by the big foreign robotics and by a couple of others and by the big integrators or not. Bertrand Schmitt I think you are right to remind about China because China has been moving very fast in robotics. Some Chinese companies are world-class in their use of robotics. You have this strange mix of some older industries where robotics might not be so much put to use and typically state-owned, versus some private companies, typically some tech companies that are reconverting into hardware in some situation. That went all in terms of robotics use and their demonstrations, an example of what’s happening in China. Definitely, the Chinese are not resting. Everyone smart enough is playing that game from the Americans, the Chinese, Japanese, the South Koreans. Nuno Gonçalves Pedro Exciting things are manufacturing, and maybe to bring it all together, what does it mean for all the big players out there? If we talk with startups and talk about startups, we didn’t mention a ton of startups today, right? Maybe incumbent wind across the board. But on a more serious note, we did mention a few. For example, in nuclear energy, there’s a lot of startups that have been, some of them, incredibly well-funded at this moment in time. Wrap: what it means for startups, incumbents, and investors There might be some big disruptions that will come out of startups, for example, in that space. On the chipset side, we talked about the big gorillas, the NVIDIAs, AMDs, Intel, etc., of the world. But we didn’t quite talk about the fact that there’s a lot of innovation, again, happening on the edges with new players going after very large niches, be it in networking and switching. Be it in compute and other areas that will need different, more specialized solutions. Potentially in terms of compute or in terms of semiconductor deployments. I think there’s still some opportunities there, maybe not to be the winner takes all thing, but certainly around a lot of very significant niches that might grow very fast. Manufacturing, we mentioned the same. Some of the incumbents seem to be in the driving seat. We’ll see what happens if some startups will come in and take some of the momentum there, probably less likely. There are spaces where the value chains are very tightly built around the OEMs and then the suppliers overall, classically the tier one suppliers across value chains. Maybe there is some startup investment play. We certainly have played in the couple of the spaces. I mentioned already some of them today, but this is maybe where the incumbents have it all to lose. It’s more for them to lose rather than for the startups to win just because of the scale of what needs to be done and what needs to be deployed. Bertrand Schmitt I know. That’s interesting point. I think some players in energy production, for instance, are moving very fast and behaving not only like startups. Usually, it’s independent energy suppliers who are not kept by too much regulations that get moved faster. Utility companies, as we just discussed, have more constraints. I would like to say that if you take semiconductor space, there has been quite a lot of startup activities way more than usual, and there have been some incredible success. Just a few weeks ago, Rock got more or less acquired. Now, you have to play games. It’s not an outright acquisition, but $20 billion for an IP licensing agreement that’s close to an acquisition. That’s an incredible success for a company. Started maybe 10 years ago. You have another Cerebras, one of the competitor valued, I believe, quite a lot in similar range. I think there is definitely some activity. It’s definitely a different game compared to your software startup in terms of investment. But as we have seen with AI in general, the need for investment might be larger these days. Yes, it might be either traditional players if they can move fast enough, to be frank, because some of them, when you have decades of being run as a slow-moving company, it’s hard to change things. At the same time, it looks like VCs are getting bigger. Wall Street is getting more ready to finance some of these companies. I think there will be opportunities for startups, but definitely different types of startups in terms of profile. Nuno Gonçalves Pedro Exactly. From an investor standpoint, I think on the VC side, at least our core belief is that it’s more niche. It’s more around big niches that need to be fundamentally disrupted or solutions that require fundamental interoperability and integration where the incumbents have no motivation to do it. Things that are a little bit more either packaging on the semiconductor side or other elements of actual interoperability. Even at the software layer side that feeds into infrastructure. If you’re a growth investor, a private equity investor, there’s other plays that are available to you. A lot of these projects need to be funded and need to be scaled. Now we’re seeing projects being funded even for a very large, we mentioned it in one of the previous episodes, for a very large tech companies. When Meta, for example, is going to the market to get funding for data centers, etc. There’s projects to be funded there because just the quantum and scale of some of these projects, either because of financial interest for specifically the tech companies or for other reasons, but they need to be funded by the market. There’s other place right now, certainly if you’re a larger private equity growth investor, and you want to come into the market and do projects. Even public-private financing is now available for a lot of things. Definitely, there’s a lot of things emanating that require a lot of funding, even for large-scale projects. Which means the advent of some of these projects and where realization is hopefully more of a given than in other circumstances, because there’s actual commercial capital behind it and private capital behind it to fuel it as well, not just industrial policy and money from governments. Bertrand Schmitt There was this quite incredible stat. I guess everyone heard about that incredible growth in GDP in Q3 in the US at 4.4%. Apparently, half of that growth, so around 2.2% point, has been coming from AI and related infrastructure investment. That’s pretty massive. Half of your GDP growth coming from something that was not there three years ago or there, but not at this intensity of investment. That’s the numbers we are talking about. I’m hearing that there is a good chance that in 2026, we’re talking about five, even potentially 6% GDP growth. Again, half of it potentially coming from AI and all the related infrastructure growth that’s coming with AI. As a conclusion for this episode on infrastructure, as we just said, it’s not just AI, it’s a whole stack, and it’s manufacturing in general as well. Definitely in the US, in China, there is a lot going on. As we have seen, computing needs connectivity, networks, need power, energy and grid, and all of this needs production capacity and manufacturing. Manufacturing can benefit from AI as well. That way the loop is fully going back on itself. Infrastructure is the next big thing. It’s an opportunity, probably more for incumbents, but certainly, as usual, with such big growth opportunities for startups as well. Thank you, Nuno. Nuno Gonçalves Pedro Thank you, Bertrand.
Are you actually growing your product, or just stacking signups that never turn into usage?A lot of teams get stuck there. More registrations feel good, but it's not the same as real usage, paid adoption, and a pipeline you can trust. And now with AI in the mix, it's easy to create more activity without getting more signal.In this episode of B2B SaaS Marketing Snacks, hosts Stijn Hendrikse and Brian Grav bring on their first guest, Alex Laventer.Alex has spent years in growth roles in B2B SaaS, including leading growth at DataStax and now leading go-to-market work on an AI agent product at IBM.The conversation gets practical fast, what “growth” really means, and how teams split (or combine) growth marketing and product growth.You'll walk away with a clearer way to measure growth, how to set up tracking you can rely on, and where AI can help (and where it tends to distract), including lead scoring and workflow automation.In this episode, you'll learn:Why signups mislead growth conversationsWhere teams lose signal without trackingHow PQLs connect product and marketingPerspective on sales assist with PLGExample: AI-assisted lead scoring workflows By the end, you'll know what to measure, what to ignore, and what to fix next so “growth” stops being a vague label and starts being a real operating system. Resources shared in this episode:BSMS 88 - Why founders overestimate PLG, and what VCs should check before investingBSMS 23 - Product led growth vs. sales led growthThe Foundation of a Successful SaaS GTM (Go-to-Market) Strategy T2D3 CMO MasterclassSubmit and vote on our podcast topicsABOUT B2B SAAS MARKETING SNACKSSince 2020, The B2B SaaS Marketing Snacks Podcast has offered software company founders, investors and leadership a fresh source of insights into building a complete and efficient engine for growth.Meet our Marketing Snacks Podcast Hosts: Stijn Hendrikse: Author of T2D3 Masterclass & Book, Founder of KalungiAs a serial entrepreneur and marketing leader, Stijn has contributed to the success of 20+ startups as a C-level executive, including Chief Revenue Officer of Acumatica, CEO of MightyCall, a SaaS contact center solution, and leading the initial global Go-to-Market for Atera, a B2B SaaS Unicorn. Before focusing on startups, Stijn led global SMB Marketing and B2B Product Marketing for Microsoft's Office platform.Brian Graf: CEO of KalungiAs CEO of Kalungi, Brian provides high-level strategy, tactical execution, and business leadership expertise to drive long-term growth for B2B SaaS. Brian has successfully led clients in all aspects of marketing growth, from positioning and messaging to event support, product announcements, and channel-spend optimizations, generating qualified leads and brand awareness for clients while prioritizing ROI. Before Kalungi, Brian worked in television advertising, specializing in business intelligence and campaign optimization, and earned his MBA at the University of Washington's Foster School of Business with a focus in finance and marketing. Visit Kalungi.com to learn more about growing your B2B SaaS company.
Welcome to another episode of the EUVC Podcast! Today, we're diving into How Corporates Might just be able Beat VCs in the AI Race. Or maybe more importantly, how we can collaborate.Our guest is Alex Dang, co-author of the bestselling book The Venture Mindset: How to Make Smarter Bets and Achieve Extraordinary Growth. Alex is a seasoned technology executive and innovation advisor with over two decades of experience. He was a product leader at Amazon, where he launched new businesses across e-commerce, supply chain, and AI; a partner at McKinsey, helping Fortune 500 companies build digital ventures; and today advises corporate leaders and investors on AI strategies, venture building, and applying VC principles to large organizations.In this conversation, Alex shares provocative insights on why the venture mindset is now non-negotiable for corporates in the AI era, where incumbents hold hidden advantages over VCs, and how to avoid “innovation theater” while turning data, distribution, and scale into real venture wins.Let's jump in!Here's what's covered:01:56 | The Venture Mindset in one frame with nine principles from 20 years of Stanford VC research: uncertainty → portfolios → outliers03:44 | The post-book update Alex wishes he had added time compression: “days, not weeks,” and the rise of the “one slice team”05:53 | Venture mindset applied to AI 07:34 | Why “adding AI” is the wrong framing; start customer-backward, not tech-backward08:43 | “AI theater”, innovation theater and press release strategies vs real product value11:19 | The European corporate trap: regulation, consensus, and downside protection as the enemy of transformation11:56 | The right AI rollout sequence with start in back office to learn and protect trust, then go customer-facing at scale15:21 | Why CVCs die after 3.7 years: incentives, leadership fear, and why corporate venturing fails structurally17:24 | AI is now the world's most democratized intelligence: everyone has the same tools; the gap is execution18:47 | Where corporates fit in venture + startup ecosystems: strengths: data, distribution, enterprise scale20:38 | When corporates should build in-house, when to partner, and why AI must become an internal muscle25:24 | Incentives drive behavior: why executives won't take venture-style risks unless failure is structurally safe28:18 | AI-native teams and corporate reskilling among smaller, senior teams + digital workers replacing junior tasks35:24 | What happens to the average corporate employee: tasks disappear, workflows evolve, but people still matter38:50 | If Alex were CEO: how to move a workforce into an AI-safe future and target 25% profit uplift through AI44:01 | Most counterintuitive venture principle — “drop bad ideas fast” and why persistence is sometimes the wrong discipline46:05 | What top CEOs are doing right now: coding with Claude, learning by building, and staying close to users49:00 | The compounding effect: “what was impossible 6 months ago is normal today” and why constant feedback loops win
If you're an early-stage CPG founder struggling to raise money, it's probably not your product—it's your pitch list. In this episode we're talking about Why Your First Investor is Also Your Customer. We break down why the right investors are often already fans of your brand and your product, and how to identify those early believers. Make this mindset shift now and stop wasting time in the wrong rooms. Click below and start targeting smarter. Topics Covered; Your first investors are likely to be your customers. Many founders pitch to the wrong people, like VCs. Angel investors are often passionate about the problem you're solving. Lead with pain points, not product features. Finding believers in your product is crucial for early funding. Networking is key; start with personal connections. Ask your network for introductions to potential investors. The investor community is more cautious in uncertain times. Building momentum requires talking to many people. Shift your mindset from seeking investors to finding believers. About Your Host Jayla Siciliano, Shark Tank entrepreneur turned real estate investor, excels in building brands, teams, and products. CEO of a bi-coastal luxury short-term rental company, she also hosts the Seed Money Podcast, where she's on a mission to help early-stage entrepreneurs turn their ideas into reality! Connect Website: https://seedmoneypodcast.com/ Instagram: https://www.instagram.com/jaylasiciliano/ Subscribe and watch on YouTube https://www.youtube.com/@seedmoneypodcast/ Subscribe, Rate, & Review Please rate, follow, and review the podcast on https://podcasts.apple.com/us/podcast/seed-money/id1740815877 and https://open.spotify.com/show/0VkQECosb1spTFsUhu6uFY?si=5417351fb73a4ea1/! Hearing your comments and questions helps me come up with the best topics for the show! Disclaimer The information in this podcast is educational and general in nature and does not take into consideration the listener's personal circumstances. Therefore, it is not intended to be a substitute for specific, individualized financial, legal, or tax advice.
2025 marked the end of a four-year slide in series A financings for biotechs, with 144 biotechs raising an aggregate of $8 billion, up $1 billion from the prior two years. On the latest BioCentury This Week podcast, BioCentury's Danielle Golovin assesses which companies VCs backed last year and what their investments say about where technology is headed.Washington Editor Steve Usdin offers a perspective on why compounded Wegovy is an assault on the biopharma industry and also explains how the spending bill signed into law last week is a rebuke to proposed White House biomedical cuts.And Executive Editor Selina Koch unpacks her interview on The BioCentury Show podcast with neuroscientist and Seaport Chair Steven Paul, noting that while serendipity drives drug discovery in psychiatry, it's engineering that gets it across the finish line.View full story: https://www.biocentury.com/article/658367#BiotechFinancing #SeriesAFunding #VentureCapital #DrugDiscovery #BiopharmaPolicy00:00 - Introduction02:15 - Start-up Spotlight11:03 - Compounded Wegovy18:10 - Congress Rebuffs Trump Cuts23:50 - Steve Paul on NeuropsychiatryTo submit a question to BioCentury's editors, email the BioCentury This Week team at podcasts@biocentury.com.Reach us by sending a text
Red to Green - Food Tech | Sustainability | Food Innovation | Future of Food | Cultured Meat
Early-stage founders spend years learning how to fundraise from venture capitalists.But very few ever look beyond the VC sitting across the table.Just like founders need to fundraise from VCs, VCs need to fundraise from limited partners.Who are the guys who give VCs the molah-molah?What are the hidden incentives?And how those dynamics quietly shape fundraising, timing, and pressure.“Everyone thinks they're pitching one person. They're not.”Ariel Barack is a Senior Partner and the Chief Executive of Ordway Selections, a private investment office investing primarily in food and agriculture, health, blockchains, and digital assets.As Einstein said, “You have to learn the rules of the game. And then you have to play better than anyone else.”Well, today we will look at the rules of the game, so you can play better than anyone else.This was a very interesting conversation, and I hope you will enjoy it as much as I did.LinksConnect with Ariel Barackhttps://www.linkedin.com/in/arielbarack/Mentioned: Anterra Capitalhttps://anterracapital.com/Connect with the host:https://www.linkedin.com/in/schmidt-marina/marina@wearekinetik.comCould use some help with your comms? Check out https://www.wearekinetik.com/
Linktree: https://linktr.ee/AnalyticJoin The Normandy For Additional Bonus Audio And Visual Content For All Things Nme+! Join Here: https://ow.ly/msoH50WCu0KIn this segment of Notorious Mass Effect, Analytic Dreamz explores Royal Match, the dominant free-to-play match-3 puzzle game from Dream Games, the Istanbul-based powerhouse founded in 2019 by ex-Peak Games executives including CEO Soner Aydemir. Launched globally in early 2021 after a 2020 soft launch, it features King Robert as protagonist in polished, ad-free gameplay where players match 3+ tiles like crowns, coins, and shields to complete objectives—collecting items, breaking obstacles like vases and chains, or clearing paths—across move- or time-limited levels.The core loop includes regenerating lives (5 total), earning stars to decorate and progress the castle meta-layer, and deploying boosters like rockets, TNT, light balls, and hammers earned through combos or purchased. Events such as Sky Race (PvP-style), tournaments, quests, team alliances, streak rewards, card collections, and minigames drive engagement. With over 12,400 levels by late 2025 (expanding biweekly with 100+ new ones every two weeks), progression is endless—no true endgame—demanding thousands of hours, especially for F2P players facing aggressive difficulty scaling and near-miss designs that push impulse buys for extra moves or boosters.Analytic Dreamz breaks down its extraordinary success: 300M–370M+ downloads, lifetime revenue surpassing $5–7B (with $1.3–1.4B in 2024–2025 alone, topping casual/puzzle charts), and ~55M MAU. Dream Games, now valued at ~$5B following a major 2025 CVC Capital Partners investment (providing liquidity to early VCs while founders retain majority control), dominates match-3 IAP revenue share through masterful user acquisition (heavy Apple Search Ads, creative pin-pull campaigns) and retention via live ops—no ads interrupting play.Praised for smooth UX, polish, and uninterrupted experience (4.7/5 store ratings), it faces criticism for paywalls, "rigged" difficulty spikes, Super Hard levels, and misleading ads. A 2024 gambling lawsuit in Washington alleged coin purchases resemble gambling, though no major resolutions noted. Sequel Royal Kingdom (2024) adds PvP and ranked play, already generating hundreds of millions.Join Analytic Dreamz to unpack how Royal Match redefined mobile puzzle dominance through relentless monetization, UA strategy, and live service mastery, turning Dream Games into a top global publisher. Support this podcast at — https://redcircle.com/analytic-dreamz-notorious-mass-effect/donationsPrivacy & Opt-Out: https://redcircle.com/privacy
What is the single most powerful indicator that a founder will succeed? According to Ben Savage, it isn't just a great product or a massive market—it's the "Compete Test". When a seasoned investor looks at a founder and realizes, “That's not somebody I want to compete with,” they know they've found a winner.In this episode of Demo Day, we sit down with Ben Savage, Partner at Clocktower Technology Ventures, to demystify the internal frameworks used by top VCs to evaluate talent and risk. With over 13 years at Clocktower, Ben shares his deep expertise in the "Foundational Economy"—investing in FinTech, energy, and industrials.Key TakeawaysThe "Unbeatable" Founder: Why the best indicator of success is being a person that others are afraid to go up against in the market.The 4-Part Investment Framework: How Clocktower evaluates every deal based on Founder Quality, Narrative Quality, Fit, and Value.Investor vs. Operator: Why "making the donuts" is fundamentally different from coaching from the sidelines, and why you must choose a spike.The "I" vs. "We" Red Flag: How small shifts in vocabulary reveal a founder's true ability to build a world-class team and culture.Navigating the AI Disruption: Why founders today must either lead with an AI-centric strategy or risk being disrupted at an accelerating pace.The Power of Simplicity: Why the best investment decisions often come from cutting through complexity to the "dumb" or obvious version of a story.Ben also opens up about the "lonely journey" of entrepreneurship and why radical vulnerability is a superpower for building long-term partnerships.
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