Podcasts about Airtable

Gokul Rajaram is one of the greatest operators turned investors of the last 2 decades. He is trusted as the go to advisor for the greatest founders in the world. Today he serves as a Board Director at three public companies: Coinbase, Pinterest and The Trade Desk. Prior to Marathon (his firm), Gokul served on the executive team at DoorDash and Block. Before Block, he served as Product Director of Ads at Facebook. Earlier in his career, Gokul served as a Product Management Director for Google AdSense. Gokul is also a prolific angel investor, having invested in 700+ companies, including Airtable, Figma, Groq, Runway, Supabase, and Vercel.  AGENDA: 03:53 — Investing Lessons from Google, Doordash and Facebook 05:32 — Why Mark Zuckerberg is the Greatest Distribution Genius Alive 07:23 — Why Every Company Today Needs to be Multi-Product 09:16 — Negative Gross Margins: Are the Best Companies Actually Built on "Shit" Economics? 10:50 — The SaaS Apocalypse: Is the Entire Sector Going to Zero? 12:15 — The 8 Moats of Enduring Software Companies: How to Analyse Companies 14:50 — Why Brand is No Longer a Strong Moat (And What Replaced It) 16:13 — Salesforce vs. Atlassian: Which Systems of Record are Dying? 18:13 — Outcome-Based Pricing: Is This the Total Death of Seat Pricing? 20:16 — The Bolt-On AI Trap: Why Rebuilding Your Entire UX is Non-Negotiable 23:44 — Are the Outcome Sizes of Vertical SaaS Large Enough for VC Today? 28:16 — The Zombie Cohort: What Happens to Private Companies with High Valuations? 32:44 — Is "King Making" Complete Bullshit? 34:21 — Durability Over Margins: What Really Matters in a 100x Growth World 35:36 — The Non-Consumption Miracle: Why Granola and Gamma are Crushing It 38:50 — The PayPal Rule: Can You Raise Prices 5 Times in 3 Years? 42:47 — My Biggest Miss: How I Misread the Shopify Billion-Dollar Mark 45:18 — The Courage to Bet: Why Instacart is the Best VC Deal Ever 46:33 — Seed vs. Growth Pricing: When Does Price Actually Destroy Returns? 50:53 — Does "Proprietary Founder Access" Even Exist? 54:33 — Double Down or Diversify? The Truth About Fund Reserves 59:44 — The Vanta Anti-Portfolio: A Mistake I'll Never Forget 01:01:21 — When to Sell: The "Sell a Third, Hold a Third, Trade a Third" Rule 01:04:12 — Why Remote Early-Stage Companies are Dying 01:07:33 — Why Mid-Level Partners are Fleeing Mega Funds 01:09:47 — The Best CEO Superpowers: Larry, Mark, Jack, and Tony 01:12:33 — The Next 10 Years: Why Dropouts are "AI Maxing" the World    

In this episode of Research Like a Pro, Diana and Nicole discuss the all-new Version 4.2 (2026) of the Research Like a Pro with DNA Airtable Research Log. The updates are designed to streamline the genetic genealogy workflow, making DNA research more flexible and reducing duplicate data entry.  Diana details the biggest change: the "Test-taker" and "DNA Match" fields in the DNA Match Details table are renamed to "Person 1 (P1)" and "Person 2 (P2)." This simple but powerful update allows users to record the shared DNA between any two people, including matches and their shared matches, which is particularly useful for analyzing data from Ancestry Pro Shared Matches, MyHeritage, and FTDNA. Nicole highlights that the family tree URLs, kit administrator fields, and match usernames are now centralized exclusively in the People table. This makes them lookup fields in other tables, meaning users enter the information only once and save significant time. Furthermore, Nicole discusses the Timeline table enhancement, where a new formula automatically converts varied date entries (e.g., "March 1857") into a standardized sortable format. Diana confirms that core tables like Locations, FANs, and Segments remain the same, preserving existing workflows. Listeners will learn how to make the most of the new base, with tips for migrating data from older versions. Diana concludes that the changes are designed for maximum efficiency, helping researchers focus more on analysis and discovery. This summary was generated by Google Gemini. Links RLP with DNA Research Log 4.2 (2026) Airtable Template Updates - https://familylocket.com/rlp-with-dna-research-log-4-2-2026-airtable-template-updates/ RLP with DNA Airtable Template 2026 – Updates and Change Log (https://docs.google.com/document/d/1UYWptPpc02N5S8Rn8muSoGXvE2SfCkcl_DehG9TVRvQ/edit?usp=sharing Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro Institute Courses including Merging and Separating Identities - https://familylocket.com/product-category/institute-course/ Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

Kenny Harper interviews Brenda Canaan about reducing tax-season chaos by scheduling tax prep and controlling workload instead of accepting documents anytime. Cannon explains how her firm previously promised 2–3 week turnarounds without knowing capacity, leading to bottlenecks like 105 clients submitting documents on March 15, and how the pandemic highlighted the lack of workload control. Inspired by a podcast, she implemented a scheduling system using Calendly, Make, and Airtable, then co-developed the Schedule E software to better track client scheduling, automate reminders, and support flexible calendars by preparer or client type. She emphasizes proactive client communication about extensions, using tax projections when needed, improving efficiency, reducing status checks and errors, and using scheduling for capacity planning, client fit, and better work-life balance. 00:00 Why Scheduling Matters 01:12 Meet Brenda Cannon 03:26 From Chaos to Control 05:11 Building Schedule E 06:34 Client Buy In 08:42 Rolling It Out 15:22 Handling Extensions 15:48 Community and Setup 22:28 Capacity and Team 24:51 Lessons and Wrap Up

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

In this episode, we explore the intersection of AI and Airtable with Rob Weidner. We discuss the current state of AI, its potential impact on productivity, and how Airtable is uniquely positioned to lead the charge. Rob also shares his thoughts on the pros and cons of building on Airtable versus standalone platforms and showcases his work with HyperAgent, a cutting-edge AI tool. Tune in to learn more about the future of work and how AI is changing the game!

Get the guide to create AI Agents: https://clickhubspot.com/wvh Ep. 403 Can you build a team of AI assistants—like a competitive researcher, content strategist, and world-class data analyst—all inside your email inbox? Kieran dives into how AI specialists can supercharge your productivity right from your inbox. Learn more on setting up inbox-native AI agents, why bespoke email-based delegation beats chatbots, and the game-changing workflows for competitive analysis and content repurposing—all done through your email. Mentions Mail Manus https://manus.im/features/mail Airtable https://www.airtable.com/  OpenAI https://openai.com/ Claude https://claude.ai/ Gemini https://gemini.google.com/ Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by Hubspot Media // Produced by Darren Clarke.

In this episode, we dive into Airtable's recent outage and the introduction of HyperAgent. We also explore a script that helps manage naming conventions in Airtable, making it easier to keep track of linked records and lookups. Tune in to learn more about the differences between SuperAgent and HyperAgent, and how HyperAgent is more closely tied to Airtable.

You've landed a foothold in a big company, delivered a great project, the client loved it, so why are you still stuck in the same corner six months later winning the same small deals? In this episode, I break down why most consultants stay trapped in one department and how to turn a single project into an enterprise-wide engagement. I share how one Airtable consultant turned a $20,000 clinical trial tracking project at a top-three pharmaceutical company into a $200,000 transformation across three countries, all by making one strategic shift in how he treated his internal champion. If you've got a foothold in a big company and you're watching other consultants land the deals you should be winning, this is your playbook.Resources and LinksApply for a Multiplier CallPrevious episode: 666 - The partner trapCheck out more episodes of the Paul Higgins PodcastSubscribe to our YouTube channel: @PaulHigginsMentoringJoin our newsletterSuggested resources

Ever wonder what actually happens after someone makes a big backend decision?In this episode, I'm giving you a real update on two announcements I made last month:• Hiring a professional Notion strategist to build my marketing team dashboard• Bringing Chelsea on as my fractional CMO for 2026Spoiler: I am not abandoning Airtable. But I did need a better way to coordinate a growing team without becoming the bottleneck.I'm sharing what's working, what surprised me, and how it actually feels to wake up and not have marketing on my to-do list — while everything still moves forward.If you love behind-the-scenes updates, this one's for you.Also Mentioned:Systems in Session (Now Booking for Q2)Email Like You Mean It (next live sprint: April 6-10)Ania my Notion ExpertChelsea my Fractional CMO

Get ready to take your Airtable skills to the next level with expert Martin. In this episode, we dive into the world of Airtable webhooks and explore how to build a schema change log, manage cursors, and handle token expiration. Martin shares his experience and expertise on the benefits and challenges of using webhooks, and we discuss some of the limitations of Airtable webhooks. Whether you're an Airtable enthusiast or a developer, this episode is perfect for anyone looking to master Airtable webhooks.

Get ready to take your Airtable skills to the next level! In this episode, we dive into the world of metadata management with expert Ali. Learn how to create a custom script to track field and table changes, and discover tips for optimizing your base for the upcoming Airtable Hackathon. Whether you're a seasoned pro or just starting out, this episode is packed with valuable insights to help you master Airtable metadata.

Get ready to explore the latest and greatest in the Airtable universe! In this episode, we're talking about Super Agent, a new product that's got everyone buzzing. We'll dive into its features, limitations, and potential use cases. Plus, we'll showcase some amazing community creations, like a custom interface extension for tracking the Winter Olympics. Join us for a conversation that's all about innovation, creativity, and getting the most out of Airtable.

Want to learn how to automate repetitive tasks in Airtable? In this episode, Kamille shares a demo of a habit tracker and provides tips and tricks for debugging complex formulas. Learn how to use Airtable to streamline your workflow and increase productivity. From setting up a habit tracker to creating a system for repetitive tasks, this episode covers it all.

Get ready to revolutionize your Airtable workflow with AI-powered interfaces. In this episode, we chat with Aly Elosa about the possibilities of generating custom interfaces using Airtable's AI tools. Learn how to harness the power of AI to create tailored interfaces that meet your specific needs. Tune in to discover the benefits and limitations of this exciting feature.

Welcome back to BuiltOnAir! After a six-month hiatus, we're excited to introduce our new format and catch up on what we've been up to. In this episode, we'll discuss some of the latest updates and features in Airtable, including the ability to display the show name instead of the primary field, labs for detail pages, and the new ChatGPT add-on. We'll also dive into the recent Airtable community-led hackathon and talk about some of the amazing projects that were submitted. Tune in to hear about the latest and greatest in the Airtable community.

Please follow us on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook ⁠⁠⁠⁠⁠⁠⁠! In this episode, Kimberly and Tommaso share their experiences after living in Italy for almost a month. They discuss the daily adjustments, from understanding local customs to enjoying Italian cuisine. Key Points: The Italian Tabacchi: More Than Meets the Eye: Kimberly and Tommaso explain how a “tabacchi” in Italy serves multiple purposes beyond selling cigarettes. It is a place to purchase a “Marco da Bolo,” a stamp needed for immigration applications. This discovery highlights the unique role of local establishments in daily Italian life. The Rhythm of Reposo: Kimberly and Tommaso describe the challenge of adapting to store closing times for “riposo” or “pausa,” the Italian equivalent of a siesta. Store hours vary, making it tricky to plan errands. They joke about needing a spreadsheet or an “Airtable database” to keep track of business hours. These closures offer a peaceful atmosphere, especially during midday, creating a quiet charm in the streets. Grocery Shopping Adventures: A humorous incident occurs when Kimberly attempts to bring a two-wheel shopping cart into a grocery store. She learns that these carts are not allowed inside due to unspoken rules. Kimberly ‘s New York City instincts made her hesitant to leave her cart unattended. The grocery manager's reaction to her concern about theft provides a moment of cultural contrast. A Culinary Awakening: Kimberly and express their delight in the quality and accessibility of Italian food. Small “alimentaries” (local markets) specialize in different products, from prosciutto to Parmigiano. Even simple roasted vegetables become a culinary revelation due to the fresh ingredients and olive oil. They highlight the artistic display of food in shops, which makes shopping a visually appealing experience. The Echoes of History: Living in a village with roots dating back to the Bronze Age give Kimberly and Tommaso a deeper appreciation for history. The Venetian architecture in their village adds to its charm. Tommaso Il Favoloso reflects on his lifelong dream of living in Europe and the magical feeling of making Italy his home. Ciao!

Bernie thinkis we should try a community project using Obsidian. It's starting with a small project between Roger Overall, Brigit Kolen in The Netherlands, and Tim Ereneta in California. Bernie just heard something interesting in the podverse and by Adam Curry, the podfather. He is using Obsidian.Can you imagine?Here is what Adam had to say inCasting 2.0 for February 13th, 2026, episode 250, Dopaminergic:"Obsidian's my jam. I live in Obsidian. A lot of people use Obsidian. I use it as an outline. You can use it in many different ways, and it's completely scriptable. So an example: every day it has a new folder for the year, month, day. I use a markdown widget on the browser. So if I see an article that I want to save, then I just hit that little widget and it will save the title and the URL. And on desktop, it'll actually save a markdown version of the page. The whole thing is based on markdown files.And even if I get something from Gemini, I have a prompt that says put it into an Obsidian template. It does tags and all the stuff I need to just have a database, a knowledge base of stuff, and I can search it and I can organize it. And so when it comes to show day, regardless of what show it is, I'll check on the tags, as I mark all the different shows I do with tags. And then I drag it into a show folder with topics. And then I have a script which will export it to OPML and I can import that right into the Freedom Controller. It really is nice. But you can also, if you want, turn it into mind mapping. I don't use that. I just use it as an outliner, knowledge-based storage system, and it syncs between all my devices. I live in that. I just absolutely write down a note, boom, got it, because you can find it. You can really find stuff. Yeah, I probably need to look at this because Alex Gates turned me on to it. Ever since I got Obsidian, like, oh man, I love this. This thing is awesome. It really is. My whole life is in it. You can put code in it. Code blocks. Yeah, it's Markdown. So, yeah. Hello. Yeah. Hello. Pretty cool."So that's Adam Curry talking about Obsidian, my favorite knowledge management system.With Roger, I'm hoping to connect a vault in Obsidian between Roger, Brigit Kolen, a creative media writer in the Netherlands, and myself as we talk about authentic storytelling.Another partner, and it would be Tim Ereneta in Berkeley, may row in.  For you then, Simon, if you think you'd be interested in connecting up a vault that would generate OPML, that would be handy.I think I can figure it out based on the community plugins that are inside the Obsidian community, but who knows?This is interesting.And the other thing I want to do is use Airtable iframes inside of Obsidian.And that should be as dead simple as buying the right plan with Airtable and then injecting, inserting the iframe.Different plans allow different kinds of dynamic insertion. Some are just a view. Some are allowing in and out.But those are two things: Obsidian in its native form to generate OPML. And Obsidian with in and out Airtable.This is interesting to me because I know it moves the ball down the pitch of authentic storytelling.Become a supporter of this podcast: https://www.spreaker.com/podcast/topgold-audio-clips--2663090/support.

This episode focuses on the exciting custom clustering feature now available in Ancestry's Pro Tools. Diana introduces the tool, explaining how it allows for the strategic targeting of specific ancestral lines, offering more flexibility than the original clustering tool. She describes Ancestry's process, which looks for matches sharing 65 cM to 1,300 cM with the user, and then finds those matches that also share at least 20 cM with each other. Nicole discusses the key benefits of using custom clusters: they help you hone in on specific ancestral lines, quickly identify groups descending from common ancestors, and work more efficiently at distant generations. Before creating a cluster, Diana reviews critical points from Ancestry, noting that clusters expire after 30 days unless saved to a group and you are limited to 25 clusters in your history. Nicole shares Ancestry's recommended centimorgan ranges based on the generational distance of the ancestor you are researching. She then walks through the four steps for creating a cluster: choosing a target match, selecting four additional "sidekick" matches, setting the centimorgan range, and generating the cluster. Diana provides a real-world example from her Cline family research, detailing how she used a custom cluster with a 20-50 cM range to test a hypothesis about the parentage of John C. Cline. The results successfully separated her matches into distinct sub-clusters that provide additional evidence for her research. Listeners learn practical tips for success, including saving clusters strategically, trying different target and sidekick match combinations, and systematically tracking all experiments in a research log like Airtable. This powerful strategy helps you apply a new approach to breaking down your DNA research brick walls. This summary was generated by Google Gemini. Links How to Use Ancestry DNA Custom Clusters in Your Research – with Video - https://familylocket.com/how-to-use-ancestry-dna-custom-clusters-in-your-research-with-video/ Ancestry Support Article - Matches by Cluster https://support.ancestry.com/s/article/Matches-by-Cluster?language=en_US Ancestry Support Article - Custom Match Clusters https://support.ancestry.com/s/article/Custom-Match-Clusters?language=en_US  Sponsor – Newspapers.com For listeners of this podcast, Newspapers.com is offering new subscribers 20% off a Publisher Extra subscription so you can start exploring today. Just use the code "FamilyLocket" at checkout.  Research Like a Pro Resources Airtable Universe - Nicole's Airtable Templates - https://www.airtable.com/universe/creator/usrsBSDhwHyLNnP4O/nicole-dyer Airtable Research Logs Quick Reference - by Nicole Dyer - https://familylocket.com/product-tag/airtable/ Research Like a Pro: A Genealogist's Guide book by Diana Elder with Nicole Dyer on Amazon.com - https://amzn.to/2x0ku3d 14-Day Research Like a Pro Challenge Workbook - digital - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-digital-only/ and spiral bound - https://familylocket.com/product/14-day-research-like-a-pro-challenge-workbook-spiral-bound/ Research Like a Pro Webinar Series - monthly case study webinars including documentary evidence and many with DNA evidence - https://familylocket.com/product-category/webinars/ Research Like a Pro eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-e-course/ RLP Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-study-group/ Research Like a Pro Institute Courses - https://familylocket.com/product-category/institute-course/ Research Like a Pro with DNA Resources Research Like a Pro with DNA: A Genealogist's Guide to Finding and Confirming Ancestors with DNA Evidence book by Diana Elder, Nicole Dyer, and Robin Wirthlin - https://amzn.to/3gn0hKx Research Like a Pro with DNA eCourse - independent study course -  https://familylocket.com/product/research-like-a-pro-with-dna-ecourse/ RLP with DNA Study Group - upcoming group and email notification list - https://familylocket.com/services/research-like-a-pro-with-dna-study-group/ Thank you Thanks for listening! We hope that you will share your thoughts about our podcast and help us out by doing the following: Write a review on iTunes or Apple Podcasts. If you leave a review, we will read it on the podcast and answer any questions that you bring up in your review. Thank you! Leave a comment in the comment or question in the comment section below. Share the episode on Twitter, Facebook, or Pinterest. Subscribe on iTunes or your favorite podcast app. Sign up for our newsletter to receive notifications of new episodes - https://familylocket.com/sign-up/ Check out this list of genealogy podcasts from Feedspot: Best Genealogy Podcasts - https://blog.feedspot.com/genealogy_podcasts/

In this episode recorded at the Presales Collective Leadership Next Summit in November of 2025, Jack Cochran sits down with Gretchen Fitzgibbons, Senior Manager of Strategic Solutions Consulting at Airtable, to discuss what it means to be a courageous leader in presales. They explore how to make difficult decisions under pressure, navigate organizational politics with integrity, and build the support systems that enable consistent leadership. Gretchen shares powerful stories from her two decades of experience advising Fortune 500 customers and leading presales teams, including standing up for a team member being unfairly assessed and creating win-win solutions in challenging situations. Follow Us Connect with Jack Cochran: https://www.linkedin.com/in/jackcochran/ Connect with Gretchen Fitzgibbons: https://www.linkedin.com/in/gretchenfitzgibbons/ Links and Resources Mentioned Join Presales Collective Slack: https://www.presalescollective.com/slack Sol/Con 2026: https://www.presalescollective.com/solcon-2026  Book mentioned: Think Again by Adam Grant: https://adamgrant.net/book/think-again/  Book mentioned: Thinking, Fast and Slow by Daniel Kahneman: https://www.goodreads.com/book/show/11468377-thinking-fast-and-slow  Key Topics Covered Redefining Courage and Leadership Making Tough Calls: Standing Up for Team Members Focusing on Your Team rather than on Yourself How to Prepare for a Leadership Role It's OK to be Wrong Developing Your Leadership Skills Grounding Principles for Leadership Timestamps 00:00 Welcome and Introduction 02:14 Defining Courage and Leadership in Presales 05:15 Making Tough Calls: A Story of Standing Up for What's Right 11:20 Focusing on Your Team rather than on Yourself 22:07 How to Prepare for a Leadership Role 27:40 It's OK to be Wrong 30:30 Developing Leadership Skills 37:42 Final Takeaways and Grounding Principles

This is a story of growth through creativity, experimentation, and using technology to stay lean.Carlo Pandian (LinkedIn) is the founder of Slow Travel Italia. Four years ago he started with a single wine tasting in Verona, and today runs 160 experiences across 12 Italian cities, serving 15,000 guests a year with a very small team.In this episode, he talks to TP host Mitch Bach about exactly how he did it: experimenting with neglected time slots (like 6pm) that competitors ignore, launching five tours at once instead of one to multiply his chances of finding a niche, using Airtable and automations to eliminate manual booking assignments and personalize communication at scale, and treating OTAs as a launchpad rather than a long-term home. Carlo shares how he identifies gaps in crowded markets by studying what's missing—not just in Italy but in places like Japan—and why he pulled out of Milan when the math didn't work. He explains his "requirements manifesto" for vetting partners, how he coaches food producers on storytelling for international audiences, and why the biggest trend he's seeing is travelers willing to spend half a day outside the city for a single product done deeply—visiting the olive grove, watching mozzarella pulled from boiling water, understanding one thing fully rather than tasting nine things superficially.As always, more info and takeaways on tourpreneur.com.

Today we sit down with John Lack, Global Head of Sales Development at Airtable, to demystify the world of software sales as a profession. John breaks down the immense rewards of the industry—from earning six figures right out of college as a successful BDR to mastering the "autonomy, mastery, and purpose" of high-level tech sales. We explore why the BDR role is the most critical time in a career for building foundational grit and why 90% of AE struggles stem from poor front-end pipeline generation. John also shares his own unconventional journey, starting as a BDR at age 30 and scaling teams through massive growth phases at Oracle and MongoDB.

Zevi Arnovitz is a product manager at Meta with no technical background who has figured out how to build and ship real products using AI. His engineering team at Meta asks him to teach them how he does what he does. In this episode, Zevi breaks down his complete AI workflow that allows non-technical people to build sophisticated products with Cursor.We discuss:1. The complete AI workflow that lets non-technical people build real products in Cursor2. How to use multiple AI models for different tasks (Claude for planning, Gemini for UI)3. Using slash commands to automate prompts4. Zevi's “peer review” technique, which uses different AI models to review each other's code5. Why this might be the best time to be a junior in tech, despite the challenging job market6. How Zevi used AI to prepare for his Meta PM interviews—Brought to you by:10Web—Vibe coding platform as an APIDX—The developer intelligence platform designed by leading researchersFramer—Build better websites faster—Episode transcript: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Archive of all Lenny's Podcast transcripts:https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Zevi Arnovitz• X: https://x.com/ArnovitzZevi• LinkedIn: https://www.linkedin.com/in/zev-arnovitz• Website: https://zeviarnovitz.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Zevi Arnovitz(04:48) Zevi's background and journey into AI(07:41) Overview of Zevi's AI workflow(14:41) Screenshare: Exploring Zevi's workflow in detail(17:18) Building a feature live: StudyMate app(30:52) Executing the plan with Cursor(38:32) Using multiple AI models for code review(40:40) Personifying AI models(43:37) Peer review process(45:40) The importance of postmortems(51:05) Integrating AI in large companies(53:42) How AI has impacted the PM role(57:02) How to improve AI outputs(58:15) AI-assisted job interviews(01:02:57) Failure corner(01:06:20) Lightning round and final thoughts—Referenced:• Becoming a super IC: Lessons from 12 years as a PM individual contributor | Tal Raviv (Product Lead at Riverside): https://www.lennysnewsletter.com/p/the-super-ic-pm-tal-raviv• Wix: https://www.wix.com• Building AI Apps: From Idea to Viral in 30 Days: https://www.youtube.com/watch?v=j2w4y7pDi8w• Riley Brown on YouTube: https://www.youtube.com/channel/UCMcoud_ZW7cfxeIugBflSBw• Greg Isenberg on YouTube: https://www.youtube.com/@GregIsenberg• Bolt: https://bolt.new• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Lovable: https://lovable.dev• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• StudyMate: https://studymate.live• Dibur2text: https://dibur2text.app• Claude: https://claude.ai• Everyone should be using Claude Code more: https://www.lennysnewsletter.com/p/everyone-should-be-using-claude-code• Bun: https://bun.com• Zustand: https://zustand.docs.pmnd.rs/getting-started/introduction• Cursor: https://cursor.com• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Wispr Flow: https://wisprflow.ai• Linear: https://linear.app• Linear's secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu• Cursor Composer: https://cursor.com/blog/composer• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Base44: https://base44.com• Solo founder, $80M exit, 6 months: The Base44 bootstrapped startup success story | Maor Shlomo: https://www.lennysnewsletter.com/p/the-base44-bootstrapped-startup-success-story-maor-shlomo• v0: https://v0.app• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder & CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Cursor Browser mode: https://cursor.com/docs/agent/browser• Google Antigravity: https://antigravity.google• Grok: https://grok.com• Zapier: https://zapier.com• Airtable: https://www.airtable.com• Build Your Personal PM Productivity System & AI Copilot: https://maven.com/tal-raviv/product-manager-productivity-system• The definitive guide to mastering analytical thinking interviews: https://www.lennysnewsletter.com/p/the-definitive-guide-to-mastering-f81• AI tools are overdelivering: results from our large-scale AI productivity survey: https://www.lennysnewsletter.com/p/ai-tools-are-overdelivering-results-c08• Yaara Asaf on LinkedIn: https://www.linkedin.com/in/yaarasaf• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Loom: https://www.loom.com• Cap: https://cap.so• Supercut: https://supercut.ai...References continued at: https://www.lennysnewsletter.com/p/the-non-technical-pms-guide-to-building-with-cursor—Recommended books:• The Fountainhead: https://www.amazon.com/Fountainhead-Ayn-Rand/dp/0451191153• Shoe Dog: A Memoir by the Creator of Nike: https://www.amazon.com/Shoe-Dog-Memoir-Creator-Nike/dp/1501135910• Mindset: The New Psychology of Success: https://www.amazon.com/Mindset-Psychology-Carol-S-Dweck/dp/0345472322—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Produced by Foundersuite (for startups: www.foundersuite.com) and Fundingstack (for emerging manager VCs: www.fundingstack.com), "How I Raised It" goes behind the scenes with startup founders and investors who have raised capital. This episode is with with Sam Lessin of Slow Ventures, a a generalist early stage venture capital firm based in San Francisco, Boston, and New York that has invested ~$1B in startups building in the security, fintech, buyouts/rollups, SaaS, crypto, consumer, healthcare, and the creator economy. Slow's portfolio includes companies like Airtable, Brightside, Gusto, Metropolis, OpenPhone, PillPack, Ro, Solana, Teamshares and more. In this episode we discuss what Slow invests in across its 5 funds, why Slow is a "generalist fund," how Sam and Kevin raised capital for their first fund from ex-Facebook employees, why Slow decided to launch a dedicated fund focused on the creator economy, his advice for emerging VC managers and much more. How I Raised It is produced by Foundersuite, makers of software to raise capital and manage investor relations. Foundersuite's customers have raised over $21 Billion since 2016. If you are a startup, create a free account at www.foundersuite.com. If you are a VC, venture studio or investment banker, check out our new platform, www.fundingstack.com

In this episode, Don McGray, product marketing leader and Head of Growth PMM at Vimeo (formerly Dropbox and Airtable), shares how to separate identity from performance without dialing down ambition. From being told his launch plan was “C-plus work” to navigating a surprise layoff, Don shares the inner-game shifts that helped him rebuild trust, make cleaner calls, and keep moving in high-stakes environments.Don gets specific about executive alignment (and the invisible pre-meeting “backchannel”), the moment he realized he was in the wrong role—and said it out loud—and why cultivating distance from work (and toward real hobbies) made him a steadier operator when pressure spiked.In this conversation, you'll learn:How to detach self-worth from outcomes so feedback, layoffs, and big swings don't break your momentum.How to earn executive buy-in before “the meeting” and turn harsh input into an actionable A-grade plan.How to diagnose a role misfit early, have the hard conversation, and land where your strengths actually compound.Things to listen for:(00:00) Intro(02:10) Don's early career(04:37) High stakes and career growth at Dropbox(09:42) Thank you to our sponsor, Navattic(13:50) Lessons from Airtable: handling tough feedback(18:31) Navigating executive expectations(25:04) Facing imposter syndrome(25:25) Struggles in a new role(28:19) The importance of vulnerability(30:10) Navigating career changes(38:32) Handling layoffs and job insecurity(42:58) Balancing work and personal lifeA huge thanks to this episode's sponsor:Navattic: Interactive Product Demo Software - https://navattic.com/value Resources:Connect with Don: LinkedIn: https://www.linkedin.com/in/donmcgray/ Connect with Andrew:LinkedIn: https://www.linkedin.com/in/andrewcapland/ Substack: https://media.deliveringvalue.coHire Andrew as your coach: https://deliveringvalue.co/coachingJoin Growth OS: https://deliveringvalue.co/growth-operating-system

Dans cet épisode, je vous raconte mon expérience de “vibe coding”, cette nouvelle façon de développer des outils sans écrire une seule ligne de code grâce à l'IA. Spoiler : c'est incroyable.Tout est parti d'un besoin très conret : améliorer les outils que j'utilise au quotidien pour produire et organiser ce podcast. Jusqu'ici, Notion faisait bien le travail, mais avec le temps, le système est devenu plus lourd, plus complexe et surtout limité. Je me suis alors tourné vers Airtable pour structurer un véritable tableau de bord dédié à la gestion “business” (suivi commercial, engagements, controle de facturation, etc.). J'ai apprécié la richesse des interfaces visuelles, les automatisations et l'assistant IA intégré, que j'ai complété avec ChatGPT et Gemini qui m'ont aidé à réfléchir à la logique globale et à l'architecture des bases de données.Mais la vraie révélation a été Lovable. Cette start-up suédoise permet de créer une véritable application web simplement en décrivant ce que l'on veut. En quelques jours, j'ai conçu un outil que j'ai baptisé PodTracker pour la planification des épisodes, la gestion des interviews et des messages de partenariats à travers un calendrier partagé; avec même un éditeur de texte intégré, le tout à travers une interface élégante et même une version mobile. Pour tout cela, je n'ai pas écrit une seule ligne de code. J'ai travaillé uniquement avec le chatbot inclus qui propose, teste, corrige et améliore en continu.Grisant et addictifBien sûr, il y a des limites, comme des interrogations autour de la sécurité du code généré, ou encore une dépendance à la plateforme pour l'hébergement et l'exportation de l'application. Mais le constat est clair : ces outils transforment profondément la manière de concevoir le développement logiciel. L'expérience est à la fois grisante et addictive.Au final, ce que je retiens surtout, c'est ce sentiment très fort d'être réellement “augmenté” par l'intelligence artificielle. J'ai pu créer des outils sur mesure dont j'avais besoin depuis longtemps, mais que j'étais incapable de réaliser seul auparavant. Pouvoir transformer une idée en application fonctionnelle, en quelques semaines à peine, sans compétences professionnelles réelles, est une incroyable révolution.Quant au métier de développeur, il est certain que celui-ci va évoluer très vite, en étant moins centré sur l'écriture de code que sur l'analyse des besoins, le pilotage de l'IA et la vérification des résultats. Le vibe coding est certainement l'avenir du code, tout simplement.-----------♥️ Soutien : https://mondenumerique.info/don

Bilan d'une année 2025 hors normes pour la tech, projections pour 2026 et premières tendances du CES de Las Vegas : Monde Numérique ouvre l'année avec un épisode dense, analytique et résolument tourné vers l'avenir.

Exploring the Future: Ecommerce Predictions for 2026 As we get ready for another rollercoaster in 2026, ecommerce landscape is poised for continued transformation. In the last podcast of the year, James and Paul explore the trends and innovations that they think are set to define the industry. Sponsored by Shopify, this episode offers an interesting analysis of what the future holds for ecommerce businesses.Summary:2025 has been a whirlwind, and as we look ahead, the question on everyone's mind is: what will 2026 bring? James and Paul put their necks on the block, predicting the future & focusing on key areas such as the evolution of the point of purchase, the expanding role of SEO and agentic commerce, and the strategic use of technology.Key predictions:Point of Purchase Evolution: The traditional ecommerce website is still critical but where people buy is evolving. James predicts a shift towards instant checkouts and purchases made directly from ads, thanks to innovations from companies like PayPal and Stripe. This evolution is expected to increase the percentage of sales made outside traditional platforms.SEO and agentic optimisation: As AI continues to advance, the role of SEO is expanding. Paul highlights the need for businesses to adapt to new optimisation techniques that blend traditional SEO with agentic engine optimisation. This shift is expected to reignite the SEO industry, offering new opportunities for growth and innovation.Tactical middleware: The use of tactical middleware is set to become a game-changer for businesses. By leveraging third-party apps like Airtable and SuperBase, companies can solve specific challenges without the need for complex integrations. This approach simplifies development and reduces costs, making it an attractive option for many.Inside Commerce's predictions for 2026 paint a picture of an industry in flux, driven by technological advancements and changing consumer behaviours. As businesses prepare for 2026, staying informed and adaptable will be key to success.

Ever feel like you're constantly creating content for strangers on social media? If so, are you doing it while ignoring the people who've already paid you for your products or services? Yeah, we need to talk about that.In this final episode of 2025, my friend Colie James joins me to call out the exhausting cycle of chasing new leads when the people most likely to say yes are already in your world—your former clients, your email list, even those leads who didn't book the first time. We're breaking down why marketing to your actual audience beats talking to strangers in the void, how to stop making assumptions about who will buy from you, and why your first stop for any cash infusion should never be Instagram._____________________________________________  EPISODE 176.Read the show notes and view the full transcript here: https://erinollila.com/selling-to-the-people-who-are-already-in-your-audience-with-colie-james/______________________________________________Learn all about our guest expert, Colie JamesColie James is a Disney-loving Client Experience Systems Strategist and the host of the Business-First Creatives podcast. Her heart pumps in helping photographers & creative service providers automate their processes, reclaim their time and get back to living! With 13+ years in the creative space, Colie believes every creative deserves to build a business that is sustainable and profitable, and no one should quit their 9 to 5 only to work 24/7 [in their business].The truth—automated systems can save us all from being overworked and overwhelmed.When Colie isn't building killer workflows and automations, you can find her spending some much needed time with her husband, James, daughter Chloe, or [you guessed it] at Disneyland. When you're done listening to this episode of the podcast with Colie, click through the archives to hear an episode on customer experience and another on Airtable content hubs (or just click those links!) Oh, and she interviewed me on my podcast about my business trajectory, too!https://erinollila.com/why-is-customer-experience-important-with-colie-james/https://erinollila.com/erin-ollilas-business-trajectory/https://erinollila.com/creating-an-airtable-content-marketing-hub/And then—and only then!—I suggest you head over to HER podcast, Business-First Creatives, to hear even more awesome content from this great guest expert.Here's the info on your host, Erin OllilaErin Ollila believes in the power of words and how a message can inform – and even transform – its intended audience. She graduated from Fairfield University with an M.F.A. in Creative Writing, and went on to co-found Spry, an award-winning online literary journal.When Erin's not helping her clients understand their website data or improve their website copy, you can catch her hosting the Talk Copy to Me podcast and guesting on shows such as Profit is a Choice, Mindful Marketing, The Power in Purpose, and Business-First Creatives.Stay in touch with Erin Ollila, SEO website copywriter:• Learn more about my VIP intensive options or just book a strategy session to get started right away• Visit Erin's website to learn more about her business, services, and products

Immad Akhund is the Co-founder & CEO at Mercury - one of the most widely used business banking platforms globally. He is also an active investor in Silicon Valley - as an active investor in 350 startups at their earliest stages including Airtable, Substack, and Rappi. In this episode we talk about the three photographs that define Immad's life so far, the fateful weekend of the Silicon Valley Bank failure, and his leadership lessons learnt in a time of crisis.Building a purpose driven company? Read more about Giant Ventures at www.Giant.vc.Music credits: Bubble King written and produced by Cameron McLain and Stevan Cablayan aka Vector_XING. Please note: The content of this podcast is for informational and entertainment purposes only. It should not be considered financial, legal, or investment advice. Always consult a licensed professional before making any investment decisions.

Immad Akhund is the Co-founder and CEO at Mercury - one of the most widely used business banking platforms globally. He is also an active investor in Silicon Valley - as an active investor in 350 startups at their earliest stages including Airtable, Substack, and Rappi. This year he announced that Mercury raised $300 million at $3.5 billion valuation. He also announced his $26 million fund to back early-stage startups. In this episode we talk about why founders make the best venture investors, his experience with investors at Mercury, and what it takes to scale a unicorn.Stay tuned next week to hear episode 2 about Immad's life so far and how he dealt with the panic of the weekend Silicon Valley Bank failed.Building a purpose driven company? Read more about Giant Ventures at www.Giant.vc.Music credits: Bubble King written and produced by Cameron McLain and Stevan Cablayan aka Vector_XING. Please note: The content of this podcast is for informational and entertainment purposes only. It should not be considered financial, legal, or investment advice. Always consult a licensed professional before making any investment decisions.

Do you really need a fancy all-in-one CRM to run your business like a pro? Plot twist: NOPE. In this episode, I'm breaking down how I've successfully onboarded hundreds of clients over the years—without ever stepping foot inside Dubsado, Honeybook, or any of those popular client management tools.This episode was inspired by a question from my Six-Figure Sprint client, Alyssa, who asked what CRM everyone uses. Spoiler: I don't use one. And the real kicker? I don't think you need to either (unless you want to!).Instead, I'm sharing my super streamlined, rinse-and-repeat onboarding process that doesn't require any complicated software. It's simple, boring, profitable—and ADHD-friendly. If your current system is clunky, chaotic, or (let's be honest) non-existent, this one's for you.In this episode, you'll learn:Why I've never used a CRM (and still built a multiple six-figure business)What you actually need to onboard clients seamlessly (hint: it's not 12 tools)A step-by-step walkthrough of my onboarding workflowThe 3 essential tools I use (and how to set them up in less than an hour)Why the welcome email is the most important part of your client experienceHow to use Asana or Airtable to manage clients without the overwhelmThe psychology behind clear client communication—and how it prevents burnoutMentioned Resources:Download the free client welcome email template: https://courtneychaal.com/welcome-emailWatch the free masterclass: https://courtneychaal.com/masterclassJoin Yay for Clients: https://courtneychaal.com/shopApply for Six-Figure Sprint: https://courtneychaal.com/apply Learn how to build a Client Booking Machine! I'll teach you the entire process at this free masterclass (a must-watch for service providers): https://courtneychaal.com/masterclass

If life has been lifing hard lately and you're wondering, "How am I supposed to keep showing up in my business like this?"…this episode is going to blow your mind in the most practical way. Today I'm joined by Jordan Gill, creator of Systems Saved Me, longtime VIP Day queen, and the systems brain you wish you had on retainer. We talk about how she turned a 3-hour daily school commute into a content machine that produces up to 80 pieces of content a day, without her sitting at a laptop, and without sounding like an AI robot. This conversation is part systems masterclass, part permission slip to build a life-first business and let automation and collaborations do the heavy lifting. In this episode, we dive into: How Jordan accidentally discovered she's a "systems person" and went from content strategist for a big-name online brand to founder of Systems Saved Me. Her exact "car-to-content" workflow: How she uses a 45-minute school run to answer 10 interview-style questions Why each question becomes 8 pieces of content across platforms The tools she uses (Cleft, Telegram, Zapier, Airtable, ChatGPT, Metricool) to automate everything behind the scenes. Using AI without losing your voice: how Jordan uses AI to organize, structure, and repurpose her actual words, not replace them. The number one system she recommends for non-systems people who feel overwhelmed (spoiler: it's your scheduler, not a 47-step backend build). Collaboration as a growth strategy – how Jordan approaches collabs so they feel like real relationships, not awkward "networking." Why some of her best clients come from collaborations and how she thinks about long-game reciprocity (not tit-for-tat). The "unusual" ways she runs her business: Why she's never required collaborators or speakers to promote her events Why she has always paid her speakers and how that aligns with her values Her philosophy on creating share-worthy offers that people can't help talking about Connect with Jordan →Get Her Carpool Content System Here: https://systemssavedme.spiffy.co/a/Y7zFnxeG7n/5720  →Connect with Jordan on Instagram: @systemssavedme   Connect with Meg →Snag your seat in the Edge Led Launch System Workshop: https://meganyelaney.com/black-friday-workshop-opt-in  This workshop will show you how to choose the right topics, craft edge-led messaging, and structure launches that convert even when your Instagram reach is trash. →Come say hi on Instagram: https://www.instagram.com/meganyelaney       

Are you addicted to complexity in your business… but calling it “freedom” and “creativity”?Yeah. Been there. Built a 17-tab Airtable base there.This week on the podcast, I'm getting REAL about what's holding so many service providers back from making consistent, six-figure income—and surprise! It's not your marketing, or your audience size, or the fact that you haven't posted on Instagram in a week. It's the way you're clinging to chaos in the name of passion and possibility.This episode is your wake-up call.We're talking about the personal and strategic shift I'm making for 2026: boring and profitable.This is not about making your business soulless. It's about getting laser-focused, creating repeatable systems, and constraining your energy so that your business runs smoother, pays you more, and takes less of your life force to operate.I'll walk you through what's changing in my business, the symptoms of over-complexity you might not realize you're dealing with, and how to adopt the “boring and profitable” mantra to simplify and scale.And hey, if you're multi-passionate, high on ideas, or allergic to planning... you're gonna feel very seen.In this episode, we'll cover:Why creative entrepreneurs overcomplicate EVERYTHINGThe 4 main functions of your business and how to simplify each oneSigns your business is too complex (even if it's “working”)The sneaky drama you're addicted to (and how it's costing you money)What actually builds a profitable business (hint: it's not another new offer)How I'm structuring my 2026 with boring, repeatable systemsWhat it takes to become a 6-figure CEO—and what's getting in your wayResources & Mentions:

Chris and Daniel unpack how AI-driven document processing has rapidly evolved well beyond traditional OCR with many technical advances that fly under the radar. They explore the progression from document structure models to language-vision models, all the way to the newest innovations like Deepseek-OCR. The discussion highlights the pros and cons of these various approaches focusing on practical implementation and usage.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiFramer – Design and publish without limits with Framer, the free all-in-one design platform. Unlimited projects, no tool switching, and professional sites—no Figma imports or HTML hassles required. Start creating for free at framer.com/design with code `PRACTICALAI` for a free month of Framer Pro.Upcoming Events: Register for upcoming webinars here!

Running a content marketing agency means wearing about 15 hats before lunchtime… strategist, editor, designer, writer, project manager, and sometimes therapist (to yourself and clients).To keep everything flowing (without burning out), having the right tech stack is non-negotiable. Over the years, my toolkit has evolved with my business - from solo freelancer to agency owner managing multiple clients, team workflows, and creative outputs across platforms.So in true “teach what you do” style, here's a look behind the curtain at the tools that power Content Queen, from content planning and editing to scheduling, communication, and client delivery.If you LOVED this episode, make sure you share this on your Instagram stories and tag us @contentqueenmariah. ⁠⁠⁠LEARN THE DETAILS OF A CONTENT STRATEGY WITH MY FREE AUDIO GUIDE⁠⁠⁠KEY EPISODE TAKEAWAYS

Runway is building FP&A software that solves what Siqi Chen calls "the impossible problem"—matching Excel's speed and flexibility for thinking while functioning as an enterprise finance platform. In this episode of The Front Lines, wew sat down with Siqi to unpack Runway's mischief marketing playbook, why they enriched hot sauce pre-orders for lead gen, and how they're implementing AI as a coworker rather than a copilot. Topics Discussed: The unit economics behind the Burn Rate hot sauce campaign: $40K spend, 5K pre-orders, millions of views  How Siqi justifies creative marketing spend as CEO and CFO: downside scenarios must break even, upside gets uncapped returns  Naval's prescient 2020 advice: don't call it CFO AI because "everything's going to be AI anyway"  Why finance buyers completely flipped on AI in 24 months—from indifferent to requiring it  The three emotional triggers that drive FP&A tool adoption: frustration, resentment, anxiety  Runway's approach to competing with Excel by changing abstraction layers, not features  Building AI as a coworker (Ari) that lives in Slack, email, and comments—not a sidebar  Why proof-of-human marketing compounds in value as AI slop becomes the baseline GTM Lessons For B2B Founders: Model creative campaigns like venture bets with downside protection: Siqi's framework: $40K for 200 hot sauces wrapped with $100 bills equals 1.5 deals to break even at mid-five-figure ACVs. But the real play was generating 5,000 pre-orders, enriching the top 200, and converting ICP matches at "well above 1%" into pipeline. The math ensures you don't lose money in downside scenarios while creative execution delivers uncapped upside. For B2B founders: calculate your break-even deal count, then structure campaigns where lead gen mechanics provide a safety net under the brand play. Hire for proof of work, not creative credentials: When Cal (Taika co-founder) cold-emailed Siqi with designed mockups of Burn Rate hot sauce and Runway jerseys, that was the interview. Siqi was already a Taika customer who remembered the 415 phone number branding on the can. His advice: "There's no better resume than someone saying 'hey, I submitted a pull request' or 'here's some designs.'" For creative roles especially, evaluate the artifacts directly rather than filtering through credentials or pitches about what they could do. Sell to emotion-driven active searchers, not satisfied users: Runway identified three specific emotions that trigger FP&A software searches: frustration (manually pulling from 20+ data sources monthly, copy-pasting QuickBooks exports), resentment (department heads treating finance requests as "the stupid form" and ignoring deadlines), and anxiety (one error in 10 million Google Sheets cells breaks the entire model). These aren't rational pain points—they're emotional breaking points that drive active solution-seeking. Don't build go-to-market around convincing satisfied Excel users. Instead, optimize for discovery when these specific emotions converge. Treat abstraction changes as category creation opportunities: Siqi explains Airtable's success came from changing Excel's abstraction from cell to row, enabling databases and applications. Runway's insight: business planning requires abstraction changes that Excel can't provide—specifically treating the model as a "game engine" or "simulation of a business" rather than a spreadsheet. The category emerged from that technical insight, not from marketing positioning. For technical founders: identify where your abstraction layer change creates fundamentally new capabilities, then let category definition follow from customer language around those capabilities. Time creative marketing to buyer perception shifts: Two years ago, Runway demoed AI features to leads who "didn't care at all." Today, buyers "don't care what the AI feature is, they just care that it's AI"—a complete flip. Meanwhile, Runway's competitors use .ai domains while Runway uses .com, creating unexpected differentiation. The lesson: buyer perception of emerging technologies follows unpredictable curves. Creative marketing that feels early can land perfectly if timed to perception inflection points. Track not just technology maturity but buyer discourse and demand signals to time creative bets. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Waymo's VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.Featuring:Drago Anguelov – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Waymo ResearchNew Insights for Scaling Laws in Autonomous DrivingAI in MotionSponsors: Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Register for upcoming webinars here!

Dan and Chris unpack whether today's surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation?Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks: Powell says that, unlike the dotcom boom, AI spending isn't a bubble: ‘I won't go into particular names, but they actually have earnings'Sponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!

Ever feel like you're burning through tactics (LinkedIn, conferences, outbound) with nothing sticking while your spouse picks up the financial slack? You're smart enough to execute anything, but you're making million-dollar decisions about equity, offshore teams, and pipeline strategy completely alone. Your peer group can't help because they're still solopreneurs. Your casual mentors give generic advice. And you'd pay someone a fortune just to tell you what you did wrong in the last 12 months. Two consultants I spoke with, both mid-to-high six figures and both technically brilliant, were living this exact reality. One's a Salesforce partner wrestling with niche versus product focus. The other's an Airtable partner navigating equity deals with a peer group that's outgrown. In this episode, I break down why strategic isolation kills growth and reveal the three things you can't get from your current support system: pattern recognition across multiple businesses, permission to challenge your assumptions, and execution frameworks that compress time.Resources and LinksWatch the video hereApply for Mentoring herePrevious episode: 646 - Why This Consultant Targets Job Postings Instead of Cold Outreach (And Gets Better Results) with Andy CulliganCheck out more episodes of the Paul Higgins PodcastSubscribe to our YouTube channel: @PaulHigginsMentoringJoin our newsletterSuggested resources

Stop losing deals after the demo. Roy Mathew shows how to align every next step to what buyers actually care about. This is next-level sales leadership in action.

Today, I'm pulling back the curtain and sharing every system and tool I use to stay organized, land brand deals, and keep my business running while I'm on the go. From pitching tools to project management to the #1 most underrated resource , you'll walk away with practical tools you can plug into your own workflow today. I break down the exact business systems and tools I use daily, weekly, and monthly to manage my travel creator business. If you're a travel influencer or content creator who's ready to turn your creativity into a streamlined business, this episode is packed with tips, tools, and insider tricks.What You'll Learn:

Embracing slow and steady growth, scaling a food blog without losing joy or balance, and hiring team members with Isabel Orozco-Moore from Isabel Eats. ----- Welcome to episode 542 of The Food Blogger Pro Podcast! This week on the podcast, Bjork interviews Isabel Orozco-Moore. Scaling a Team and Reaching 2 Million Monthly Pageviews In this episode, we're welcoming back Isabel Orozco-Moore from Isabel Eats, who first joined us on the podcast back in 2019, just after she had narrowed her niche to Mexican recipes. Since then, she's grown her blog from 650,000 to over 2 million monthly pageviews and grown her team to 3 full-time employees (including her husband!) and several contractors. Isabel shares how she's built a sustainable business by focusing on slow, intentional growth, smart hiring, and maintaining joy in her work. Bjork and Isabel chat about how she avoids the comparison trap, what it's like working with her husband, and how she uses tools like Airtable to stay organized while managing a growing team. Isabel also gives us a peek into her upcoming cookbook project (coming spring 2027!) and shares what it really takes to scale a business while still loving what you do. Three episode takeaways: How Isabel balances making, managing, and scaling — Even as her traffic and team have grown, Isabel has stayed connected to the creative side of her business by focusing on what she loves most — developing recipes in her niche and creating videos — not managing a team. Systems and support are game changers — Hiring strategically, using tools like Airtable, and taking advantage of Raptive's SEO support have helped Isabel delegate tasks, stay organized, and focus on the creative work she loves. Balance fuels longevity — From setting boundaries around her work to prioritize family time to avoiding comparison, Isabel shares how finding balance has kept her passionate, efficient, and motivated. Resources: Isabel Eats The Freedom of a Niche with Isabel Orozco-Moore The Future of Wanting (in an age of A.I.) Slow Productivity Toggl Focus Things App How to Get Things Done, Stay Focused and Be More Productive with Dr. Cal Newport Asana Airtable Buy Back Your Time Slack Semrush Pinch of Yum Email Crush Diversifying Income Series: Monetizing Your Email List with Matt Molen Email Marketing for Bloggers with Matt Molen WisprFlow Grammarly Raptive Tastes Better from Scratch Follow Isabel on Instagram Join the Food Blogger Pro Podcast Facebook Group Thank you to our sponsors! This episode is sponsored by Raptive. Interested in working with us too? Learn more about our sponsorship opportunities and how to get started here. If you have any comments, questions, or suggestions for interviews, be sure to email them to podcast@foodbloggerpro.com. Learn more about joining the Food Blogger Pro community at foodbloggerpro.com/membership.

In this fully connected episode, Daniel and Chris explore the emerging concept of tiny recursive networks introduced by Samsung AI, contrasting them with large transformer based models. They explore how these small models tackle reasoning tasks with fewer parameters, less data, and iterative refinement, matching the giants on specific problems. They also discuss the ethical challenges of emotional manipulation in chatbots.Featuring: Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:Less is More: Recursive Reasoning with Tiny NetworksResearchers detail 6 ways chatbots seek to prolong ‘emotionally sensitive events'Sponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Fabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiMiro – The innovation workspace for the age of AI. Built for modern teams, Miro helps you turn unstructured ideas into structured outcomes—fast. Diagramming, product design, and AI-powered collaboration, all in one shared space. Start building at miro.comUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!

As AI systems move from simple chatbots to complex agentic workflows, new security risks emerge. In this episode, Donato Capitella unpacks how increasingly complicated architectures are making agents fragile and vulnerable. These agents can be exploited through prompt injection, data exfiltration, and tool misuse. Donato shares stories from real-world penetration tests, the design patterns for building LLM agents and explains how his open-source toolkit Spikee (Simple Prompt Injection Kit for Evaluation and Exploitation) is helping red teams probe AI systems.Featuring:Donato Capitella – LinkedIn, XChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:ReversecSponsors:Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org.Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiUpcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they've scaled AI solutions. Don't miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today!Register for upcoming webinars here!

Katie Kim shares how she turned a $50K bakery investment into a $5.5M project, scaled her family business, and now teaches others to develop smarter.In this episode of RealDealChat, Jack sits down with Katie Kim, real estate developer, CCIM, and founder of The Kim Group, to talk about her journey from growing up in a construction family to leading multimillion-dollar development projects.Katie reveals how she turned a $50K bakery investment into a $5.5M project, why scars and setbacks led her to get her CCIM designation, and how she now teaches aspiring developers to avoid costly mistakes through her Real Estate Developer 101 Bootcamp.She also shares why negotiations are where the real fun happens, how to build resilient teams, and why she believes in “AI-enhanced, human-powered” real estate.Here's what you'll learn in this conversation:How Katie got her start in real estate at 16 with a no-money-down dealLessons from running her family development company & launching The Kim GroupHow a $50K bakery project became a $5.5M development with incentivesCreative financing strategies beyond seller financing & down paymentsWhy failure and scars often teach more than winsThe role of mindset, grit, and negotiation in getting real deals doneWhy short selling during 2008 motivated her to become a CCIMHow to build partnerships and choose the right team membersTips for leadership: “Don't bring me problems without 3 solutions”How AI, Airtable, and automations are transforming development todayWhy Katie believes in “fail faster” and taking reps in real estate

This week, we chat with Katie Stanton!Katie is the Founder and General Partner of Moxxie Ventures. Katie is an investor, operator, board member, and proud mom of three kids and two “poorly-trained” dogs. She has built her career leading teams at Yahoo, Google, Twitter, and Color, and also served in the Obama White House and Clinton State Department.As Founder and Managing Partner of Moxxie Ventures, Katie backs entrepreneurs tackling hard problems that improve life, work, and the planet. She was also a Founding Partner of #Angels and has invested in over 50 early-stage companies including Airtable, Coinbase, Cameo, Carta, and Modern Fertility.Katie currently serves on the Boards of Vivendi and Yahoo and previously served on the Board of Time Inc. Her career has been defined by a commitment to brilliant people, bold ideas, and building a better future.✨ This episode is presented by Brex.Brex: brex.com/trailblazerspodThis episode is supported by Gusto, OpenPhone & Athena.Gusto: gusto.com/trailblazersQuo: Quo.com/trailblazersAthena: athenago.me/Erica-WengerFollow Us!Katie Stanton: @katies@thetrailblazerspod: Instagram, YouTube, TikTokErica Wenger: @erica_wenger

Julie Zhuo is the former VP and Head of Design at Facebook (now Meta), author of the bestselling book The Making of a Manager, and co-founder of Sundial, an AI-powered data analysis company. Also, my first-ever podcast guest over 3 years ago!In our conversation, we discuss:1. The three core manager skills that translate directly to managing AI agents2. How her team uses AI to learn new skills 10x faster3. The “diagnose with data, treat with design” framework for balancing gut and data4. Why hypergrowth AI companies have terrible data infrastructure (and why it doesn't matter)5. How to give feedback that actually lands—including Julie's exact script for difficult conversations6. What Julie's teaching her kids about an AI future (hint: it's not coding or STEM)—Brought to you by:Mercury — The art of simplified financesDX — The developer intelligence platform designed by leading researchersPostHog—How developers build successful products—Transcript: https://www.lennysnewsletter.com/p/from-managing-people-to-managing-ai-julie-zhuo—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/172723725/my-biggest-takeaways-from-this-conversation—Where to find Julie Zhuo:• X: https://x.com/joulee• LinkedIn: https://www.linkedin.com/in/julie-zhuo/• Website: https://www.juliezhuo.com/• Newsletter: https://lg.substack.com/• Sundial: https://sundial.so/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Welcome back, Julie!(05:18) The success of The Making of a Manager(08:41) Why AI will make everyone a manager(11:38) The future of management roles(14:00) Empowering teams with AI(21:30) Specific roles being accelerated by AI(26:53) Data analysis in AI companies(32:02) The role of data in design(37:21) The evolving role of managers in the AI era(40:22) Embracing change and uncertainty(42:14) Timeless lessons for managers(49:03) Balancing strengths and weaknesses(57:49) Building a feedback culture(01:05:33) Creating win-win situations(01:09:27) Being aware of your own energy and conviction(01:12:12) Navigating disagreements with higher-ups(01:15:57) AI corner(01:20:08) Contrarian corner(01:23:14) Lightning round and final thoughts—Referenced:• Julie Zhuo on accelerating your career, impostor syndrome, writing, building product sense, using intuition vs. data, hiring designers, and moving into management: https://www.lennysnewsletter.com/p/episode-2-julie-zhuo• Waymo: https://waymo.com/• How we restructured Airtable's entire org for AI | Howie Liu (co-founder and CEO): https://www.lennysnewsletter.com/p/how-we-restructured-airtables-entire-org-for-ai• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Inside ChatGPT: The fastest growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/behind-the-founder-marc-benioff• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• The Magic Loop: https://www.lennysnewsletter.com/p/the-magic-loop• Dunning-Kruger effect: https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect• Eric Antonow on LinkedIn: https://www.linkedin.com/in/antonow/• Methaphone: https://methaphone.com/• Replit: https://replit.com/• “Baby” by Justin Bieber on Spotify: https://open.spotify.com/track/6epn3r7S14KUqlReYr77hA• Kingdom Rush: https://www.kingdomrush.com/• Dr. Becky on TikTok: https://www.tiktok.com/@drbeckyatgoodinside• Emily Oster on TikTok: https://www.tiktok.com/@profemilyoster• La La Land on Netflix: https://www.netflix.com/title/80095365• Granola: https://www.granola.ai/• Matic robots: https://maticrobots.com/• Limitless pendant: https://www.limitless.ai/• How I AI: https://www.youtube.com/@howiaipodcast—Recommended books:• The Making of a Manager: What to Do when Everyone Looks to You: https://www.amazon.com/Making-Manager-What-Everyone-Looks/dp/0525540423• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884/• Zen and the Art of Motorcycle Maintenance: An Inquiry into Values: https://www.amazon.com/Zen-Art-Motorcycle-Maintenance-Inquiry/dp/0061673730• Conscious Business: How to Build Value Through Values: https://www.amazon.com/Conscious-Business-Build-through-Values/dp/1622032020• Good Inside: A Practical Guide to Resilient Parenting Prioritizing Connection Over Correction: https://www.amazon.com/Good-Inside-Guide-Becoming-Parent/dp/0063159481/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Howie Liu is the co-founder and CEO of Airtable, the no-code platform valued at around $12 billion. After a viral tweet declared “Airtable is dead” based on incorrect data, Howie led a radical transformation: reorganizing the entire company around AI, becoming an “IC CEO” who codes daily, and achieving over $100 million in free cash flow.What you'll learn:1. The “fast thinking” vs. “slow thinking” team structure that lets Airtable ship AI features weekly (inspired by Daniel Kahneman)2. Why Howie uses AI hourly (not daily) and is Airtable's #1 inference-cost user globally3. Why CEOs must become ICs again in the AI era (and how to restructure your calendar to make it possible)4. Why “playing” with AI tools should be mandatory—Howie tells employees to cancel all meetings for a week to experiment5. The specific skills product managers, engineers, and designers need to develop to succeed in the AI era6. Why evals can kill innovation (and when to use “vibes” instead)—Brought to you by:LucidLink—Real-time cloud storage for teamsDX—The developer intelligence platform designed by leading researchersClaude.ai—The AI for problem solvers and enterprise—Where to find Howie Liu• X: https://x.com/howietl• LinkedIn: https://www.linkedin.com/in/howieliu/• Email: howie@airtable.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Howie Liu and Airtable(04:05) The “Airtable is dead” viral tweet controversy(08:07) The rise of IC CEOs(10:57) AI's paradigm shift in product development(16:27) Specific changes Airtable has made(21:38) Fast- and slow-thinking teams(32:57) The emergence of new form factors in AI models(34:48) Airtable's vision and philosophy(40:20) Empowering teams with AI tools(46:50) Encouraging experimentation and play(50:55) Cross-functional skills in product teams(01:03:35) The importance of evals and open-ended testing(01:08:06) Key strategies for AI-driven success(01:12:43) Counterintuitive startup wisdom(01:22:21) Don't step away from the details that you love(01:25:50) Advice for aspiring engineers and designers(01:30:00) Lightning round and final thoughts—Referenced:• Airtable: https://www.airtable.com/• All In podcast: https://allin.com/• Nikita Bier on X: https://x.com/nikitabier• Figma: https://www.figma.com/• The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code | Dan Shipper (co-founder and CEO of Every): https://www.lennysnewsletter.com/p/inside-every-dan-shipper• Every: https://every.to/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Rippling: https://www.rippling.com/• Omni: https://www.airtable.com/lp/ai-psu-plp• How ChatGPT accidentally became the fastest-growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Palantir: https://www.palantir.com/• Harvey: https://www.harvey.ai/• v0: https://v0.dev/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Replit: https://replit.com/• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/building-lovable-anton-osika• Runway Game Worlds: https://play.runwayml.com/login• Sesame: https://www.sesame.com• NotebookLM: https://notebooklm.google• Salesforce: https://www.salesforce.com• Andrew Ofstad on LinkedIn: https://www.linkedin.com/in/aofstad/• Stripe: https://stripe.com/• Eames chair: https://en.wikipedia.org/wiki/Eames_Lounge_Chair• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• IDEO design thinking: https://designthinking.ideo.com/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• The Studio on AppleTV+: https://tv.apple.com/us/show/the-studio/umc.cmc.7518algxc4lsoobtsx30dqb52• Silicon Valley on HBOMax: https://www.hbomax.com/shows/silicon-valley/b4583939-e39f-4b5c-822d-5b6cc186172d• Self Edge: https://www.selfedge.com/• Studio D'Artisan: https://www.selfedge.com/studio-dartisan• Whitesville T-shirt: https://store.toyo-enterprise.co.jp/shopbrand/ct48/• Guest Series | Dr. Paul Conti: How to Understand & Assess Your Mental Health: https://www.hubermanlab.com/episode/guest-series-dr-paul-conti-how-to-understand-and-assess-your-mental-health—Recommended books:• Thinking, Fast and Slow: https://www.amazon.com/Thinking-Fast-Slow-Daniel-Kahneman/dp/0374533555• The Three-Body Problem: https://www.amazon.com/Three-Body-Problem-Cixin-Liu/dp/0765382032• Trauma: The Invisible Epidemic: How Trauma Works and How We Can Heal From It: https://us.amazon.com/Trauma-Invisible-Epidemic-Works-Heal/dp/1683647351/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Brian Balfour is the founder of Reforge, the former VP of Growth at HubSpot, and a student (and teacher) of product growth. Brian has studied every major platform shift—from Facebook to Apple to Google—and he's spotted a pattern that's about to repeat with ChatGPT.In this conversation, you'll learn:1. The 4-step cycle every platform follows (and why ChatGPT just entered step 2)2. Why ChatGPT's platform launch could be bigger than Facebook's early platform3. The exact signals that ChatGPT will launch a third-party platform within six months4. Why you have six months (not years) to make your platform bet5. Why companies that don't integrate with ChatGPT will lose to competitors that do6. How Zynga grew to $1B by betting on Facebook's platform early (before it was obvious)7. Why so few companies are actually doing what they need to be doing right now—Brought to you by:DX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyMiro—A collaborative visual platform where your best work comes to life: https://miro.com/lenny—Transcript: https://www.lennysnewsletter.com/p/why-chatgpt-will-be-the-next-big-growth-channel-brian-balfour—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/170294620/my-biggest-takeaways-from-this-conversation—Where to find Brian Balfour:• X: https://twitter.com/bbalfour• LinkedIn: https://www.linkedin.com/in/bbalfour/• Website: https://brianbalfour.com/• Substack: https://blog.brianbalfour.com/• Podcast: https://www.reforge.com/podcast/unsolicited-feedback—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Welcome back, Brian!(04:13) The changing landscape of product growth(05:09) The importance of distribution(08:14) The role of new distribution platforms(09:45) The four-step cycle of distribution platforms(17:38) Examples of platform cycles(30:01) The rise of ChatGPT(44:47) The future of AI agents(46:01) Preferred partners and platform credibility(47:18) Monetization mechanisms and free tiers(48:14) Betting strategies for startups(01:04:34) Adopting AI tools: challenges and strategies(01:08:41) The importance of hard constraints(01:14:23) Effective AI adoption in companies(01:19:05) Lightning round and final thoughts—Referenced:• The Next Great Distribution Shift: https://blog.brianbalfour.com/p/the-next-great-distribution-shift• Brian Balfour: 10 lessons on career, growth, and life: https://www.lennysnewsletter.com/p/brian-balfour-10-lessons-on-career• This Week #9: Breaking into growth, leading with influence, and (not) stepping on toes: https://www.lennysnewsletter.com/p/this-week-9-breaking-into-growth• Distribution vs. Innovation: https://a16z.com/distribution-vs-innovation/• On Platform Shifts and AI: https://caseyaccidental.com/on-platform-shifts-and-ai/• How to sell your ideas and rise within your company | Casey Winters, Eventbrite: https://www.lennysnewsletter.com/p/how-to-sell-your-ideas-and-rise-within• Thinking beyond frameworks | Casey Winters (Pinterest, Eventbrite, Airbnb, Tinder, Canva, Reddit, Grubhub): https://www.lennysnewsletter.com/p/thinking-beyond-frameworks-casey• ChatGPT: https://chatgpt.com/• Claude: https://claude.ai/• Gemini: https://gemini.google.com/• Vine: https://en.wikipedia.org/wiki/Vine_(service)• Periscope: https://en.wikipedia.org/wiki/Periscope_(service)• Myspace: https://en.wikipedia.org/wiki/Myspace• Friendster: https://en.wikipedia.org/wiki/Friendster• AltaVista: https://en.wikipedia.org/wiki/AltaVista• Lycos: https://www.lycos.com/• HubSpot: https://www.hubspot.com/• Zynga: https://www.zynga.com/• TBPN: https://www.tbpn.com/• Deedy Das on LinkedIn: https://www.linkedin.com/in/debarghyadas/• ChatGPT's product retention curves are a product manager's wet dream: https://www.linkedin.com/posts/debarghyadas_chatgpts-product-retention-curves-are-a-activity-7338384752393035776-ice1/• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Udemy: https://www.udemy.com/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can't stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell• Notion: https://www.notion.com/• Airtable: https://www.airtable.com/• Monday: monday.com• Sierra: http://sierra.ai• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• Introducing ChatGPT agent: bridging research and action: https://openai.com/index/introducing-chatgpt-agent/• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Marc Andreessen on Why Optimism Is the Safest Bet: https://nymag.com/marc-andressen-2014-10-20/• Reforge: https://www.reforge.com• Reforge Insights: https://www.reforge.com/insights• Shopify: https://www.shopify.com/• 25 proven tactics to accelerate AI adoption at your company: https://www.lennysnewsletter.com/p/25-proven-tactics-to-accelerate-ai• Clouded Judgement: https://cloudedjudgement.substack.com/• NFX: https://www.nfx.com/news• James Currier: https://www.nfx.com/team/james-currier• Hallway Chat: https://www.hallwaychat.co/• Bryan Johnson on LinkedIn: https://www.linkedin.com/in/bryanrjohnson/• Silicon Valley on HBO: https://www.hbomax.com/shows/silicon-valley/b4583939-e39f-4b5c-822d-5b6cc186172d• Stick: https://tv.apple.com/us/show/stick/umc.cmc.52w04zy67tiv11p8xvbc57wmc• Ergonofis standing desks: https://ergonofis.com/en-us/collections/standing-desks• Coping with the loss of a child and protecting your time | Brian Balfour (father of 2, CEO and founder Reforge, venture partner): https://www.startupdadpod.com/coping-with-the-loss-of-a-child-and-protecting-your-time-brian-balfour-father-of-2-ceo-and-found/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com