Podcasts about b2b saas

George had to wind down his last startup and give investors their money back. He went deep into the valley of despair, certain he'd missed his window to build something big. Then he met a co-founder, decided to start over, and started selling.In this episode, George breaks down how a customer signed a $36K pilot off nothing but a Loom and a one-pager, how cold email took him from zero to $1M ARR with no sales team, and why a "seven out of ten" is the most dangerous hire you can make.Why You Should ListenHow a customer signed a $36K pilot after a single Loom and zero calls.Why he gave the money back on his last startup—and what "follow your energy" really means.How cold outbound email built his first $1M ARR with no sales team.Why a "seven out of ten" is the most dangerous hire you can make.Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, fintech, accounts receivable automation, AI agents, cold outbound email, B2B SaaS, Series A fundraising, services as softwareChapters00:00:00 Intro00:01:39 The Moment of True Product Market Fit00:03:33 Shutting Down a Small-Market Startup00:07:44 Picking Fintech From Five Ideas00:17:12 From Black Box to Full App00:24:47 $1M ARR on Cold Email Alone00:36:11 Why a "Seven" Is the Most Dangerous Hire00:42:15 Compressing a $25M Series ASend me a message to let me know what you think!

Ara Ohanian is the CEO of Netstock, a global provider of AI-powered inventory optimization and supply chain planning software for mid-market businesses. An experienced B2B SaaS and enterprise software leader, he brings deep insight into the challenges companies face when managing inventory, forecasting demand, and scaling operations. Ara leads Netstock's mission to help businesses reduce stockouts, lower excess inventory, and unlock working capital. He has held executive roles at Systech, Unite Us, Infor, and Dubilier & Co., bringing broad expertise across supply chain, ERP, compliance, and growth strategy. In this episode… Inventory can either fuel growth or quietly drain cash from a business. When companies rely on spreadsheets or outdated planning systems, they risk tying up working capital in the wrong products while missing demand for the right ones. So how can growing businesses forecast smarter, reduce stockouts, and keep cash moving? Ara Ohanian, a seasoned B2B SaaS and enterprise software leader, says businesses need better visibility into what inventory they should have in the future, not just what they have today. He highlights the importance of using predictive planning tools to help companies make faster decisions when demand shifts, supplier costs change, or disruptions hit the supply chain. The main impact is more efficient inventory management, fewer missed sales, and less working capital tied up in excess stock. Instead of relying on manual spreadsheets, businesses can use AI-powered insights to anticipate demand across warehouses, markets, and product categories. This gives mid-market companies a stronger chance to compete with larger enterprises that have historically had access to more sophisticated planning resources. In this episode of the Inspired Insider Podcast, Dr. Jeremy Weisz speaks with Ara Ohanian, CEO of Netstock, to discuss smarter forecasting for inventory and cash flow. Ara explains predictive ERP overlays, demand planning across warehouses, and retail forecasting challenges like pricing, promotions, and shelf life. He also shares leadership lessons on culture and curiosity.

Last 4 days before regular tickets sell out at AI Engineer World's Fair - this is the single biggest gathering of AI Engineers, Founders, Leaders, and Researchers in the world. Attendees get >$5000 worth of sponsor credits and talk tracks are looking FANTASTIC. Join us!The AI scaling debate always focuses on the question of “how do we get more GPUs?” but the better question may be: how do we make the most of ones we already have.The fact that a frontier lab like xAI could be running at sub-10% MFU (Model FLOPs Utilization) is just a hint at what the real problem may be.For context, older frontier-scale training runs were already much higher than 10%. GPT-3 was around 21% MFU. Gopher was around 32%. Megatron-Turing NLG was around 30%. PaLM reached around 46%. And our guest Anjney says best-in-class MFU today is closer to 60–70%.It's not necessarily that xAI is uniquely incompetent (it's clear they have talented folks) but rather the priorities may be flipped in the GPU arms race.While GPU access is a bottleneck, simply increasing CapEx won't automatically translate to better models as frontier AI is increasingly a systems problem: scheduling, utilization, networking, kernels, frameworks, data pipelines, parallelism, cluster reliability, and the thousand small decisions that determine whether your theoretical FLOPs become real training progress.From building Discord's developer platform and backing frontier AI companies like Anthropic, Mistral, Black Forest Labs, and Periodic Labs to now building AMP's independent compute grid, Anjney Midha has spent years close to the real bottlenecks of AI scaling. In this episode, Anjney joins swyx at Periodic Labs to unpack why the AI race is not just about buying more GPUs, why 95% utilization would have been considered an outage at Google, and why the next era of AI infrastructure has to be more aligned, more efficient, and more responsible.We go deep on AMP's vision for a compute grid that makes FLOPs flow like megawatts, the difference between full-stack AI labs and horizontal pooling, why AI data centers need community buy-in, and how compute markets could evolve into something closer to an independent system operator. Anjney also explains why DeepMind's unpublished research points to a market failure, why end-of-life prediction remains one of the most important AI applications he has thought about for fourteen years, and why “output maxing” may become a new discipline for frontier systems.We also discuss Anthropic's culture, why “luck favors the prepared mind” in coding models, how Claude cracked coding, why too much capital too early can make AI labs fragile, what Periodic Labs is trying to do with science and superconductors, why great researchers can become great CEOs, and why Silicon Valley is both deeply missionary and deeply mercenary.We discuss:* Why 95% utilization was considered an outage at Google* Why AI infrastructure waste compounds at frontier-lab scale* Why “move fast and break things” does not work for AI data centers* How data center backlash, power grids, and community incentives shape AI scaling* AMP's vision for making FLOPs flow like megawatts* Why compute needs an independent system operator* How interruptible demand and dynamic prioritization worked inside Google* Why DeepMind research hoarding creates negative externalities* AMP's 1.2GW base-load ambition and the need for 6GW of spike capacity* Why end-of-life prediction could become one of AI's most important healthcare applications* Frontier Systems, output maxing, and full-stack alignment* Why APIs and abstraction layers become lossy as organizations scale* Superconductors, standards, and the dream of lossless systems* SF Compute, open protocols, and the future of compute marketplaces* Why non-NVIDIA chips can still benefit from NVIDIA's reference architecture* Trust boundaries and why chip startups need visibility into future model architectures* Why VCs often underestimate researchers as CEOs* Scientists as star athletes of the mind* Why great CEOs need to be confrontational up and down the stack* Why leading the frontier matters more than “winning”* How Anthropic cracked coding* Why culture is fragile, not a permanent moat* Why hardship was a feature, not a bug, for Anthropic* Why Anthropic's P0 was coding from day one* Periodic Labs, physics as the constraint, and technical reality* Silicon Valley mercenaries, missionary teams, and what happens after a breakthroughAnjney Midha* LinkedIn: https://www.linkedin.com/in/anjney* X: https://x.com/AnjneyMidhaAMP PBC* Website: https://amppublic.com/* X: https://x.com/amppublicTimestamps00:00:00 Introduction00:00:09 Why AI Compute Is Being Wasted00:03:17 Responsible Infrastructure and Data Center Backlash00:06:07 AMP Grid: Making FLOPs Flow Like Megawatts00:12:41 Foundry, Frontier Labs, and Research Hoarding00:14:42 Gigawatt-Scale Compute and End-of-Life Prediction00:24:08 Frontier Systems, Output Maxing, and Alignment00:27:38 Compute Markets, SF Compute, and Non-NVIDIA Chips00:32:57 Trust Boundaries, Co-Design, and Researcher CEOs00:38:17 AI Coachella and First-Principles Thinking00:42:43 Leading vs Winning in Frontier AI00:45:54 How Anthropic Cracked Coding00:48:25 Culture, Hardship, and Anthropic's P000:54:03 Periodic Labs, Physics, and Silicon Valley Mercenaries00:56:26 Rishi Valley, Singapore, and Money as a Measure00:58:47 Closing ThoughtsTranscriptIntroduction: Anjney Midha, AMP, and Compute WasteSwyx [00:00:00]: We're in Periodic Labs with Anjney Midha, CEO, founder of AMP. Welcome.Compute Utilization: Node Allocation, MFU, and AlignmentAnjney [00:00:09]: Thanks for having me. At Google, there are two types of utilization usually, right? That you're measuring in these clusters. One is node allocation, and then the other's MFU. Node utilization is usually like what percentage of cards in the data center are just, used, and that, if it's not at, 95%-Swyx [00:00:29]: There is no excuseAnjney [00:00:29]: There's no excuse, right? I think 95% at Google, which is where my co-founder, Seb, came from, he built the Borg, PBorg/GQM scheduler at Google, and there I think 95% was considered an outage, so 96% node utilization is, should be standard. And most single-tenant clusters are not running at that. So that's one. And then MFU should be, I would say the best in class today is somewhere between 60 and 70%. I think this is a leadership question, right? Fundamentally it's an alignment question, which is are the people who are funding the cluster and then deploying the cluster actually aligned? And sometimes theoretically they are, but in practice the number of people in the chain, the supply chain between, the capital and all the way to whoever's managing the cluster and then whoever's measuring what the output is, are just so many, degrees of separation away that, the, The Have you ever heard the radian metaphor, which is at the beginning of an arc, if you have two arcs that are two lines that are just off by a few degrees, that-Swyx [00:01:33]: It spreads outAnjney [00:01:34]: It spreads out, right? Or at scale. And I think what's happening is a lot of cluster implementations and infrastructure, a lot of frontier labs and other teams, that's what's happening, is they're, they initialize the plan, which is kind of like North Star with a team that wants to do good, but then they're, required to scale so fast instead of iteratively that the wastage just compounds really fast at scale. And so I think we know the answer, which is just do iterative bring ups. If you spend time with people who've been in the semiconductor industry or the DSN industry for a long time, this is not new, and I don't think AI should be an excuse. Sure. Something What is new? Okay. We have a lot of new capabilities, but that doesn't mean just abandon common sense. Common sense should always be in fashion. ? AI scaling doesn't change the in fact, if anything, AI scaling should be putting a premium on the value of common sense and infrastructure because the margin of error now is so much lower and the costs of wastage are so much higher. And the cost of wastage, by the way, is not just economic. I'm, obviously I'm, I'm an investor, or I'm an investor by background. Over the last few years now we're running an AI infrastructure business called, AMP. And I think that it's okay to say this time is different on the capabilities front. We are genuinely getting capabilities at, of the, of a kind we haven't had before. That doesn't give you an excuse to say this time is different for everything, especially infrastructure. So look, I love the hacker mindset and the hustler mindset. Now, that's great for the startup mindset, but you remember this moment where Zuck went from saying, “Move fast, break things” to, move-Responsible Infrastructure and Data Center BacklashSwyx [00:03:10]: Fast and stable infrastructureAnjney [00:03:11]: Move fast with stable infrastructure. I think now we need to move fast with, responsible infrastructure. People are going to ask where the impact is. There was a really In our class yesterday, Scott Nolan, who's the founder of General Matter, came by at Stanford to speak about energy bottlenecks. And he had a phenomenal idea. He said, “if you look at the marginal unit economics of compute per hour,” he goes, “let's call it, $4 an hour. If you're having to bring up a new data center in a new community, why not just say we're going to charge 4.50 an hour, and that marginal impact or that marginal increase, we just literally take that and give it to the local community as cash?” I can tell you as a customer of that compute, I would love that. I'd be happy to pay an additional 50 cents per hour at scale.Swyx [00:03:57]: Wow. Yeah.Anjney [00:03:58]: Because if that means the public benefit is so clear to the communities that the data centers are coming up in, I'm going to feel like that compute is much more reliable. Up to 20% of all data centers this year in the US, my understanding is are at risk.Swyx [00:04:13]: Of community backlash?Anjney [00:04:14]: Correct. Of not getting the community support they need to get brought up.Swyx [00:04:19]: Wow. That's a huge number.Anjney [00:04:20]: Yeah. Now, we, I think we should dig into what that number is. I think it's a little bit of overstated. These things can get over-reported, but it-Swyx [00:04:27]: They don't just care about jobs. They care about all the other stuff around it, right? They care about power grid, they care about environments-Anjney [00:04:33]: Power grid, permitting, and so on. And imagine I think if you said there's a new AI deal. If we're bringing up a data center in your community, we're actually going to reduce the cost of your electricity bill. Okay, now we're talking. Right? The community's going, “Okay. Now this is a deal. I feel like a partner in this.” Right now that's not happening. There will be audits, there will be investigations, and when the, when the regulators come, I don't know when it's going to be, the folks who are moving fast and breaking things in the name of AI progress better be prepared. That's certainly not how we're procuring compute. Or we're, we're trying as much as we can to work with partners who have long-term track records. Many of whom, by the way, are not, AI providers. I think this whole idea of neoclouds being somehow this new category is a lot of marketing speak. There are really good, reliable, trusted data center providers in America who've been around 20 plus years. I love those folks. They know how to Sure. Are they sponsoring happy hours at NeurIPS? No. Are they legibly listed in Build? No. Are they hanging out in my, in, situational awareness parties? No. But they're adults. I trust them.Swyx [00:05:44]: They can run LAN. They can run power.Anjney [00:05:45]: They can run LAN, power, and shell. They have credit histories. We sit down, we have a conversations. Many of them live in Silicon Valley. They've, they've had to deal with the boom and bust cycles of the internet, and I love those folks. They are stable infrastructure partners and thinkers. And I think there's a lot of short-term thinking going on in the compute layer, and it's going to catch up to us. It's not going to be good.AMP Grid: Making FLOPs Flow Like MegawattsSwyx [00:06:07]: You talk about aligning incentives, and, I would think that aligning incentives means you have the full stack in one company, which is xAI and OpenAI, right? So you as a standalone infrastructure layer, why are you somehow more aligned to your portfolio companies than people who just own the whole thing?Anjney [00:06:28]: In systems design, right, there's, there's two regimes of, architecture, right? You have integration, and then you have pooling and utilization, right? So the Or rather, the way to increase utilization often is you can do systems integration where you collapse a lot of process into one node, or you can pull out a process from a node and share that amongst various That resource amongst several different nodes. And so we see the AMP grid, which is, the, what, the system we're building here, which is basically a compute grid. We're trying to do for compute what the electric grid-Swyx [00:07:02]: PowerAnjney [00:07:02]: Yeah, what the power grid did for electricity. It-- this is a pooling and utilization layer across clouds, And so we're actually the opposite of a full stack integration like approach.Swyx [00:07:12]: Super horizontal.Anjney [00:07:13]: Where it's much more horizontal and it's, it's multi-cloud, it's multi-silicon. The goal is to try to make FLOPs flow like megawatts, and that is very hard to do today for many reasons. There's stranded pools of compute all over the place and there's no fungibility. And so right now we do it at the level of scheduling, and we often do it at the economic layer. But as we start to announce what we're working on, it's extraordinary like how many folks are coming out of the woodworks and saying, “Hey, I'm actually working on a way to make compute fungible at this part of the stack and that part of the stack.” And as a grid, we'd like all of these folks to participate on the grid. There's, people often ask me, “Andra, are you a new cloud?” And I go, “No, actually neoclouds are suppliers.” sometimes they'll ask, “Are you a venture capital firm?” I go, “No, actually they are, they are demand like sort of off-takers of the grid.” We see ourselves as what's called an independent system operator. So if you study the history of the electric grid, once it became legible to a lot of factories and industrial sort of participants that, hey, actually it turns out pooling is a good idea. We should pool our generators instead of all having a generator running at half capacity in our backyard. There was a need for an independent entity who could coordinate all these parties. Transmission line, power generation, facilities, transmission lines, factories, and that neutral coordination mechanism is very critical. In order-- If you study like the history of grids, the most enduring ones were those that never owned their own assets. They were ones that had, or often started with long-term anchors who are uncorrelated sources of demand, a steel factory, a shoe mill or whatever in a particular town who weren't competitive, where the steel factory want to spike up at night, the shoe mill wanted to spike up during the day. So then you pool and you share, right? So each of you is guaranteed some base load, but then you kind of schedule your spikes to drive a peak utilization across the town. The gold standard, so to speak, historically, has been these utility companies like PJM Interconnect in the northeast of America, where they, over many years became this what's called an ISO, an independent system operator of the grid. So that's how we see ourselves. Economically, that's what we are. From a technical perspective, we started at the scheduling layer because Seb and Mihai, who, run engineering here, built that at-Swyx [00:09:28]: Did your schedulingAnjney [00:09:28]: They did that at Google. And, -Swyx [00:09:32]: And you have infra shops from Discord as well.Anjney [00:09:35]: I have some.Swyx [00:09:35]: I don't know, I don't know if Discord is like the primary identity, but what-whatever, I'm just kind of-Anjney [00:09:39]: No, D-Discord was-Swyx [00:09:40]: Choosing a well-known name.Anjney [00:09:42]: Well, I So I was running the developer platform there. The internal infrastructure I was not responsible for. That was actually a guy by the name of Mark Smith, who was extraordinary. And yes, Discord did pool So Discord is actually a counter example. I had the chance to learn a lot about fully, full stack infra there because-Swyx [00:09:56]: It's the same thing, yeahAnjney [00:09:57]: It's the, it's the other architecture which is, Discord built its own WebRTC vo-voice and video infra. So like Discord did not use-Swyx [00:10:08]: For the calls, yeah.Anjney [00:10:09]: Yeah, did not For communication, Discord did not use third party infra. It was all built in-house. And then the way you maximize utilization was you pool demand from the world's 200 million plus monthly active gamers, right? And so that's, that's how those stacks were constructed. Again, in systems design, the two concepts that keep coming up over and over again are abstraction and composition, right? And-Swyx [00:10:31]: Bundling and unbundlingAnjney [00:10:33]: Bundling and unbundling, abstraction, composition, like verticalization and-Swyx [00:10:36]: HorizontalAnjney [00:10:36]: Horizontalization. So in that sense, AMP is an independent system operator of the grid. We pool demand, we pool supply from a number of partners we trust At about 1.3 gigawatt scale over four years. And then we pool demand from some of the world's best, research labs and so on. We're sitting at one, periodic labs who need extraordinary long-term demand. And the idea is that, each of them is guaranteed base load on the grid, but they can spike up and down flexibly on, for compute, with much shorter timelines as needed. That was roughly the design of the program I came up with at a16z called Oxygen. The same-- That was the same design of the GQM, BorgX, Borg GQM implementation at Google that Mihai and Seb had built. Which was that how do you allow, teams inside of Google, on the internal infrastructure to be guaranteed capacity, for their base workloads? But when they need to spike up on research, how could they ensure that was sufficiently there? And of course, the big innovation that was not discovered, but kind of implemented in the space, this infra space maybe three, four years ago at Google was the idea of interruptible demand, right? Where you just queue up a bunch of jobs and through this like sort of credit system, there can be a bidding mechanism.Swyx [00:11:53]: Like priorities.Anjney [00:11:54]: It's a dynamic prioritization Basically. And jobs can get interrupted based on somebody else who's saying, “what? I have 10 tokens, 10 credits I want to spend on this job.” Another like team lead, research lead is “Genie 3 or whatever is only worth five, credits, and NanoBanana2 is worth 10 credits,” and so the NanoBanana job gets priority. That's a, that's a made up example.Swyx [00:12:15]: It's very real. Brain Marketplace was real. And, we've, we've covered this on the pod with David Luan, who was-Anjney [00:12:20]: Oh, great. OkaySwyx [00:12:20]: Was there. And the criticism is that, well, actually sometimes you need central command to go all in on a thing. And actually sometimes capitalism via credits doesn't work. Not, this is not a criticism of AMP. I'm just saying, this is a thing that has been tried, internally within Google, and it led to Google missing GPT.Foundry, Frontier Labs, and Research HoardingAnjney [00:12:41]: Like, we structured ourself essentially very similarly to Google. We are structured as a holdings company. So, Alphabet holdings is Alphabet holdings, and then they've got these subsidiaries called Google and-Swyx [00:12:51]: Other betsAnjney [00:12:52]: Other bets and so on. We've got, AMP holdings, and we've got our infrastructure business, and then we've got a capital business called Foundry that incubates new frontier AI labs or invests in them as venture capital, like Periodic. We put a few hundred million dollars into Anthropic from our fund earlier this year. So wherever we feel like teams are making progress, especially researchers and so on who've pushed the frontier inside of existing labs like DeepMind, I find, there comes a point where they feel misaligned with the dictatorship of Alphabet holdings. And at that point, sometimes the dictatorship doesn't want them anymore. And they're “Thank you. You've done your job here. You've kind of helped us through the zero to one phase, and for whatever reason, we're going to deprioritize your amazing, omni model or whatever it is, and instead we're going to prioritize coding.” And, I think that's a tragedy, but I get it. They're Sergey and team are running their own business there. But that doesn't mean we the rest of us should sit around waiting for that progress to get unlocked for the rest of the world and humanity. If you think about how much extraordinary research has happened inside of DeepMind over the last 10 years, I, Demis and Sergey and those guys did such a great job. But at the end of the day, so much of that has never seen the light of day?Swyx [00:14:00]: Or they're like papers only, but they never actually shipped it to production or-Anjney [00:14:03]: What's worse is the paper is actually not even being published anymore ‘cause there's a six-month embargo inside of DeepMind, right? We've heard about this where a paper comes out, and then I think there's a six-month embargo window where if anybody on the business team says, “This could be interesting” It's embargoed for life.Swyx [00:14:18]: Exactly. So the stuff that gets published is the stuff that's not good enough.Anjney [00:14:21]: There's an adverse selection problem, basically. Yeah. At this point-Swyx [00:14:25]: It's, it's a common complaint at NeurIPS, by the way, that's “Well, why would I look at the papers that are the trash of GDM?”Anjney [00:14:31]: Again, I think it's a tragedy. I get it. They're running their business, but the rest of the I think there's negative externalities of research being hoarded, and so that'there's a market failure. And somebody needs to unlock that research, and we can't do it on our own. We only have 1.2 gigawatts of compute. That's nothing. That's about $40 billion of cloud spend. We're going to need a lot-Gigawatt-Scale Compute and End-of-Life PredictionSwyx [00:14:51]: By the way, is that's a new number. I haven't, haven't come across that gigawatt number. That's huge.Anjney [00:14:56]: Yeah. And to be clear, we haven't secured all of it. That's how much demand we have started to secure. I think publicly we haven't actually confirmed how much we have for this year. In order-Swyx [00:15:04]: Where do you want to get to?Anjney [00:15:06]: I think the steady state would be that we have a base load pool Of 1.2 gigawatts at all times Of base load capacity. For spike capacity, right now my estimate is we need roughly six gigawatts over the next four years for all our teams to feel like they were able to keep moving the frontier, whatever they're working on, whether it's, like superconductor discovery over here. There's a new investment we're working on right now, which is in the end of life prediction space in healthcare. It's extraordinary how much you can, you can give this was actually my graduate school work. I went to grad school for bioinformatics at Stanford Med. And I know we-Swyx [00:15:40]: Econ, MCS, bio.Anjney [00:15:41]: So my-- I was this really weird cat where, I was never satisfied with my major options. So at one point I was an econ major, then I was a CS major, then I was a MCS major called mathematical computational science, and they decided they were going to end that major. So I took all that coursework, and I applied it to grad school, my graduate degree in bioinformatics, which was the master's program, and then I thought I was going to do a PhD. I never ended up doing it. I dropped out and went to work at Kleiner. But I was lucky enough to apprentice with this professor at, Stanford Med. His name is Nigam Shah, and he was working on end of life prediction. Stanford is one of the only research facilities in America that has a longitudinal patient data set that's larger at scale. I think it's at least 12 million patient lives. The only larger data set is at the VA, the Veterans Affairs, of America. And to do research, like do any deep learning and so on that data set, it was called the STRIDE data set at that time, you had to be a Stanford Med School affiliate, which is why I went and enrolled in the bioinformatics department. End of deep learning was early. Nigam Shah had the visibility-- the vision to see that, you could do end of life prediction to help palliative care. In America, the, over 30% of all Medicare, Medicaid spend, at least at that time, was spent on end of life care. And what's we grew up in Asia, so we all-- Yeah, at least I won't speak for you, but I have A very different relationship with death than I find folks who grew up in America do. In America, spiritually and culturally, especially in Western societies where Christianity, the Christian tradition sort of frames death as this terminal point, there's often a judgment day and so on. The way we view death is with a finality. In Indian culture, in Hindu culture, death is one-Swyx [00:17:35]: Also, he's Buddhist as well.Anjney [00:17:36]: You're Buddhist, yeah. So it's one, it's one step in a journey of many lives, right? And so, I grew up in this city called Chennai in the south of India, and when people die, you dance on the street. There's like a procession where your body is carried to be cremated and your family, like celebrates and there's drums and so on. It's this huge thing. And, It's because the idea is that you're going to be reincarnated. You've been liberated from the responsibilities of this life, and now you're onto your next. It's a new It's like going off to a new college or whatever, right? And so it was so alien to me when I got here as an undergrad- That the medical system works backwards from that assumption that we have to view death as this terminal thing and delay it, postpone it's a bad thing. And so at the time, clinical decision support in the United States was this very primitive field. Even to this day, physicians in the United States often will tell you when you have a terminal disease, this is your, we've diagnosed you, which is great. Our ability to diagnose you is extraordinary. You have somewhere between six months to six years to live. What do you do with that information? The error bars are so high that then you In times of uncertainty, we default to culture, and when the culture is let's-- this is a bad thing, I've got to prolong my life, then you start doing things like And just to, just sort of from a systems perspective, what's going on there is Physicians often feel like they need to provide such high error bars because there's always some uncertainty in end of life diagnosis, and if you provide the wrong Diagnosis or recommendation to your patient, you can be sued for medical malpractice. And then your license can be taken away. It can be catastrophic for your career. In contrast, if in countries where that's not the case, what you often observe is that patients, physicians are quite prescriptive with their recommendation. They say, “Hey, this is your condition. The literature says that you probably have this much time on Earth left. My expert opinion is that you are an outlier or whatever.” And they try to be more prescriptive, and that empowers a patient, right? ‘Cause then a patient can say, “I trust my doctor. They said on average, I have six months to live, but if I do these things, I may have a shot because of my particular predispositions or my genetic history or whatever.” And that empowers you to go about your life in a actually more scientific way than leaning on religion, culture, spirituality, and so on. In contrast, here, because of that medical malpractice sort of thing looming over your head, a physician never gives you a clear recommendation. So instead you say, “Okay, Doc, well, let's try it all.” And then you start a whole regime of drugs and therapies, and then you often spend weeks and weeks in the hospital, and that deteriorates your quality of life. And when that deteriorates your quality of life, you instead of spending your last few days doing the things you love with your family, you're spending it on a hospital bed. And that ends up being thirty percent of Medicare and Medicaid. So it's worse for the patients. The doctors feel terrible. The American taxpayer is paying a huge amount of money. And so this is why Nigam Shah, who was this professor at Stanford, said, “Anjney, if there's “ I kind of sat down with him. I was this young, I'd, I was twenty-one, and I was “I want to work on a big problem.” He's “The big problem is end of life care.” And so we tried to do deep learning to say, to-- So we started trying to run deep learning on these tried patient data sets to say, “Could you have an AI system make a recommendation that is orders of magnitude more precise about how much time you have left once you've been diagnosed with a terminal condition than a human?” And then if we can get that precision to be high enough, then you can empower the patient. And it turns out the tech works. Like it's-- Once you get the data set, like RL works. Honestly, even regression models work. You don't need to get that fancy. At the time, we were just trying, doing like very simple neural nets.Swyx [00:21:54]: Simple solutions, yeah.Anjney [00:21:54]: Today, what we can do with RL is extraordinary. The problem remains then and now is regulatory, because you actually can't shift the burden of the wrong clinical diagnoses from the physician to the AI system. And so at that time, I got quite disillusioned ten years ago for, twelve years ago where, ‘cause I felt I just didn't have the resources to influence regulation. Today, I'm very lucky. I'm in a different place. I've, I'm a lot older, and so I've been spending a lot of time on my next incubation, which is how can we unlock the, patient empowerment by training AI models to do end of life prediction much, with much more precision and ac-Swyx [00:22:37]: Oh, wow. You're still focused on this the whole time.Anjney [00:22:40]: The-- I haven't been able to get, this out of my mind a single day for the last fourteen years. This is the hill I want, I would like to die on. There's two, I would say. What? I actually, I'd prefer not to die.Swyx [00:22:51]: Yeah, exactly.Anjney [00:22:52]: But I think two bipartisan issues, I think two issues that should be bipartisan in America are how do we empower patients to make the right clinical decisions at the end of their life, such that we're reducing the taxpayer burden with science? It's just good old science, and AI can help here. And the second is, net positive data centers, ‘cause I think that's the biggest critical bottleneck on training and good enough AI models to help people at the end of their life. So there's sort of two sides of the, of the same scaling bottleneck curve, but those two, we formed AMP as a public benefit corporation. My wife and I, who you've met, you've met Viv. Her passion is education. Her family is a long line of educators and so on, and, of physicists. And so this class is my attempt to stop being the black sheep of the family and be a, an educator. But if I'm not educating, the thing I would be doing is working, on these two problems, whether on the political spectrum or as a researcher back at, in some lab. And my hope is if anyone's listening to this podcast, if they're passionate about either of those two topics, I'd love to hear from them. We'll, we'll we can share the contact in the show notes, but, we're looking for people to join both of those missions on the, on the political side as well as on the medical side, on the research side.Frontier Systems, Output Maxing, and AlignmentSwyx [00:24:08]: You said, this is a discipline that you want to form. You call it's called variously called Frontier System. It's variously called One Person Frontier Lab. What is the ideal name or shape of this? Like the, what is the mission?Anjney [00:24:24]: Of the class?Swyx [00:24:26]: Of the discipline that you're, exploring, right? I The class is called Frontier Systems. But like for me, maybe one phrase is you're, you're just anti-waste, right? Which is wasting GPUs, wasting in human and Medicare. But is there, is there a broader theme that I'm, that maybe you can encapsulate more succinctly?Anjney [00:24:45]: Yeah. The, from an engineering perspective, it's very simple. It's output maxing. It's the, it's the department of output maxing.Swyx [00:24:51]: Making the most of what we have.Anjney [00:24:52]: Exactly. I'm a huge believer in optimal outcomes. I think both in America and other countries, we are losing our appreciation for nuance, and this is the thing of And AI is the same case, right? Oh, the bitter lesson holds. Okay, fine. But that doesn't mean you just like throw 500 GB300, 500,000 GB300s at your suboptimal model scaling and you waste a bunch of compute. It also doesn't mean that, the most optimal is to have like 50 different architectures where there isn't enough standardization. One of the reasons Anthropic has had extraordinary sort of velocity is ‘cause they picked the transform architecture and said, “This is simple. Let's double down on it,” right? And now luckily there's enough investment going to the space that we can afford other architectures, but at the time, investment was just too fragmented into other architectures, so that arguably unlocked scaling. So I think there's a philosophy. I think we all owe it to ourselves to do output maxing with a new capability called AI on a global level. I think if I was starting a new department at Stanford, depending on how fuzzy or technical I wanted to be, I'd probably call it the Department of Alignment. Like-Swyx [00:25:59]: It's an overloaded termAnjney [00:26:01]: But it is, But alignment really Is a hard problem. And I think when you unlock it, full stack alignment is super hard in any organization and in any system. Like in a, in a venture capital firm, if you can have full stack alignment between your limited partners and your, the founders who are creating the value and ultimately the public that owns the IPO stock, that is a gift that keeps giving. And when you study the history of these systems, when they start off, they usually start out small scale where the feedback loop is actually so tight that there's alignment. And then the more you try to scale, the more division of labor happens, the more specialization happens, and at each step you add abstractions. And wherever there's an API interface, there's like loss. There's communication loss. And so I think a really cool thing would be for us to figure out is there a way for us to have our cake and eat it too as an engineering discipline? Is there a way to actually scale up and scale out Without losing any alignment, without lossy transmission?Swyx [00:27:01]: You mean standards?Anjney [00:27:02]: So standards is one way. The other way is you just have net new capabilities. So like what we're trying to do here is discover new superconductors. A room temperature superconductor would be a lossless transmission mechanism for energy. We would have flying cars. We are right within a few years of having a new room temperature superconductor. So I think those are the two. You either have to standardize On protocols or API specs that allow lossless communication, or you can come up with a whole new capability that unlocks so much abundance, the standardization doesn't matter ‘cause you just unlock net new capacity. This, the, so this is what I spend my days thinking about these days.Compute Markets, SF Compute, and Non-NVIDIA ChipsSwyx [00:27:38]: No, I think every infra person at, who wants scale and wants to output max does eventually end up thinking about this. We don't have time to go into it, but we have done an episode with SF Compute-Anjney [00:27:50]: Oh, coolSwyx [00:27:50]: That is trying to standardize The futures contract for compute. I don't, I don't know how that's going by the way, but like at some point this will be public.Anjney [00:27:57]: Oh, I think Evan is awesome and SF Compute is the kind of effort that I hope we can accelerate because what often happens is these exchanges are very hard to get, they, it's hard to bootstrap them, right? Because they often require-- There's many inefficiencies between parties. There's trust boundary inefficiencies in infrastructure because you don't trust, one part of the stack doesn't trust another part of the stack to give them visibility. There's capital markets inefficiencies, there's operational efficiencies. So if you can inject like a single shock to the system of a ton of compute demand or supply, then you can accelerate, these new flywheels. And so my hope is one day, or soon, if SF Compute needs extra like has excess capacity, they just hook it up to the grid and they get flooded with demand from us. And on the other side, if they have a ton of demand but they don't have supply, they just again hook up to the grid and it's a two-way protocol where they can just hook up to our capacity. And I don't think we're too far from that. Today our working implementation of it is mostly through a group of labs, universities, and a few sort of trusted parties who are, who all feel like they're in alignment to borrow an over sort of used word. But our hope is to just have it be an open protocol that anyone can hook up to on-Swyx [00:29:20]: Hook up for demand or hook up for supply? In primarily demand, it sounds like. Like you-Anjney [00:29:25]: No, bothSwyx [00:29:26]: You would want to offer demand.Anjney [00:29:27]: Both. Yeah. Unfortunately, what's happened in the last six weeks is, we thought we'd have a bunch of excess capacity by the end of this year. It's all gone.Swyx [00:29:37]: It's exploding.Anjney [00:29:38]: It, yeah. It's all gone. And so I have, my text messages are full of friends, we know many of these people, these are founders who've raised billions of dollars in San Francisco going, “Oh, any chance you have like 50 nodes in the next few weeks?”Swyx [00:29:51]: What is the scope for, non-Nvidia, right? You have Lisa Su coming and, Rainer Pope as well. And so There is a lot of demand for, more performance Alternative architectures and all that. At the same time, this hurts your standardization.Anjney [00:30:11]: I don't think so. So actually Rainer's a great example, right? Rainer is a CEO and founder of, MatX. I actually had him by for office hours in the class earlier today, and there was an insight he brought up that I hadn't considered before, which is when they decided to pick the standard For their data center, they picked the NVIDIA reference architecture. So the MatX chips Just plug in to any site that has an NVIDIA bring up planned. And, the-Swyx [00:30:42]: It's just software then. It's, it's not the-Anjney [00:30:44]: A-Swyx [00:30:44]: Hardware.Anjney [00:30:46]: Well, from an input and IO perspective It's the same footprint as an NVIDIA rack.Swyx [00:30:52]: That makes sense.Anjney [00:30:53]: Where they have done, innovated a bunch from what I can tell is on systems co-design. Which is where a lot of the gains are to be had. And so he picked He was “Anjney, we, there's just so much work to do when you're building a new chip company.”Swyx [00:31:08]: Can't fight every front.Anjney [00:31:08]: You just can't fight on every front. So my question to him was, “Well, you're working on this new chip. Their tape-out is next year. What, who are you going to partner with to host the chips?” And he said, “Whoever will host them. That's just not, that's not my focus.” And I said, “But how did you “ you decided back to our earlier systems design question, he decided that, he didn't want to be a full, fully integrated chip provider. The bottleneck they're focused on is the logic die, and they, he feels they can crank out a ton of performance gains through co-design there. But then that means you delegate, to our question earlier, it, you he's the data center provider is a different part of the stack, and so then he's dependent on that part of the ecosystem to host his chips to get the performance gains to the customer. So now you have another abstraction, and you might have loss. So I asked him, “How do you prevent loss?” And back to your point, he said, “I just picked the NVIDIA standard ‘cause I didn't want to Like I wanted to piggyback off of an existing protocol.” And that, what's great about NVIDIA is that reference architecture is known.Swyx [00:32:15]: Open.Anjney [00:32:15]: It's open. They've published it. So Jensen's actually enabled someone like Rainer to build a chip company like MatX, and I don't see them as competitive. The compute demand is so high. Like, I don't I think NVIDIA's not able to meet the demands of production, so we just need more chips. And I think it's very smart what MatX has done, which is say, “We're just going to we're not going to innovate on the data center design ‘cause actually, thank you, Jensen, you've done all the hard work. Where we can innovate is somewhere else.” And I think that's, that's very healthy. I think that's how we unblock new bottlenecks. And my view is these, the, chip teams like MatX, who have arrived at the insight that co-design is the way, The primary bottleneck for them is trust boundary. To do co-design well, you need visibility into the next model generation as soon as possible ‘cause it takes two years to tape out. So if by the time I bring my chip to market, your model architecture's changed, I'm host. Now, when he was inside Google, he was sitting next to the Gemini team. He was on Palm or whatever.Trust Boundaries, Co-Design, and Researcher CEOsSwyx [00:33:19]: His co-founder was the, was one, was one of the Palm guys, I think.Anjney [00:33:23]: Yes. Yes, exactly. So when you're inside the trust boundary of Google, then your systems co-design loop is super tight. When you leave as a founder, one of the biggest risks you take is now you're outside the trust boundary. And so what I love doing is helping chip teams who can help us unlock more capacity for the independent ecosystem access to trust. Because when I If I've been, involved with a lab from day one, and I was lucky enough to work with Anthropic, and then I'm on the board of Mistral and helped Black Forest Labs get started. I think at this point I'm on six or seven different teams.Swyx [00:33:57]: Only six? I feel like my mental number was going to be 13, but yeah, it's-Anjney [00:34:02]: No, I go deep with one at a time.Swyx [00:34:04]: You're founding CEO of Arena.Anjney [00:34:07]: Nah, that was an, that was an-Swyx [00:34:08]: Administrative CEOAnjney [00:34:09]: It was an administrative five-month gig where Whalen and Anastasios were graduating from their PhDs, and they didn't need a product team. So I helped recruit the head of engineering product and design. But Anastasios has always been the CEO of that company. I played a pinch-hitting I'm an intern. I was CEO intern For five months. -Swyx [00:34:33]: I interviewed him, and he's he's very well-spoken. I think he's a debate, former debate, champion. But also very quantitative and mathematical, which is-Anjney [00:34:41]: He-Swyx [00:34:41]: Such a unicorn.Anjney [00:34:43]: See, what's amazing about him? If you look at his output, he's an output maxer. By the time he was graduating from his PhD, which he only graduated last year, he had published more work with a citation count than, people twice his age. But at the same time, he'd already started a project called LLM Arena that was being used by millions of people As a side project. And time and time again, what I've realized is venture capitalists suck at seeing human beings as, dynamic agents where-Swyx [00:35:14]: They want to put you in a boxAnjney [00:35:15]: They want to put you in a box.Swyx [00:35:15]: This is your thing.Anjney [00:35:16]: So the first time I got introduced to Anastasios, somebody had told me “Oh, he's amazing, but he's a researcher.” I was “what? What do you mean he's a researcher?” That's what-Swyx [00:35:28]: Like he's not a CEO, not a founder.Anjney [00:35:29]: Not a CEO, exactly. I was “Are you crazy? Do you Have you met Dario?” Dario's a scientist. He's gone from zero to, what will soon be a trillion-dollar company in four years. Being a CEO, nominally speaking, is not that hard. Being a good CEO is hard. Being a great CEO actually requires a level of performance that scientists who have already published at the top of their field have accomplished. It is super hard to be a competitive scientist. To publish in academia over the last 20, 30 years, to make it to the top of your discipline at a place like Berkeley, you are a star athlete. Like, you are an athlete of the mind, and you perform at the highest levels. And to get there, whether you're, Anastasios or Whalen at Berkeley, or you are Robin, who-Swyx [00:36:23]: BFL, yeahAnjney [00:36:24]: With Black Forest, who created Stable Diffusion, or if you're, like Guillaume at Meta, who created Llama before he started Mistral. The amount of human leadership you have to demonstrate to get the resources, like get the trust of the organization, publish it, put it up. I would just fund researchers all day Right? If who have contributed already to the field. If they've, if they've put SOTA out there, they're, they're star athletes already. If they haven't done SOTA Look, they can still be good CEOs, but then I find the failure mode is that they just don't want to be CEOs, they primarily want to publish, and that's okay, too. One of the things we do with the AMP Grid is we donate excess compute. We have two nonprofits, like university labs. We carved out like a couple thousand H100s. But I do think there's extraordinary research being done on university campuses. My father-in-law's a physicist. He's a professor. Extraordinary work in physics, and we need that. But if you want to be a CEO, what you need to be willing To do is be super confrontational, outside of science. Like within the scientific community, some of the best researchers are very confrontational about their convictions, right? This architecture is right. To be a great CEO, you basically have to be willing to be confrontational up and down the stack.Swyx [00:37:41]: To your own team.Anjney [00:37:42]: To your own team-Swyx [00:37:43]: To customersAnjney [00:37:43]: Hiring, recruiting customers. Well, I would say, Yeah, pretty much to everyone Everybody. Of course-Swyx [00:37:50]: I see, I feel a little bit of that in my own work, but yeah, I can't imagine the stakes that Dario has had to go through. It's, it's pretty insane.Anjney [00:37:56]: No, I don't think the stakes are that different From how you're feeling it, right? Stakes are personal scaling vectors, right? The stakes that seem so low to you, like having this podcast where you can talk to somebody and just have a you're an extraordinary communicator, right? Like already in this conversation, you've pulled more out of me than most people, and I've been on 12 podcasts in the last two weeks.AI Coachella and First-Principles ThinkingSwyx [00:38:17]: I think I, we've just seen each other enough that there's some base trust.Anjney [00:38:20]: There's base trust.Swyx [00:38:20]: And I think, and I know that you, that I've done my homework and like I know that trust is a big deal for you, so.Anjney [00:38:27]: I think trust is about consistency, and you and I have seen each other In the community for years, right? Like, I remember the first time we met was at NeurIPS in New Orleans. I don't know if you remember that, luncheon.Swyx [00:38:38]: Oh my God.Anjney [00:38:39]: Reiko had set up this Reiko's amazing, and he set up this luncheon and-Swyx [00:38:43]: Yeah, I was “Who's this Discord guy?” I'm “Okay.” But-Anjney [00:38:45]: No, you weren't-Swyx [00:38:46]: You were just “You made some investments.”Anjney [00:38:47]: You were much less polite. You were “Who's this VC?” You're like-Swyx [00:38:51]: No, I Was I? Oh my God.Anjney [00:38:53]: It was-Swyx [00:38:53]: I'm so sorryAnjney [00:38:53]: It was visible on your face.Swyx [00:38:54]: I'm so sorry. But you weren't, you weren't The introduction was bad. I was I didn't know who you were.Anjney [00:39:00]: The, see, this is the thing about context, right? Like, but then I think I heard your accent. And I was “Are you-”Swyx [00:39:06]: Singapore, yeahAnjney [00:39:06]: “Are you Singaporean?” And you're “Yeah.” And I said, “I went to high school, JC, in Singapore.” And then the ice broke. But This is the there are in the scientific community, sometimes the stakes are very high for people who haven't had the emotional, what is called EQ Coaching and mentorship, right? Which is like to have scientific impact, you often need to be a extraordinary emotional, like emotionally in tune person with the folks you're trying to influence. And so what comes so naturally to you is actually a super high stakes thing to other people. And so I wouldn't assume that Dario's more stressed out than you. These things are you'd be surprised how similar and small sometimes the problems are to you That some of the world's biggest, leaders are facing. And that's what I've learned from this class. The guest speakers are Sam, Satya, Jensen.Swyx [00:40:01]: AI Coachella.Anjney [00:40:02]: Yeah. It's AI Coachella, right? So we got to get all the headliners, and they're I'm very lucky that some of these people have either mentored me over the years or I've done business with them. And when you, take the performative stuff out and any assumptions you may have about these people that you read in the press or on Twitter, We're all just humans. We're all trying to get along. And what's so special about this moment is AI is forcing, like scaling, the bitter lesson is forcing a lot of people to revise their assumptions for how the world works and go back to first principles or go and educate themselves. So the kind of people I was, I won't name who this person is, but I was at an event last week in Texas and, ran to somebody who said, “Anjney, I came across the class. What do you think about real time action prediction models?” And I was, don't know how happy it made me feel when they asked me that question. I know they've done the work. They've challenged themselves. I'm, they didn't ask me, “What do you think of world models?” They said, “What do you think of n-”Swyx [00:41:04]: Real time action predictionAnjney [00:41:05]: “action, real time action prediction models?” World models, don't get me wrong, are cool and everything, but you and I both know that is a layer of abstraction that is sometimes not usefully precise enough. Right? Ours-Swyx [00:41:16]: There's like four different kinds of world models.Anjney [00:41:17]: Yes, exactly.Swyx [00:41:18]: We've done the part with general intuition, by the way, which is very focused on, -Anjney [00:41:22]: Oh, cool. Yes. I love Pim. Pim is great. And this is what I love about people who've done that level of work. They realize they're not in competition with people who the rest of the world thinks they're in competition with.Swyx [00:41:34]: Because they're not in the category, they're in the specific thing they're trying to do.Anjney [00:41:37]: They're focused on their mission, and they have a systems understanding of the bottleneck they're trying to solve. And when somebody else says, “I'm working on real time, action prediction models too,” Pim goes, “Oh, I love that person. I want, I can learn from them.” But the minute they're “Oh, that person's a world model person,” it's “like which type of world model person?” But mostly they're just trying to figure out if it's a waste of their time, because we don't have enough time. So, Pim, for example, is super, loves this other company I work with we've talked about called Black Forest Labs. And he's mentioned to me multiple times that he's so, He thinks what Flux is doing is really cool. Andy Blattman came by and spoke in the class. And what I find over and over again is for people who do the work, who can be usefully precise enough about like what is actually going on in the world of frontier research, The sense of camaraderie is still well and alive, but it gets lost sometimes when you have to like abstract The technical complexities in, business terms And then the VCs are “How are you different from that world model?” I'm going to say Where do I even start to explain this stuff? And then the misalignment creeps in.Leading vs. Winning in Frontier AISwyx [00:42:43]: This is good. Yeah, I think, people listening get a sense of, what it is like to operate at a real level, like yourself, rather than at, the journalist level, where you have to sort of put everyone in, a rough category and create a narrative of competition, and who's winning today, who's behind.Anjney [00:42:58]: It-- this idea of winning is so Weird to me.Swyx [00:43:03]: You do want to win. You want you want competitiveness.Anjney [00:43:06]: No, I think you want to lead.Swyx [00:43:07]: You want SOTA.Anjney [00:43:07]: No, I think you want to lead. Yes, so you want to push the frontier. You want to push the SOTA. You want to do something that hasn't been done before. You want to capture value, but you don't want to capture so much value that, people think you're unaligned with your mission or trying to do what's best for the world. You want to capture enough value that you can keep innovating, right? And I think that people want to lead, they don't really This idea of winning and losing, again, I love Jensen. He's a, he's a leader. The mindset that he talked about on Dwarkesh's podcast, right? He's “I didn't wake up with a loser mindset.” I think that was awesome, right? Because he's, he's an engineer. Dwarkesh has done the work. So there's at least-- even though the, to me, it was very obvious they're talking about the same thing, they just passed each other. They just had to basically, Jensen has this, five-layer cake abstraction of how the industry works. And Dwarkesh had, I think from that podcast, had more of, a pre-training, mid-training, post-training systems loop concept.Swyx [00:44:04]: It's just a factor of who he talks to, right? Again, it's very clear.Anjney [00:44:06]: It's the systems It's the abstraction, the mental models, the It's the whole-- Dude, so much of the problem in the world is reasoning by analogy. And then the assumptions that are held invisibly.Swyx [00:44:19]: Yeah, I've, I've said, this is actually the best time in human history for first principles thinkers. Because everything you think will happen is actually now coming true.Anjney [00:44:28]: Correct. And the venture capital community is, notorious for this, where people look-- In times of uncertainty, they, cling to axioms that ended up being true from the previous era, and they kind of like proclaim them with confidence as if they're truths, but they're not. And it's very important to see the distinction between a heuristic and an axiom. An axiom can be proven-Swyx [00:44:55]: Like from internal consistency point of viewAnjney [00:44:56]: With internal consistency. A heuristic is a way you kind of a shortcut. And my God, the number of people I have had to put up with over the last few years who proclaim-- use heuristics As axioms to judge people, to judge which companies are going to succeed or the number of people who are “Oh, yeah, Anthropic, they're just training models right now,” but this one continue.Swyx [00:45:22]: Because that's a B2B SaaS?Anjney [00:45:23]: Yeah, the, like Which over the fullness of time, if you squint at it, maybe. But the way you arrive there is so important that you can-- you just, you can dismiss people. Here's what happened, right? What happened is Anthropic basically achieved takeoff in October of last year. That training run-Swyx [00:45:41]: Whatever, three seven?Anjney [00:45:42]: I forget the numbers now, but whatever that checkpoint was-Swyx [00:45:45]: We saw the cognition.Anjney [00:45:46]: Yeah. Right? You probably-- The, to those of us in the community, especially once post-training was done and it was released in December-Swyx [00:45:52]: Yeah. Can I sneak a sneaky question in there? I don't know if you have a perspective, maybe you don't, I just The number one question is how did Anthropic crack coding, right? Because Claude One, Claude Two, okay, like it was part of it, but it wasn't a big deal. And the leading hypothesis, it's a lucky dice roll that was then compounded, right? Like it was like Mildly better, but then they saw it and they were “Okay, let's really invest.”How Anthropic Cracked CodingAnjney [00:46:17]: I had this very annoying teacher. I went to this boarding school called Rishi Valley in India, which is like this, bird preserve. It's like three hundred and fifty acres of bird preserve in rural India, and there was no technology for seven years. There was this teacher, I won't name them, but they would have this-- I hated it every time he said this to me. He was “Luck fa-favors the prepared mind,” which is like a common saying, but the way he delivered it, always grated me, ‘cause he was always I was always one of those kids who got, a good grade without trying very hard. ‘Cause like high middle school is not that hard if you, if you're generally, paying attention and so on. And there was this one time where I-- But then I would get an eighty percent grade, and he would keep pushing me to say “The reason you didn't get the ninety-five plus percent is because you're not that lucky.” And I would say, “What do you mean?” ‘Cause I would think that I deserved that grade, and I would sometimes argue with him. And he'd say, “You didn't have a prepared mind. If you want to get lucky again “ There was basically one time where I got like ninety-five or ninety-six on this, on this subject, and I, now that I felt entitled. I was “Okay, I'm going to keep doing this,” and I didn't. And then he was “Luck favors a prepared mind. You got lucky last time, but you got to stay prepared.” And I didn't understand what he meant. Now, as I'm older, I'm okay, these adults actually knew a thing or two. Anthropic has been the most prepared company for four years. And so then when the right, context data comes in, the right developers start sending in, the right context diffs, Sure, you could say you got lucky, but if you ask me, they're pr-pretty damn prepared with paranoia for like four years. And you have to remember, it was so hard for them to get going early on that they had to do so much more with so much less that you just have to be prepared to be so efficient.Swyx [00:48:06]: Yes. There's numbers on their burn compared to OpenAI. I've, I've written about it, but they are so much more efficient in their, in their tech stack.Anjney [00:48:14]: It's not even It's not funny.Swyx [00:48:14]: Not even close.Anjney [00:48:15]: Yeah. But it's so clear, right? Like how to output max for the world. They have been prepared, and you could call that luck, but Luck favors the prepared mind.Culture, Hardship, and Anthropic's P0Swyx [00:48:25]: This is one of those things that I was going over some of your old lectures and, you were data, people think it's a moat and actually it's culture and actually it's team Actually. And I, it's-- there's different levels of moats, and this is the ultimate one that determines everything else. Which you can then compoundAnjney [00:48:43]: You're saying culture is the ultimate moat? Yeah. But the thing about culture is it's very fragile. So moats, I don't think they're-- there's very few moats I found that are actually moats. They're-- It's, it's a nice concept, but in reality, you have to replenish your culture. Ben Horowitz was, the speaker in CS153 on Tuesday, and I asked him this question about the culture bottleneck in teams because, there are several AI teams-Swyx [00:49:09]: His book, Hard Things About Hard ThingsAnjney [00:49:11]: Hard Thing About Hard Things. But more concretely, there are so many AI labs today that have all the cash they need, they have all the compute they need, and they're still not able to ship anything SOTA. And then you start seeing people leave and so on, and my diagnosis, it's, is it's the culture. And so I asked him, Ben, they're-- He's been one of the most aggressive investors in AI labs. He goes back to this thing which resonates in my mind a lot. It-- When I used to work at a16z, I would, book a conference room, and right outside the conference room, which is closest to the toilet ‘cause it was the fastest way for me to go use the bathroom between Zoom meetings-Swyx [00:49:45]: Oh my God, I'll put maxing my toilet optimization. Okay, never mind.Anjney [00:49:48]: It was not healthy in hindsight, but maybe this is TMI. But anyway, outside that conference on the wall was this quote that was printed that said, “Culture is not a set of beliefs, it's a set of actions.” And it's by Bushido, is this, Japanese philosopher. And if you stop taking the actions that demonstrate the mission alignment to what you've said to your team and to your-- the world matters to you, then your culture starts to fray. So it's not actually a moat, I would say. It's a very brittle, fragile thing that requires daily tending to like a garden. But if you figure out the system to keep that garden tended, which I think ultimately comes down to knowing yourself ‘cause you most naturally, if you're authentic and so on, you'll naturally make trade-offs that seem effortless to you, but that reinforce your culture. And then That becomes this very hard thing for other people to catch up to. And at Anthropic, from day one, there was this mission like-- missionary like zeal and belief that, hey, these capabilities will scale. These systems are stochastic, not deterministic. There will be error bars, and until we crack interpretability, there's risk. And at some point, people will go-- stop using Claude just for coding. They'll use it in some mission-critical context where there's-- it'll throw off a bug, and then people are going to come blame them, and they want to be on the right side of history where they said, “Yes, this is a powerful technology. We think it's going to change the world, And we want to be very measured and scientific about the fact that, ‘Hey, guys, these are stats models, statistical models.' That's how statistics works.” ultimately, when you're training neural nets, it is just a statistical system. And I think that Belief that safety is important and that it might seem toy-like in the early days, and sometimes, you could say, “Anjney, they totally over-exaggerated the risk,” like two years ago when they said, “Let's not launch Claude One,” or whatever. Well, okay, maybe in hindsight, but hindsight is twenty/twenty. And at the time, they didn't know how that model would be used, and to them it felt existential if somebody came and said, “You weren't responsible. It-- This wrote a bug.” The liability associated with that is massive. So how do you prevent against that? Well, day in, day out, you say safety. And when you start deviating from that, you have the team hold you accountable, you have the world hold you accountable, and I think that becomes a moat over time. At some point, that moat will get challenged and so on, and then it become fragile. I hope it endures because that's the beauty of having founders run the show, ‘cause they can make really hard trade-offs to do mission alignment. The hardest part is in the earliest days when you don't have a group of people who are going through difficulty, stress, crisis together, then your culture doesn't get defined sharply enough, and that's what I'm worried about right now, is there's so much money going to these labs. There's no hardship. There's no-Swyx [00:52:50]: To anyone who knowsAnjney [00:52:51]: There's no to anyone who knows. And that, in hindsight, was a feature, not a bug for Anthropic. The number of people who said no, the number of people who said, “Sorry, we're all doing investors in OpenAI,” that is competitive difference. It forces you to really understand, what is the hill you want to die on at the expense of everything else. What's the P zero? And there, P zero from day one was coding. The reason, the mechanism system there was if we crack coding, Then we will crack AGI. Our mission is AGI. We want to get there safely. If we focus on codin

In this episode, Nikola reveals his contrarian belief that AI can be better than humans at customer service (not instead of humans, they'll do very different work), why he spent two hours on the phone with Vodafone when he got their confirmation email with someone else's name on it (and why that's not really about AI or humans), why they built a "token leaderboard" internally to track which AI tools they're using most, why junior developers will definitely beat senior ones at learning these tools (plasticity just goes down as you age), how AI gives him superpowers as a CEO (a chief of staff reminding him he promised something 4 days ago), and why their business model is "Rolls Royce for large enterprises, BMW for everyone else." He also shares his journey from a Serbian family to the University of Cambridge, how his PhD supervisor convinced him not to do a PowerPoint job at McKinsey, and why he ended up founding a voice AI company instead of working in finance (he wanted to be "a proper monkey" as well as a PowerPoint monkey, in his words).What you'll learn:

Send us Fan MailWhat if building a million-dollar business no longer required a team, funding rounds, or even technical expertise? In this episode of Sidecar Sync, Mallory Mejias sits down with AI strategist and GenAIPI CEO Jon Cheney to explore how artificial intelligence is radically changing the economics of innovation. Jon shares the story of launching a company in a single weekend for just $400—and scaling it to $1M in six months—using a concept known as “vibe coding.” The conversation dives into what separates organizations that successfully adopt AI from those that stall, why execution matters more than ever, and how AI is unlocking entirely new forms of value creation beyond simple automation. If you've ever felt limited by budget, staff, or technical skills, this episode will challenge everything you thought was possible. 

Så tänker investerare när de kliver in i B2B SaaS-bolag – med Erik Syrén från Monterro Hur resonerar en investerare när de utvärderar ett B2B SaaS-bolag? Och vad händer egentligen efter att investeraren har gått in som ägare? I det här avsnittet av Sälj- och Marknadspodden pratar Anders Hermansson med Erik Syrén, tidigare entreprenör och vd på Lime Technologies och idag verksam på Monterro, där han bland annat sitter i investeringskommittén och är ordförande i flera portföljbolag. Samtalet handlar om vad som kännetecknar starka mjukvarubolag, varför nöjda kunder och låg churn är så centralt, hur ägarresan ser ut efter en investering och varför pengar sällan är den viktigaste produkten en investerare erbjuder. De pratar också om AI:s påverkan på SaaS-branschen, skillnaden mellan lättkopierade funktioner och verklig defensibility, samt varför affärskritisk mjukvara med hög stickiness fortfarande kan vara mycket starka bolag även i en AI-driven värld. Läs transkribering Anders Hermansson (00:06) Hej och hjärtligt välkomna till Sälj och marknadsbådde från Business Reflex. Jag heter Anders Hermansson. Tack för att lyssnar. Idag tar vi vi pratar om hur investerare resonerar när de tittar på bolag att investera i. Och vi pratar även om hur investerare agerar när de väl är inne i bolaget. Svaren på de här frågorna är såklart väldigt olika beroende på vilken typ av investerare man är. Och idag ska jag intervjua en av Sveriges tyngsta entreprenör inom B2B-planbara. Han sitter i en lång rad styrelser och arbetar idag på Montero där han sitter i deras investment board. Montero, för er som inte vet, är ett bolag som investerar i Scalapse, alltså ett bolag som har tagit sig en bit på sin resa men vill komma vidare därifrån. Personen i fråga heter Erik Syrén och han kommer inledningsvis att berätta om sin väldigt intressanta resa från studentrummet till framgångsrikt entreprenör och till investerare. Så häng med nu på en mycket intressant intervju om ur ägarperspektivet. Anders Hermansson (01:16) Erik Syrén, hjärtligt välkommen till Sälj marknadsbotten! Erik (01:20) Tackandes. Anders Hermansson (01:22) Grunt att ha det här jätteroligt med en sådan erfaren tungviktare inom SAS-branschen i podden. Erik (01:29) Vi får se om det blir något innehåll som är värt att lyssna på. Det håller vi tummarna för. Anders Hermansson (01:32) Ja, du är ödmjuk också. Han är Ödmuk också. Det är fantastiskt. Ja, vad roligt. Vi ska ju prata om, titta på det här lite grann ur investerarperspektivet idag och prata om kanske två aspekter. Dels hur det är bolag som du representerar när Montero, hur ni gör när ni tittar efter bolag som ni kan tänka er att in i och sedan även prata lite grann om hur ni agerar när ni väl har gått in i ett bolag. Erik (01:36) Och glimtar i ögat. Anders Hermansson (02:00) Men du har ju en rik och intressant historia inom det här gebitet. Kan inte du berätta lite grann om din resa och så fram till nu? Erik (02:10) Absolut. Så jag i slutet av 90-talet så pluggade jag i Lund och jag satt på ekonomihögskolan i Lund och så tittade ut genom fönstret och utanför dörrarna så hade vi Framtidsfabriken, hade Bord.com, vi hade Ericsson Mobile, vi hade Axis, vi hade Klick och så vidare. Så väldigt fina tech- och mjukvaruföretag och för mig som student Där och då kändes som att jag satt i huvudstaden i dotcom. Allt bara bubblar. fanns alla möjligheter. Medan jag kände själv att jag inte kollade egentligen på vad var på it och it bolag och jag kunde inte se skillnad på ett it konsultbolag eller mjukvaruföretag eller e-commerce bolag utan för mig var det bara en blandning av av det jag lärt mig efteråt är att det ingen annan som kunde det heller på slut 90 talet. De blandade ihop de här typen av bolag men men. Anders Hermansson (03:05) Nej. Erik (03:08) Då blev jag väldigt inspirerad och kände att det där vill jag hålla på med. Jag vill lära mig mer om tech och det kändes som att det hände någonting. En revolution som jag vill vara med på. Så när jag var klar med studierna så letade jag jobb på något litet mindre mjukföretag som jag kunde vara med och driva. Träffade på ett bolag som hette Lundalogik på den tiden. som utvecklar och säljer CRM-system hade de börjat fokusera mer och mer mot. Det var fem, sex stycken i Lund som drev det här företaget. Och tänkte väldigt mycket när de drev bolaget som ett litet mer traditionellt mjukvaruvare. Som ett traditionellt bolag med lönsam tillväxt. När vi har pengar så kan vi växa. Det passade väldigt bra med min småländska bakgrund. Den där typen av bolag känner igen. Anders Hermansson (04:04) Just bootstrapping. Erik (04:05) Ja, numera bootstrappingen. Så jag hoppade på det jobbet, började driva det där bolaget, blev delägare och drev detta med mina kompisar, kollegor, vänner. Och vi drev bolaget fram till 2008, då mina kollegor ville göra något annat i livet. De är lite äldre, så de kände att det kanske är värt att… att titta på en mer strukturerad process och kanske sälja bolaget. Så vi sålde 100 % av bolaget till Bisnode och ingick i ett konglomerat med över 4 000 anställda, en data provider, numera är det ju Danner Bradstreet. De köpte mjukvaruföretag för de kände att priset på data går ner. Det är inte värd så mycket att sälja personlig information, elektritinformation eller företagsinformation. Anders Hermansson (04:47) Ahoj! Erik (05:03) som de hade haft monopol på och varit väldigt starka på att kunna diktera priserna hela tiden. Men nu kände de att det blev mer och mer än… Ja, priserna gick ner och det blev mer än standardvara med uppgift. Så då ville de tänka om att om vi kan ta hand och hålla det i mjukvara inkluderat, då kan vi också skapa större värde för kunderna och därmed kan vi ta högre pris. Så det var tanken att man köpte lite mjukvaruföretag. Anders Hermansson (05:18) Mm. Erik (05:31) Men att vara ett snabbväxande mjukvaruförtag och komma in i ett konglomerat med massa olika bolag, olika varumärken, olika kulturer var helt fel för oss. Där och då ett entreprenörs drivet snabbväxande mjukvaruförtag. Så efter ett par tre år i den strukturen så landade jag tillsammans med management i Bisner och att det är bättre att gå skilda vägar. Så vi gick ut i en strukturerad process. Anders Hermansson (05:41) Mm. Erik (05:57) träffade vi kanske 30 olika private equity bolag, investerare i mjukvaruföretag. Där och då var min känsla när jag sprang runt mellan de här bolagen att jag fick utbilda dem, mer eller mindre, hur det är att riva ett mjukvaruföretag. Och framför allt hur det är att konkurrera med Salesforce och Microsoft som var de stora giganterna på serien marknaden. Och hur man kan, trots att de är stora, globala, så kan man hitta Anders Hermansson (06:15) Mm. Erik (06:26) vatikaler, nischer lokalt där man kan bli marknadsledare och man kan marknaden så pass stor som man kan bli ett stort bolag ändå. Och man kan hitta nya sätt att positionera och differentiera sig. Alla såg bara risker med att konkurrera med de här stora aktörerna. Efter några månader in i den här processen så träffade jag en helt ny spelare på marknaden som heter Montero. Tre stycken. Anders Hermansson (06:35) Mm. Erik (06:54) killar, två stycken med liknande bakgrund som mig som operatörer som har drivit mjukvaruföretag själva och en kille som kommer från Cobrids Finance och Bankvärlden. Och redan i första mötet så hittar vi väldigt väldigt väl. Istället för att prata risken med att konkurrera med Salesforce Microsoft så pratar vi möjligheten att konkurrera och hur vi kunde ta en helt unik position på en lokal marknad. Anders Hermansson (07:03) Mm. Erik (07:23) Så känslan hos mig var ju att vi byggde upp. Vi började diskutera strategier och affärsplanen i första mötet. Och efter mötet så landade vi i att vi gör management buyout tillsammans med Montero. Vi landade där att vi köper bolaget tillsammans. Som hette då Lime Technologies. Efter ett halvår in i den processen så satt jag och Peter, min ordförande, och satt och diskuterade. Anders Hermansson (07:36) Mmm, okej. Erik (07:52) Både högt och lågt. Efter ett och tre landar vi in i hur ett framtida ägande av Lime, hur skulle det kunna se ut? Vad hade varit en bra ägare efter Montero? Och där och då kände jag att jag hade ägt bolaget med mina kollegor, mina partners. Jag hade ingått i ett konglomerat med 4 000 anställda och jag var PE-ägt där och då. För mig fanns det en sak kvar att jag hade velat pröva och det var att notera bolaget. Så då sa vi att låt oss driva ett projekt och en tanke mot att en dag ska vi kunna först notera Lime. Hur skulle bolaget se ut då? Då kan man ju tänka att det är mycket med IFRS och rapportering och policies och sådana saker. Det vi pratade om var mycket mer hur bolaget vilken karaktär på bolaget ska ha vilka marknader ska vi vara på hur mycket recurring revenue hur mycket mycket revenue ska vara utomlands vilka marknader ska vi vara på i så fall hur ska management se ut vilken funktionalitet måste vi ha i produkten vad kan vi göra organiskt vad kan vi göra inorganiskt och sen la vi på rapportering och policies på det och vi jobbade med det ifrån 2014 Anders Hermansson (09:15) Öster. Erik (09:20) fram till 2018 i december. Anders Hermansson (09:23) Vad var drivkraften att notera bolaget? Erik (09:29) Dels så det ju så att om du har en ägare som är private equity så ingår det i spelet att de köper, de utvecklar och de säljer. för en private equity aktör så är det ju att deras syfte är ju att skapa returns till sina investerare. Och gör man driver man ett bolag med en ägarstruktur med majoritetsägare som är PE så kommer du vara till salu. Någon gång när det är en bra avkastning för investerarna. Så syftet var egentligen att skapa att vi behöver göra en ägarförändring och montera och ville sälja. är stora syftet och det stora syfte för min sida var ju att då kan jag gå upp som huvudägare i bolaget. Jag kan fortsätta jag på att sälja någonting. Jag kan fortsätta vara ägare i bolaget i en noterad miljö. Anders Hermansson (10:14) Ja, och tack. Erik (10:27) Och våra anställda kan vara ägare så vi kan äga bolaget tillsammans. Och sen tyckte jag också att fin tanke att då kan vi bygga en Evergreen som kan verka länge länge länge. För det är väldigt stor och viktig del i mitt liv, Lime. Och det vi har byggt tillsammans är det företaget. Så vi gjorde noteringen 2018. Anders Hermansson (10:32) Mm. Mm. Jag fattar. Erik (10:54) Den 6 december och om man vill titta tillbaka på den tiden så var det lite turbulent på aktiemarknaden även då. Under andra halvåret var det lite räntorop marknaden och den dagen vi noterade var den sämsta dagen på Stockholmsbösen det året. Så då fick man ju lite vänta vad vi gjort. Hela Asien föll när vi gick upp och ringde klockan. Sen så blev det väldigt väldigt bra. Hela noteringen och Anders Hermansson (11:10) ⁓ okej. Nej. Erik (11:24) 2019 och sen kom 2020 pandemin. Det har hänt mycket under de här åren men noteringen blev väldigt bra. Det ingick också i planen att när jag var klar med det operativa på Lime så skulle jag joinna Montero. Det hade vi i P1 och jag pratat om länge. Jag hade varit med som rådgivare, investerare och har varit med som bolgplank till många av våra Montero-investeringar vi gjort genom åren. Anders Hermansson (11:30) Alla kan. Erik (11:54) Så jag tyckte det var väldigt spännande att det skulle kunna vara en möjlighet för mig på nästa steg. Sen så kom ju pandemin. Min långväga kollega Nils Olsson som var försäljningschef väldigt länge på Lime, också vice vd och CEO på Lime. Han börjar bli mogen för att ta över. Så när vi såg ljuset tundan efter pandemin 2021 så lämnade jag över staffettpinnen till Nils. och hoppade på Montero fem och ett halvt år sedan ungefär. På Montero så är min roll att jag är ordförande i sex av våra bolag. Jag kan komma in på det vad det betyder men vi är väldigt mycket hands on. Vi jobbar väldigt nära våra management team och våra ledningsgrupper. Så det är min huvudsakliga uppgift. Sen sitter jag på investeringskommittén. Där vi går igenom alla kris och alla investeringar vi gör och vilka bolag vi investerar i. Och sen sitter jag vår styrelse. Så det är min roll på mot här. Anders Hermansson (13:02) Vad saknar du mest från vd-rollen? Erik (13:09) Mm? Dels saknar jag fokuset att vara delaktig i någonting där man känner att man kan bli mätbar varje dag. Det vill säga att blir lite svart, alltså ett och nolla, blir lite svart och vitt. Det vill säga att när man gör affärer går bra, man rekryterar lite folk, man känner att man har releasat några funktioner som varit bra och uppskattade av våra kunder. Anders Hermansson (13:23) Mm. Erik (13:39) Man har skapat ett kundvärde och nöjda användare ute hos på marknaden. Då får man rätt god feeling och en sån här feedback som man bara känner. Det här funkar. Det är bäst. Den är väldigt direkt och å andra sidan så är den ju också lika tung när man tappar en medarbetare som slutar hos dig eller du tappar en affär. Då är vi inte världens bästa CRM-system längre. Vi är inte världens bästa arbetsgivare längre och då mår du lite dåligt. Det blir lite en kris. Anders Hermansson (13:49) Den är direkt. Erik (14:09) Så då kommer du dina dippa också. Men just den där att vara företagsledare, levande med ditt bolag och entreprenör hela tiden. Du blir lite manu-depressiv brukar jag säga. Det går lite upp och ner. Alla duktiga entreprenörer har varit psykolog på något sätt. Eller någon gång. Ibland ligger man under skrivbordet och gråter lite grann och tänker nu gick det åt helsike. Och det kan jag sakna. Anders Hermansson (14:11) Tack Just det. Mm, exakt. Jag med. Exakt. Erik (14:38) Jag saknar de här kickarna när det går jäkligt bra och när man känner att man levererar högt kundvärde och medarbetarna utvecklas eller när man gör en stor affär. Samtidigt kan jag sakna de här dipparna när man bara känner att det gick åt helsike. Det har jag på Montero också för vi driver i vår låda vårt företag. Men vi är så många fler. Anders Hermansson (14:48) Pista. Så man får ta tag i det igen. Mm. Erik (15:05) som delar på den där manor depressiva. har 30, 33, 34 bolag idag som vi är majoritetsägare i. Vi gör mycket add-on förvärv, alltså tilläggsförvärv till våra bolag. Jag har sex, jag är ordförande i. Jag har väl en tre till som jag sitter i styrelsen i. När man ringer runt och tar mina fredagsamtal med alla bolagen. Det är alltid något som går bra, något som går dåligt. Man kan glädjas. Så det jämnar ute lite mer. Så jag får inte likt. Anders Hermansson (15:35) Just det. Men det kanske är lite mer som att på styrelsenivå är det mer som ett sju-punktsmedel än att vara en direkt siffra på varje. Erik (15:45) Ja, men så är det. Så det finns lite för- nackdelar med de här två uppläggen, men jag har kul på jobbet. Det är det viktiga. Anders Hermansson (15:47) Lite smodare kurva på något sätt. Ja, det är väldigt viktigt. väldigt viktigt. Ja, men grymt. Vi kanske skulle komma in lite grann på det här med då kopplat till Investeringskommittén och det här. Hur tittar ni på saker? Och jag måste säga, alltså det är ju nästan fånigt, men det finns väl… Vi har ju faktiskt lyckats prata nu i några minuter utan att nämna AI, men nu kommer det liksom. Det här med att titta på bolag och deras förmåga att skapa värde och sådana saker. Hur gör Montero och du och ni när ni tittar på bolag och också ur perspektivet om det har påverkat ert perspektiv över huvud taget med AI? Erik (16:34) Det enkla svaret är absolut. Vi lever med det här och känner både lugnet och stressen varje dag. Vi insåg väldigt snabbt att det här är en extremt stor möjlighet för våra portföljbolag. Många av de här sakerna vi sitter och kämpar med, att man sitter med en tech… Anders Hermansson (16:37) Ja, eller hur? Erik (17:00) skuld i man sett i produkten eller man behöver migrera en kundbas och behöver lägga in en produkt i harves mode eller man behöver utveckla ny funktionalitet. Länge har ju utvecklingsordning inom bit by software varit en flaskhals. Vi har ju haft långa roadmaps där det har varit diskussioner hur vi ska prioritera roadmapen. Där vi har kommit till ett läge där vi kan åstadkomma väldigt mycket. Mycket mer effektivt och öka produktiviteten i våra utvecklingsavdelningar. Och då gäller det att fånga de här möjligheterna. Fånga den här förändringen. nu kommer vi tillbaka igen till 90-talet här. Det är nästan som jag känner att jag kommer tillbaka till. Då kom eran i slut 90-talet med internet. och alla möjligheter som uppstår med mjukvara, internet och att alla fick en PC på skrivbordet. Och samma känsla har jag här och nu att vi är i en sån stor omställning och jag befinner mig mitt i den omställningen tillsammans med mina bolag. Och stressen är ju att alla bolag Anders Hermansson (18:11) Mm. Hmm. Erik (18:28) måste känna vilka möjligheter som finns här ute och ta vara på den. Samtidigt kan jag inte säga till dem vad best practice är. För vad har hänt sedan november, december med Claude och Claude Cowork till exempel. Alltså det har ju hänt extremt mycket och när det är optimalt Anders Hermansson (18:38) Nej, nej, exter. Erik (18:53) Hur ska jag bygga mitt utvecklingsteam? Hur ska jag jobba inom product management? Hur ska jag jobba med QA inom inom inom inom R &D? Hur ska jag jobba med releaserna och övriga avdelningar? Marketing, sälj, customer support, etc. etc. Så det här förändrar ju hela sättet hur vi driver våra bolag och det skapar sådana möjligheter. Och så var det ju alla de här transformeringarna jag varit inne i. Anders Hermansson (19:08) Exakt. Mm. Erik (19:22) mobil, internet och så vidare så har det alltid uppstått nya möjligheter för nya aktörer. Så det kommer ju att dyka upp nya spelare på marknaden som kan wipe code, kan göra någonting väldigt väldigt snabbt. Det är en enorm möjlighet för nya entreprenörer, för våra barn och ungdomar att driva bolag. De kan ju ta fram en produkt såhär snabbt, alltså mjukvaran i produkten. Anders Hermansson (19:30) Mm. Jag har faktiskt, jag har senaste tre veckorna så har byggt en SaaS-plattform själv. Den tog 30 år att bygga, konstaterar jag. För det är 30 år, 29 år och 11 månaders erfarenheter som på en månad nu är en SaaS-plattform för hela go-to-market-processen inom B2B. Erik (20:06) Du ser där vilka möjligheter nu och jag menar det är också intressant. är ju att precis där du sa 29 30 års erfarenhet domain expertis alla de saker för ofta får man höra här. Vi kodade över konkurrenten då som kommer upp som nytt. Ja men då kanske de kan konkurrera ut Lime eller Pythagoras eller Planema eller Pir. Jo men det man inte får glömma bort är ju att många av här bolagen har levt i 20 år 30 år. Anders Hermansson (20:18) Mm. Erik (20:36) Det är inte bara kod de har genererat. kanske är 20 procent av personalkosten är kod. Det andra handlar ju väldigt mycket om integration, nätverk, att vara compliant, supporten, implementation, domänexpertis. Allt det där är 80-90 procent av övriga erbjudandet som gör att du differentierar dig. Och då gäller det ju att dra nytta av möjligheten att kan göra med kod, att generera bra Anders Hermansson (20:38) Det ses. Erik (21:05) mjukvara och kombinerar det med övriga produkter dutehandhållen. Så i alla de här förändringarna kommer det uppstå nya nya aktörer. Det kommer vara existerande som inte hoppar på tåget som inte förstår förändringen som inte orkar med att göra förändringen som kommer bli utkonkurrerade och det kommer vara en rad befintliga som fattar möjligheten och kommer bli mycket mycket större i morgon. Tack vare AI och de möjligheterna som dyker upp. Och min stress och möjlighet är ju att hjälpa de här bolagen att göra transformationen. Att bli mjukvaruföretag som drar nytta av AI som verktyg och i sina produkter. Det svåra i det här är ju att veta exakt hur ska en utvecklingsavdelning se ut? Hur är den optimal? Vi har inga best practice. Det enda vi gett är att vi måste anamma förändringen. Vi måste vara på de här sakerna. Vi måste utveckla de första funktionerna. Jag kanske inte vet hur ett gränsligt AI-gränssnitt ska se ut optimalt i mjukvaran. Det kanske är så att det ska vara en chat där man chatta och en agent gör saker och ting i mjukvaran. Eller så kan det vara en kombination av det gamla gränssnittet eller något helt nytt. Det enda jag vet är att vi måste vara på det här och om vi gör det så lär vi oss väldigt mycket av våra portföljbolag. Vi träffar ju extremt mycket bit och software bolag. Samtidigt så kan vi ta med oss den erfarenheten in i nya bolag hela tiden. Så det finns väldigt få aktörer som i och att vi fokuserar på bit och software så bygger vi upp mycket erfarenhet kunskap och vi bygger upp en best practice över tid. Om vi bara är på den förändringen. Anders Hermansson (22:53) Och höjst är. Hur är det med bolagen i Köfir? Jag har varit med i många, dels själv i vissa startups men också delaktigt som en marknadspartner till startups. Då har alltid varit att vd måste lägga mycket energi på att leta pengar. och ringer vd-arna runt med hjälp av kassinstytet så att de andas och leta pengar. Står folk i kö utanför Montero och knackar på vill komma eller hur funkar det? Scoutar ni efter bolag på något sätt eller hur ser det ut just nu? Erik (23:33) Man önskar ju det var en kö utanför med de finaste bolagen som står här utanför och säger kom igen hjälp oss. Men men faktum är att vi har blivit större och större och vi har ett ganska bra brand i Norden. Hur har det kommit sig då? Jo men det är ju att vi har långvariga. Vi har vatt på den här marknaden sedan 2012. Anders Hermansson (23:39) Ha Erik (24:03) Det vi gör är väldigt mycket likt ett mjukvaruföretag. Vi är ute och gör olika event. Vi har det som kallas Nordic Software Summit i augusti, den 20 augusti, där vi samlar 1500 entreprenörer och C-level-nivåer i mjukvaruföretag inom B2B Software i en stor summit under en hel dag. Där vi nätverkar, Vi har bra presentatörer som kommer att presentera olika viktiga topics, till exempel AI eller pricing eller liknande ämnen. Och hela syftet är inte att de ska känna att vi säljer till dem, utan hela syftet är att bygga ett varumärke där vi är relevanta inom BTP-software. Sen gör vi på liknande sätt så sätter vi upp en turné, Nordic Software Tour, där vi åker runt i hela Norden. Anders Hermansson (24:51) Mm. Erik (24:58) ut till alla de lokala återna i Oslo, Stavanger, Trondheim, Nordra Finland, södra Danmark och så vidare för att träffa mjukvårdföretagen på sin hemmaplats eller hemmaarena. Vi gör poddar i det här forumet, väldigt viktigt för oss. Vi skriver mjukvårdförebycker, vi frukost och luncher för att hitta forum där vi kan visa vår erfarenhet och kunskap. Anders Hermansson (25:02) Mm. Erik (25:25) Vi kan ge vår erfarenhet kunskap till mjukfart företagen, även nystattade startups. För vi vet att lyckas dem så kommer de växa in i vår ICPA, i vår målgrupp. Våra sellitprocesser varar kanske två till fem år. Det vill säga vi ska träffas ett antal gånger både hos dig och hos oss för att lära känna varandra. Dela med oss av idéer och Anders Hermansson (25:36) Mm. Mm. Erik (25:54) problem vi har utbyta dem. Lite gå tillbaka till 2012 när jag träffade Peter Thomas första gången. I mötena ska vi diskutera strategi och affärsplan och bygga upp saker och ting tillsammans för att kvalificera varandra om vi vill göra någonting tillsammans. Det man kan säga är att många bolag när de träffar oss står inför inflection point där de där de känner att. Men vänta nu. Anders Hermansson (26:03) Mm. Mm. Mm. Erik (26:23) Jag saknar kunskapen att lägga till ett kontor eller gå in på en ny marknad eller hur ska jag göra här pricing projektet eller nu ska jag ta och flytta upp och skapa en ny produkt. Hur gör jag det när man står inför de där skifterna och man tycker att man saknar erfarenhet och kunskap. Det är ofta då vi kommer in och hjälper de här entreprenörerna hjälper management teamet med den erfarenheten och blir. Anders Hermansson (26:50) Okej, det är väldigt långt ifrån dumma pengar låter det som såklart. Erik (26:54) Vi egentligen så här, du behöver ha dumma pengar och behöver ha minoritetsägare där du vet exakt hur du ska driva ditt bolag. Då ska du inte gå med oss, ska du inte, då ska du inte, ska inte vi vara där. Ofta är inte ditt, bolagen vi investerar i är inte perfekta. Det finns inga perfekta bolag som vi investerar i utan ofta har de några stycken röda lampor och gula lampor så någon måste ha hjälp med. Men man kommer ofta tillbaka till att det vi vill ha och det vi söker det är Anders Hermansson (26:58) Mm. ⁓ Nej. Erik (27:24) Nöjda kunder, det är en väldigt bra grej. Och att churn rates är låga. Alla bolag som ligger på över 10 procent och inte riktigt satt den här product market fitten. De försöker vi nog undvika vanligtvis. Nummer två så är det också viktigt med produkterna. Att det är stabila, fina, bra produkter. Anders Hermansson (27:25) Just det. Mm. Erik (27:53) som har en tydlig differensering och då produkter pratar jag både mjukvara men så pratar jag också de andra sakerna runt omkring som differensierar företaget mot sina konkurrenter. Och sen så det tredje det är ju att det finns en kultur ett DNA i bolaget där man är värderingsstyret att vi kan stå för vad bolaget är. Och då kommer man ofta tillbaka till grunderna och entreprenörerna, vilka de är och vilken bakgrund de har och vilken filosofi de har. Och hur de driver bolag helt enkelt. Anders Hermansson (28:22) Mm. Ja, jag fattar. Det låter som att det kan man inte få reda på i pitchdäcket. Det är processen att lära känna varandra som säkerställer det. låter som att är väldigt annorlunda, en lång process som bygger på kvalitet och dialog istället. Erik (28:52) Ja, och tittar du på processen när vi lär känna ett bolag så är det väldigt mycket möten, olika event, olika mötesplatser. Det kan vara på event och kan vara webbinarie och det kan vara fysiska möten på vårt kontor och deras kontor för att lära känna varandra och hitta varandra. Så att absolut, och den ser ju väldigt likt ut. Anders Hermansson (28:57) Hmm. Mm. Erik (29:22) ett vanligt mjuk, alltså om du säljer enterprise mjukvara i en lång komplicerad process, då är det ungefär så. Och vi gör ju det här, vi är fullt medvetna om att entreprenörerna gör ju det här väldigt sällan. Så vårt jobb i den här är att hålla dem i handen och skapa tryggheten i att ja, men det här gör vi tillsammans. Vi hittar det här partnerskapet tillsammans. Och komma tillbaka till det, pengarna. Anders Hermansson (29:29) Mm. Just det. Erik (29:52) Nej, det är det. Det är inte vår produkt. Vår produkt är att vi sitter på massa erfarenheter och kunskap. Att vi har 35 andra bolag i ett nätverk som vi delar kunskapen och erfarenheter med mellan varandra hela tiden. Jag tänkte själv att du har… Ja, istället för att du sitter som CTO i ett bolag så kan du alltid ringa till 35 andra CTO’er och bolla din utmaning. Det är ju en enorm möjlighet. Anders Hermansson (30:17) Mm. Just det. Ja, verkligen. Annars kan man bli lite ensam. Jag fattar. Vad heter det? Behöver man vara lönsam också, Erik (30:29) Det måste man inte alltid vara. Det måste finnas en underliggande lönsamhet. Vanligtvis tittar vi på bolag som har hittat en product market fit. Vi investerar inte i startups utan vi investerar i det vi kallar scale-ups till tillväxtbolag. Om det ligger någonstans mellan 20-30 miljoner i återkommande intäkter upp till 400-500 miljoner i återkommande intäkter. Det är någonstans ett bolag vi investerar i. Och sen har vi då skapat en playbook eller en process eller en metod hur vi driver våra bolag under sju till åtta års tid som är ungefär genomsnittstiden som vi är ägare i våra bolag. Och då har vi lite olika faser och i de här olika faserna så finns det olika delkomponenter vi kan använda. Det kan vara så att du har behov av hjälp med pricing, rekrytering, gå till nymarknad, konvertera dina räkenskaper till IFRS eller ta fram en transfer pricing modell. Alla avdelningarna du har är ett mjukvaruföretag, support, sälj, finans, utveckling, AI. Så alla de specialistområdena har vi också på Montero. Och under de specialistområdena så har du delkomponenter som vi till hand och hålla som vi försöker standardisera. Så vi kan hela tiden plocka från den verktygslådan. så säger vi om okej, nu har vi problem med pricing. Då tar vi in de här två experterna som är duktiga på det och som kan hjälpa er att driva den typen av projekt. Om ni vill det. så, men det viktiga i alla de här i de här projekten är det att Anders Hermansson (32:14) Mm. Mm. Erik (32:21) att man har ägandeskapet, att ägandeskapet ligger hos bolagen. Det får aldrig bli att vi körlar eller att vi håller för mycket bolagen i handen, utan ägandeskapet måste alltid ligga i bolaget. Och det är alltid management som ansvarar för driften av företagen. Och sen blir det att… Anders Hermansson (32:38) För fråga, man tänker så här, de första 100 dagarna, finns det någon sådan liksom, vad händer? Erik (32:45) Vi kommer från en värld där vi säger att de första hundra dagarna måste vi tillsammans med bolaget lära känna varandra och tillsammans bygga upp budget eller vad heter det, affärsplan och strategi för att hitta det här. För bolaget sitter ju på DNA1, sitter ju på marknadskunskapen, de sitter på domänexpertisen, medan vi kommer ju med erfarenheten från från att driva BTP-software. Ibland så har vi lite domänexpertis men inom det området de är inom men framförallt så är det bolag som sitter på det unika där. Och det gäller ju att det smälter samman. Vår erfarenhet och bakgrund tillsammans med deras domänexpertis och bolagsexpertis är det som skapar det här unika. Vi kan ju ha hypoteser när vi köper ett bolag men det Ofta tar det några månader att lära sig och sätta alla de där blocken på plats. Nu är det så att vi träffar i bolagen så länge, alltså två till tre, fyra, fem år innan. Och vi har ju ett antal möter där vi sitter och diskuterar budget eller affärsplan och strategi. Vilket gör ju att ibland får vi lite snabbare stadt. Så vi kan påbörja det här förändringsarbetet redan. dag ett, dag två. Så det beror lite på hur situationen är och vilket bolag vi kommer in i. Likadant så är det så här att vissa bolag måste ha mycket mer action i. Det vill säga att där måste vi kanske göra management komplettering eller förändringar dag ett. Vi kanske måste rekrytera säljare, vi kanske måste bygga en marketingorganisation och då vet vi det. Och då är handlade tiden väldigt viktigt att Anders Hermansson (34:09) Jag fattar. Mm. Mm. Erik (34:37) att agera på det snabbt. andra bolag så kan ju bolagen vara mer mogna. Det kanske redan ha en organisation med 150 anställda och har kommit en bit på vägen. Då handlar det mycket mer om att justera och kanske mer fokusera på några stora grepp. Kanske göra &A eller gå till ny marknad. Så jag tycker det är viktigt att man anpassar sig efter de olika bolagens situation. Anders Hermansson (35:02) Hur ofta? Erik (35:07) Man läser de där, men vi har blivit, om man tittar på de senaste tiden så har blivit mycket mer metodiska även under de första 100 dagarna. Hur vi onbordar och skapar en struktur i bolaget för att kunna växa. Det vill säga att vi sätter många av de här grundinvesteringarna, det är ER, PSS, TIEM eller sätter olika managementfunktioner på plats. Sätter rapporteringen på plats. Ofta de där sakerna måste vi göra de första 100-200 dagarna. Anders Hermansson (35:07) Öster. Just det. Erik (35:38) så att vi kan gasa på skalningen sen med tillväxt. Anders Hermansson (35:41) Jag tänkte fråga lite om styrmodell och sånt där. Har ni en som ni då tycks ha så här? Nu gör vi så här. För det kan ju vara en chock för en vd, en entreprenör som har drivit sin egen låda och sen kommer man P.E. ägd och så smäller det till med rapportering och sånt på ett betydligt mer strukturerat sätt än man kanske gjort förut. Erik (36:02) Det jag lärde mig 2012 när jag ute i min första eller den strukturerade processen där jag träffade 30 olika private equity spelare. var att jag var en entreprenör som körde väldigt mycket på. Jag jobbade ju väldigt mycket i marknaden och bland mina medarbetare, mina kolleger och hade ju väldigt mycket anekdoter. Jag tog ju mycket på kundinformation och medarbetare information. Jag hade full koll på marknaden, men jag hade inte lika bra koll. Anders Hermansson (36:29) Mm. Erik (36:32) Jag var inte lika datadriven, intent. Jag var väldigt fokuserad på kassaflödet och förutom faktura och de där bitarna och det brukar vara så på entreprenörer. Jag hamnade i en dd-process med en private equity och då boomade jag en forecast mitt i det arbetet. Och där jag boomade en del saker jag hade sagt med på anekdotstadie och magkänsla. Och där och då på sommaren svod jag att jag inte skulle hamna i den situationen igen. Så då skapade jag det, jag gick tillbaka och jobbade med mina rådgivare vid den tidpunkten. Jag gjorde modeller, gjorde bottom-up-analyser och gjorde ett ordentligt modellarbete för att ta fram affärsplan. Och det jag landade i var ett fullständigt rapportpaket på alla avdelningar. Så jag blev datadriven. Och det jag lärde mig där och då, det var att… Att kombinera den här kundnärheten, medarbetarnärheten, marknadsnärheten ihop med datan. var det som skapade dynamiken. Det det som skapade margin. Och det är nödvändigt för att ta de här bolagen till nästa nivå. Och ibland kan det vara en liten chock när man kommer in med en rapportpaket och säger, men det här måste vi plocka fram. Det är viktigt att… Men de… Nästan alla säger tack, god gul, att vi gjorde det här. att vi satt den här CIFO på plats, att vi skapade den här styremodellen och vi blev datadrivna. För två år senare när det har jämförelsetalen, du kan verkligen bli datadriven, du kan fatta besluten tillsammans med marknadskunskapen. Det där skapar margin och det skapar en stort värde för de här tillväxtbolagen. Och du måste göra det. Om du ska gå från startup till en scale-up. Du måste ta det steget. Det är en tydlig inflection point. Anders Hermansson (38:32) Just det. Ja, jag fattar. Bra poäng där. Det är väl många som vill bli datadrivna men man behöver nog en extern påverkan för att orka ta steget. För man känner ju att man kanske har örat mot marken i sin egen verksamhet. Det inte riktigt det som prioriteras då. Hur mycket styr och mycket coachar ni? Jag fattar inte situationsdrivet men det måste väl finns någon… Erik (38:54) som brukar vara. Anders Hermansson (39:01) Någon filosofi sådär. Erik (39:04) Jo, men det är väldigt mycket coaching. Jag har ju samtal med alla mina vd-ar flera gånger i veckan, men jag ett strukturerat, inbokat samtal med alla där vi har en tydlig agenda där vi går igenom. Och då är det ju, då kan man tycka att det är väldigt operativa frågor i mångt och mycket vi diskuterar. Men det små bolag, det går inte att säga hur många procent jobbar strategiskt, hur många procent jobbar operativt. Det där blandas hela tiden upp och ner i de här två frågorna. För att kunna vara… Jag brukar säga att lång sikt byggs upp av väldigt många kortsikt. Du måste dela upp det där och leverera mot dina kopier eller datapunkter varje dag. Och ska du få till den här strategiska förändringen så måste du få det hända kortsiktiga. Så att det handlar ju väldigt mycket om att det är mycket coachande där vi bollar saker och ting. Jag hamnat i den här kunds situationen. Vad tycker du? Hur ska vi göra? Lite erfarenhet i kunskap i den. Vi funderar på den här typen av funktionalitet i våra produkter. Hade skapat det här värdet för våra kunder? Ska vi göra det organiskt, inorganiskt? Hur ska vi skapa den förändringen? Och ibland handlar det om som en vd. med det här manodepressivet jag pratade om tidigare. Och för mig som ordförande handlar det ju väldigt mycket om att vara psykologen ibland. Ibland ska jag ju pusha när de känner sig för bekväma och ibland ska jag lugna ner dem när de är stressade. Och hela tiden var den där personliga, anledning till coachen som de kan hålla i handen. Som sitter på erfarenhet och kunskap. Anders Hermansson (40:51) Hmm. Just det. Erik (40:58) Nej, men jag tycker nog att det är extremt mycket kortskning där vi driver ett bolag tillsammans. Den här vi känslan är ju det viktiga. har ju inga tjänstemän som driver våra bolag i management, utan de har instrument, de är delägare i våra bolag. Vi sitter i samma båt, så går det bra för bolaget, så går det bra för dem och det går bra för oss. båtprincipen är jätteviktig för oss att vi gör det här tillsammans. Anders Hermansson (41:05) Mm. Mm. Mm. Erik (41:28) En. Anders Hermansson (41:30) Det är en ganska stor grej ju. De entreprenörer som jag har kontakt med och sådär. Att ge upp majoriteten till någon annan. Hur tänker ni och pratar ni om det där med… Erik (41:46) Det som jag har respekt för, för det är ju ens baby som man har levt med och man har skapat över många många år. Det är inte helt enkelt att överge den frågan. Det som är viktigt i det tycker jag är just det här att det tar tid att vilja känna varandra. Att en sån här process är en kvalificering för båda parter. Anders Hermansson (42:01) Nåååå Erik (42:12) Därför är viktigt att vårt renomi, vårt varumärke ute på marknaden är extremt viktigt för att entreprenörer ska våga släppa in oss i företaget, att lämna nycklarna till oss att vara med och driva det här företaget. sen är det så här, det funkar inte så. Det inte så att en entreprenör lämnar nycklarna till oss, för då har vi nästan failat hela det här. Utan vill inte management och entreprenörer vara med och driva det här bolaget tillsammans. Anders Hermansson (42:24) Mm. Erik (42:41) Då är inte vi heller med, utan det här är väldigt, väldigt mycket ömsesidigt att vi gör någonting tillsammans. Vi driver bolaget i partnerskap tillsammans och därför är så viktigt med den här dynamiken tillsammans så att. Antiponörerna och management de sitter ju på det jag pratar om tidigare. sitter på erfarenheten, domäne, expertisen, kundkontakten, medarbetarna. Allt det som är värdet i bolaget sitter de ju på. Sen. Anledningen till att vi måste ha majoritet är ju framför allt för att vi vill ha en koncentrerad, vi kan inte äga 150 bolag i vår portfölj. För vi har inte en organisation för att hantera det. Jag kan hantera sex bolag som ordförande, jag kan inte hantera fler. Vilket innebär att jag måste ha fler, eller vi måste ha fler liknande profiler som mig hela tiden. Så köper vi två bolag till så måste vi ha en som kan hantera de här två bolagen. På det sättet är inte vår modell särskilt skalbar. Det vill säga att vi måste anställa människor som bygger på det här. Bygger det här företaget. Och det som händer då, det är just den här dynamiken att de sitter på extremt mycket makt trots att de är minoritetsägare. Så det optimala vi söker är att vi äger någonstans mellan 55 till 80 procent. Anders Hermansson (43:50) Mm. Erik (44:09) Och så sitter management och entreprenörerna kvar med stor del. Det viktiga i det är ju att som jag pratade om båtprincipen, men ofta är ju exiten i nästa steg när vi säljer bolaget. När vi har tagit bolaget till 3, 4, 500 miljoner och vi vet hur man säljer ett bolag av den size till. Och vi har byggt upp ett nätverk med massa olika private equity spelare, strategiska köpare. Anders Hermansson (44:28) Mm. Erik (44:39) så knackar på dörren och tittar på våra bolag hela tiden. Vi tror oss veta att vi kan få bättre betalt för den typen av bolag än många andra. Så det är ju ett värde vi också levererar till våra entreprenörer och våra management team. Att man krokar arm och gör en resa tillsammans. Exiten i steg nummer två är minst lika viktig som exiten i steg nummer ett. Och vill man, man… Anders Hermansson (44:50) Mm. Jästän. Mm. Ja. Erik (45:07) Det viktiga är att man lär känna varandra över tiden. Anders Hermansson (45:10) Jag fattar. Om man nu är entreprenör och har sitt bolag och som du säger, hittade lite olika triggersteg inflection points där man började ta ett lite större, så att säga, okänt steg som en tydlig signal på att det kan vara smart att utvärdera i alla fall någon som Montero. Men vad skulle du säga? Vad skulle du ge för tips till en entreprenörer som då kanske äger mycket stor del av sin bolag tillsammans med övrigt management när de börjar tänka på det här med att ta in externa ägare. Erik (45:50) Till att börja med så ska du inte ens innan du börjar tänka tanken så tror jag du ska ändå kanske ta lite luncher och vara på din del event och lära känna lite av de här potentiella köparna som du tänker det hade kunnat vara en bra partner för lite. Kommer tillbaka till det jag sa. Det är en kvalificering för båda parter. Det inte så att du får göra det sex månader innan eller tolv månader innan utan du kan ha en dialog med många. Anders Hermansson (46:08) Mm. Erik (46:20) av oss, även mina kollegor i branschen, två, tre, fyra år och ta lite tips och råd på vägen. det är lite vår grej helt enkelt. Vi delar gärna med oss vår erfarenhet och kunskap för då får man testa lite det här, vilket värde vi levererar, vilket värde vi kan skapa för ditt bolag. Så det är det ena att vara lite mer långsiktig och kvalificera. Sen så tror jag att Anders Hermansson (46:27) Mm. Mm. Erik (46:50) Det låter kanske enkelt att men jag tror att kvalificera vad är det för någonting de kan leverera förutom pengar. För pengar är ganska lätt att få om du har ett fint bolag och det är lätt att lockas av vem som sätter högst prislapp på företaget. Men ofta är ju bolaget mer viktigt än så. Det vill säga Anders Hermansson (47:05) Mm. Ja, ja. Erik (47:20) Vad vill du att bolaget ska ta vägen? Vad vill du att medarbetarna ska ta vägen? Hur vill du att det ska utvecklas? Vill du vara med på resan framåt? Och hur kommer då bolagets andra exit eller hur ska bolaget utvecklas och ta vägen? Att bygga upp den planen tillsammans med en potentiell investerare. Det tror jag är en smart grej att göra. Anders Hermansson (47:35) Mm, jävlar. Just det, så att man inte ser Montero, vad heter det, intåget som ett slutstation, så att säga, utan det är ett steg på vägen någonstans. Erik (47:58) Exakt. Och att värderingarna mellan dig och en potentiell investerare är de är hyfsat likvärdiga och att ni kan funka bra tillsammans. Sen tror jag att ett misstag jag ser väldigt många är att de raisar pengar lite löpande, de tar in lite affärsänglar och så tar du in en affärsängel som köper 5 procent och så tar du in en som köper 7 procent och en 10 procent. Anders Hermansson (48:12) Mm. Ja, exakt. Erik (48:26) Och så VIP så har du en cap table med 60 namn där det inte betyder någonting för dem. Du kanske har fortfarande kontrollen över bolaget. Du kanske har sålt 30 procent eller 40 procent. Men det enda du måste göra är att hantera en massa aktieägavtal och du måste hantera en massa olika affärsänglar. Ska du göra det? Försök göra den här ägarlistan så kort som möjligt och göra det rejält. Det är också någonting jag tror på. Anders Hermansson (48:32) Ja precis. Mm. Mm. Erik (48:56) Återigen, gå inte bara på pengarna eller värderingen utan gå på det långsiktiga. Det kommer att vara värdeskapande för företaget över tid. Anders Hermansson (49:01) Mm. Det är jäkla bra avslutning men jag måste få ta ett varv till runt AI-grejen här. Det finns ju dom som säger att AI då är liksom… vad kallar man för? Sa… Sa… Sa… Gaddon eller någonting. liksom hela… Nej nej, varför ska vi hålla på köra på appar? Jag kan ju som vanlig användare bara promta fram det jag själv vill ha, att säga. Erik (49:17) Mm, stämmer. Anders Hermansson (49:26) Hur ser ni på… Vi pratade mycket om AI. När vi pratade tidigare så är AI en stor möjlighet i form av produktivitetsökning som är helt galen. Jag har ju pratat med andra mjukhårdbolag som säger att vi har slut på idéen nu. Den här product roadmapen åts upp i natt av mina 190 klådagenter som bara tuggar i sig den. Det är ena sidan av det. Fantastiskt. Med den följer ju… Då är en konkurrens situation när andra kan göra likadant om de har huvud på skraft. Men det här med liksom hur ser du att det påverkar möjligheterna för hela SAS-branschen vad det gäller att uppfinna värdeskapande bolag helt enkelt när så mycket av värdet numera inom olika områden kan pluppa ut ur chatgrippet till heliklod. Erik (50:19) Jag tror så här att man ska vara lite försiktig att klumpa B2B-software och SAS och sätta alla i en kamm. Det är väldigt stor skillnad mellan SAP och ett mjukfaderföretag som gör någon form av dashboard. Om man går tillbaka fem till tio år så var det ganska coolt att driva ett SAS-bolag som var Low Touch eller No Touch. Anders Hermansson (50:46) Mm. Erik (50:47) Du marknadsförande på webben, kunde betala mjukvaran med ett kreditkort och så bara drog du den. Och sen så en product led growth modell. Ja, tittar man lite på de bolagen idag som har kanske inte så affärskritiska. De kanske har lite svagt usage. De kanske inte har så många integrationspunkter. Stickiness är ganska lågt. jag pluggade i Lund, om vi går tillbaka till Lundatiden igen, så pratade man om bindningar. Tekniska bindningar, juridiska bindningar, sociala bindningar mellan företag. Antalet bindningar gör ju att man bygger stickiness. S och P, vi kan ta ett exempel med Lime egentligen. 2005 försökte jag sälja till Göteborgs energi. Anders Hermansson (51:26) Mm. Erik (51:41) Vi fick inte göra det. Vi omsatte 30 miljoner. Vi var för små och vi hade inte de processerna och policy som behövdes. 2012 försökte vi sälja till Göteborgsenergi igen. Det gick inte. Vi omsatte 100 miljoner. Vi hade inte isosatveringar eller liknande ITIL-processer på plats. 2026, för ett par månader sen, sålde vi till Göteborgsenergi. Nu omsätter vi över 800 miljoner, 550 anställda och har alla de där sakerna på plats. Att implementera Göteborgsenergi, att sälja till Göteborgsenergi tar flera år. Att implementera produkterna hos dem, alltså mjukvaran, kommer ta tolv månader kanske, 18 månader. Både Microsoft och Salesforce har gått bet på denna implementation, de misslyckats med denna implementation. Samma sak i ett energibolag nere i Tyskland. tar väldigt lång tid, är svåra implementationer, krävs mycket integrationer, mycket folk som är involverade. Och då det inte bara att ta data och migrera data eller att integrera, utan det handlar ju om en förändringsledning. få det här företaget att anamma ett förändringsarbetssätt, processer och rutiner. Och det är ju en jäkla skillnad på det företaget och den typen av produkter. Jämfört med Low Touch produkt. Så när vi sitter och tittar på investeringar och tittar på så försöker vi undvika den här typen av mjukvara som är mycket Low Touch, liten usage, hög könnivå som är lätt att kopiera och när de differenserar sig så pratar de om funktioner i produkten. Ja men funktioner i produkten har aldrig varit lättare att ersätta, att kopiera. Däremot Anders Hermansson (53:19) Mm. Mm. Hej då! Erik (53:37) att konkurrera med den andra delen om du har jobbat med enterprise och implementation, support, att du har andra saker som gör att du differentierar dig. De är ju mycket större mots, mycket större valggrava, mycket svårare att konkurrera mot. Så den typen av affärskritisk mjukvara med många antal bindningar och hög stickiness, den typen av bolag gillar vi. Anders Hermansson (53:51) Mm. Mm. Mm. Jastu. Erik (54:06) och som är affärskritiskt och hög användande i grad i bolagen. Anders Hermansson (54:10) Just det. Och där har man inte utsatt för att bli satt Erik (54:15) Det kommer ta mycket längre tid i alla fall att bygga den typen av företag för att komma tillbaka till det. Du måste bygga upp den erfarenheten kunskapen. måste ha kundreferenserna. Du måste bygga upp de där processerna. Du måste bygga en organisation. Det handlar om att bygga ett bolag och då räcker det inte med att min son sitter hemma och webcoda ett CRM system. Och det kommer det vara en del mindre företag. Anders Hermansson (54:24) Ja. Erik (54:40) kommer ha någon student inne eller någon duktig medarbetare som kan göra ett enkelt CRM system. Ja, och det kan man ju funka för en eller två eller tre användare. Men jag tror att de flesta företag inser att… Tittar du på trenden de senaste 30 åren så har vi gått ifrån att göra egenutvecklade mjukvaror till att köpa standardiserade mjukvara ifrån en leverantör för man vill ha någon som… Alltså så kan man hålla ansvarig för implementation, support, uppgradering och så vidare. Sen så jag tror inte den förändringen kommer svänga tillbaka. Jag tror inte bankerna kommer börja skriva egen ut med egen mjukvara, utan de vill ha en standardleverantör. Däremot kan det vara mindre bolag som lockas och det där för att spara lite pengar. Men jag tror över tid kommer det kosta mer pengar att förvalta den mjukvaran och jag tror att alla bolag Anders Hermansson (55:24) Mm. Erik (55:36) som har en sund affärsidé i grund och botten så kommer det vara mer lönsamt att driva sitt bolag och fokusera på den saken än att göra allt annat som en stödssystem till ens företag. Anders Hermansson (55:48) Ja, just det. Ja, men grymt. Erik, tack så jättemycket för alla bra insikter och inspel här. Det här är jätteinspirerande och jag hoppas att våra lyssnare uppskattar all din klogskap också. Tack så jättemycket för att du var med i Sälj Marknadspodden, måste jag säga. Erik (56:04) Tack Andes och tack alla ni som lyssnade. Anders Hermansson (56:07) Ja, grymt! Ha det så fint! Erik (56:10) Det samma. Anders Hermansson (56:11) Det var allt vi hade att bjuda på från Sälj och marknadspodden för den här gången. Jag hoppas verkligen att ni tyckte det var lika intressant och inspirerande som jag att lyssna på Erik. Det är alltid härligt med en person som har en så otroligt tung och gedigen erfarenhet och samtidigt är så villig att dela med sig av den. Både the good and the bad and the ugly. att säga. Underbart. Vi vill bara avsluta med vårt ständiga tips som kanske gäller nu mer än någonsin i dessa AI-tider. Vad ni gör där ute så ska ni vara relevanta. Hejdå! The post Podd #251 – Erik Syrén om att investera i bolag appeared first on Business Reflex.

What if your next big business breakthrough started with owning your own blind spots?This Fan Favorite episode throws you in the trenches with Cameron Herold and SaaS Academy's former COO and current CEO Matt Verlachi, as they go far beyond surface-level business banter. From surviving firefighting chaos to building, selling, and now scaling SaaS Academy, Matt Verlachi exposes the real skills that make or break Second in Commands. They unpack why customer obsession cures more growth headaches than any software, how to weaponize one-on-ones for radical team development, and what most COOs get dead wrong about CEO dynamics.Miss this? You risk coasting on old habits while others engineer unfair advantages. Listen now for hard-won tactics you won't find in any business course from the world's largest SaaS coaching engine. Timestamped Highlights00:45 – The firefighting mindset that built decisive business instincts05:56 – The overlooked power of “small unit” teams to unlock real growth09:44 – Are you a COO trapped in a CEO's title? The unexpected identity test13:43 – Brutal truths about customer obsession and why most leaders fail here16:18 – The lesson no founder learns soon enough when selling their company18:22 – The surprising reason joining SaaS Academy changed his life21:31 – The founder's hidden block: How self-worth destroys pricing27:31 – The counterintuitive leadership split that 10x'd their decision speed41:07 – How his “full-person” one-on-ones rip open performance breakthroughs About the GuestMatt Verlaque was the former COO of SaaS Academy (now Precision), steering operational strategy for the largest coaching platform serving B2B SaaS entrepreneurs. With first-hand experience ranging from firefighting to founding and selling a SaaS startup, he delivers operating wisdom forged under real pressure. He is currently serving as the CEO at Precision, where they help growth-minded founders understand how their business actually works so they can scale with clarity, not chaos.

“It's stressful to work for an employer and it's stressful to work for yourself. It's just like ‘choose your stress.'” – Anna Burgess YangIn this episode of the Sunlight Tax Podcast, I sit down with Anna Burgess Yang to discuss her journey from corporate banking to solopreneurship. We explore the skills that helped her make the leap, how she approaches business decisions and financial management, and what it really means to navigate risk as a self-employed business owner. Anna also shares practical insights on freelancing and building a sustainable solo business while having effective financial planningAlso mentioned in today's episode:00:10 Introduction to Solopreneurship06:01 Transitioning from Corporate to Freelance10:25 Common Mistakes Solopreneurs Make12:26 The Risks of Employment vs. Self-Employment17:10 Current Economic Landscape for Freelancers22:20 Navigating Career Pivots28:04 Financial Management for SolopreneursIf you enjoyed this episode, please rate, review and share it! Every review makes a difference by telling Apple or Spotify to show the Sunlight Tax podcast to new audiences.About Anna Burgess Yang:Anna Burgess Yang is a freelance content marketer and journalist specializing in B2B SaaS and fintech. She is also a solopreneur educator focused on back-end business operations. A former corporate executive, she now writes long-form content for clients. She also maintains her own blog, newsletter, and a tutorials site. Within her content, she teaches other solopreneurs and marketers how to use AI and automation to work more efficiently.Check Out Anna's Work:FREE RESOURCE: Budget Health CheckAnna's InstagramAnna's LinkedInAnna's YouTube ChannelEpisode Links:Join the Workshop: Save Like a Millionaire: Using Tax-Smart AccountsGet your FREE visual guide to tax deductionsOrder my book: Taxes for Humans: Simplify Your Taxes and Change the World When You're Self-Employed Get full access to Taxes For Humans at sunlighttax.substack.com/subscribe

Place in B2B used to mean partnerships, system integrators, and analyst relations. Now everyone's adding AEO and GEO to the list. But Matt and Liam question whether being mentioned by an LLM actually changes buying behavior — or whether it's just a new version of the same old "just get in front of people" fallacy. A grounded, skeptical conversation about what distribution really means when your product lives in the cloud. Keywords: GEO, AEO, B2B distribution strategy, B2B SaaS go-to-market, AI search marketing, brand consideration

In this episode, Stijn sits down with Antoine, Kalungi's new CEO, for an energizing conversation about what it really takes to grow as a marketing professional in 2026. The centerpiece is Antoine's upcoming book, Level Up — a practical, story-driven guide to becoming the kind of marketer, manager, and teammate that no AI can replace.Antoine pulls from an unconventional journey — from chasing a professional soccer career to leading one of the top B2B SaaS marketing firms in the world — to show that the principles behind great teams aren't that different whether you're on a pitch or in a pipeline review.You'll hear about the frameworks that actually move the needle: situational leadership, managing up and down, self-awareness, and the Super Communicator model — a concept that bridges how you lead your team with how you get the most out of AI tools. Spoiler: the skill that saves you from a 6am angry message from an ambassador might also be the skill that saves your next campaign.Whether you're an individual contributor trying to stand out, or a marketing leader building a team that punches above its weight, this episode will leave you with new language for old challenges — and a few ideas worth acting on today. 

In this today's segment, Dan Sperring, founder and CEO of Align ICP, breaks down a mistake most revenue leaders make when defining their ideal customer profile. The instinct is to chase the highest lifetime value customers, but those segments are often the hardest to win, the slowest to close, and the first to break when the market shifts. This clip focuses on how to balance three critical factors inside your ICP: lifetime value, ease of acquisition, and market health. Dan explains why ignoring any one of these creates pipeline risk, and how leaders can avoid over-rotating into segments that look great on paper but fail in execution. For leaders responsible for predictable growth, this is about making smarter tradeoffs, not just better targeting. Dan Sperring is the founder and CEO of AlignICP, a company focused on helping revenue teams align around high-value customer segments to drive predictable growth. He brings experience across customer success, revenue leadership, and scaling SaaS businesses through product-market and go-to-market alignment. Connect with Dan: AlignICP LinkedIn Books mentioned: The Innovator's Dilemma by Clayton M. Christensen The Innovator's Solution by Clayton M. Christensen and Michael E. Raynor Predictable Revenue by Aaron Ross and ​​Marylou Tyler  Amp It Up by Frank Slootman Tools and podcasts mentioned: clay.com zoominfo.com The Science of Scaling Podcast Listen to the full episode: Aligning Pipeline to Ideal Customer Profile with Dan Sperring Get the Force Management framework for aligning your ICP, sales motion, and customer lifecycle around high-value use cases and measurable business outcomes: The Predictable Revenue Framework: Guide for Leaders Hosted by five-time CRO John McMahon and Force Management Co-Founder John Kaplan, the Revenue Builders podcast goes behind the scenes with the sales leaders who have been there, done that, and seen the results. This show is brought to you by Force Management. We help companies improve sales performance, executing their growth strategy at the point of sale. Connect with Us: LinkedInYouTubeForce Management

If you're running Google Ads and haven't checked your account-level automated assets recently, there's a good chance you're spending money on site links, callouts, and snippets and other AI-generated assets you never set up yourself.In this quick tutorial, I show you exactly where to find automated extensions in Google Ads and how to switch them off. This will save you a lot of money. This came up during a client account audit, and it was AI that reminded me and flagged where the spend was actually going — which is part of why I keep pushing AI as a core part of any PPC workflow nowadays. If you missed the previous video on how I use AI day-to-day for B2B SaaS marketing, the link is in the resources below.Note: this tutorial will help if followed visually.-------------------------------------------------

Pricing is the most avoided conversation in B2B marketing. It's handed down from finance, rubber-stamped by sales, and marketers are expected to promote whatever number comes out. Matt and Liam make the case that pricing is actually a marketing problem — and that the explosion of "no decision" outcomes in B2B SaaS is largely a symptom of not understanding how buyers think about value relative to cost. Keywords: B2B SaaS pricing, pricing strategy, marketing and finance alignment, go-to-market, buyer psychology

Send us Fan MailIn this episode of Sidecar Sync, Amith and Mallory explore three major developments shaping the future of AI. First, they unpack how an OpenAI model independently solved a decades-old mathematical problem—challenging long-held assumptions and proving AI can generate truly novel insights. Then, they break down Microsoft Build 2026 and the shift toward an “agent-first” world, where AI systems take on real work across your organization. Finally, they dive into Anthropic's powerful new Claude Fable model, discussing its capabilities, real-world applications, and the growing tension between performance and transparency. Along the way, they connect these breakthroughs back to what matters most for associations: data strategy, flexibility, and staying ahead in a rapidly evolving AI landscape. 

Going after a new segment sounds sexy… until you actually try to do it.

Explore how transparency and accountability can transform PPC campaigns and client relationships. Simran Harichand shares lessons from her experiences, including a major underspend mistake that ultimately strengthened client trust.Main Topics:Accountability and transparency in PPCRebuilding client trust after budget overspendFoundational best practices in PPCEthical and effective use of AI toolsCommunication and relationship building in advertisingChapters:00:00 Welcome, introductions, and Simran's journey from Pakistan to UK paid media04:17 A €30,000 underspend on a major B2B SaaS account06:17 How a Target CPA change quietly tanked spend08:42 Owning the mistake and facing the client10:11 Rebuilding trust after a costly PPC error12:30 Why underspending can create serious business problems16:48 Breaking into PPC, internships, and hiring junior talent20:27 Why brilliant basics matter more than shiny tactics25:03 Advice for marketers who discover a major mistake26:27 Building client relationships before things go wrong28:46 The worst GA4 and conversion tracking mistakes in account audits33:20 AI Max, Performance Max, and testing new Google features37:54 Where marketers are getting AI wrong41:41 "Nobody Told Me This Was a Career"42:53 Closing thoughts and where to find SimranSimran Harichand - LinkedInPPC Live The Podcast features weekly conversations with paid search experts sharing their experiences, challenges, and triumphs in the ever-changing digital marketing landscape.Thanks to our sponsor ⁠Adsquire,⁠ a small team of passionate and focused legal marketers that do what it takes to get law firms spectacular results! With the landscape always changing they stay on top of the trends and are first to find and use new strategies to accomplish this for our clients - for example they are the FIRST to serve a lawyer ad on ChatGPT.Join the next ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠PPC Live ⁠⁠⁠eventFollow us on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow us on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Slack Group⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter⁠⁠

What does it actually take to build a go-to-market strategy for a category that barely existed 18 months ago?In this episode of The Growth Leaders Series, Charlie Marchant sits down with Nick Lafferty, Founding Marketing Engineer at Profound, the AI Search tracking platform helping major brands understand how they show up in ChatGPT, Gemini, Perplexity, and other LLMs.Nick brings serious growth experience to this role. Before Profound, he drove millions in B2B SaaS pipeline at Loom and Mailgun, then spent two years running a solo consulting agency before joining Profound. In this episode, Nick Lafferty covers:Why velocity is a moat in AI SearchWhat a modern, lean marketing team actually looks like, why Nick hires for a generative marketer mindset, and his advice for showcasing this online The growth strategy behind Profound, centred on sharing data and insightsThe go-to-market motion behind Profound's Zero Click events, scaling from 400 to 800+ attendees across New York and LondonThe layered mentality around AI Search for different business sizesWhy FAQ content and FAQ schema is the lowest-hanging fruit most big brands are leaving on the tableHow to make the internal case for AI Search investment when leadership is still thinking in Google termsThe career advice he'd send back to his first dayRead the full show notes: https://exposureninja.com/podcast/growth-leader-series-nick-lafferty/Follow Nick Lafferty on LinkedIn: https://www.linkedin.com/in/nicklafferty/New episode launches every Wednesday throughout June 2026, so stay tuned to hear from growth leaders from leading brands like McKinsey and Company, Wise, and AirOps! Book a consultation to get a live review of your website and marketing

A gym franchise creates workout content like everyone else in their category — and sees zero brand awareness gains. Sound familiar?Michael Corcoran, the mastermind who drove 2 billion organic impressions in 18 months at Ryanair (with zero paid media), reveals why most brands are failing at social media by copying tactics without understanding strategy.Michael Corcoran is the former head of social at Ryanair, where his team of just eight people transformed the airline into a viral sensation. Today he runs Slice Social, a social media consultancy helping brands achieve extraordinary results through strategic social media marketing.In this episode, you'll discover why jumping on trends isn't a strategy, how to use the 4C's framework to develop actual social media strategy, and why Michael thinks you should create a "data dating show" for a B2B SaaS company. Plus: the real reason Ryanair's unhinged posts worked (hint: it wasn't just about being funny).Here's what you'll learn in this episode:(00:00) Intro(01:06) What clients really want from social media consultants(06:05) The education gap between social media managers and marketers(07:42) Why content pillars aren't strategy (and what actually is)(14:56) Why everyone copying Ryanair's tactics is missing the point(19:31) The 4C's framework: Company, Category, Culture, Customer(22:26) Why posting memes might be lifting your category, not your brand(31:14) Creating a "data dating show" for B2B marketing(60:14) The ROI of 2 billion impressions at Ryanair(63:26) Rapid fire: Books, tools, and who to interview nextWe hope you enjoyed this episode of Ahrefs Podcast! As always, be sure to like and subscribe (and tell a friend).Where to find Michael Corcoran:LinkedIn: https://www.linkedin.com/in/michaelrichardcorcoran/X: @mc_so_meWebsite: https://www.slice-social.com/Where to find Tim:LinkedIn: https://www.linkedin.com/in/timsoulo/X: @timsouloWebsite: https://www.timsoulo.com/Referenced:Alchemy by Rory Sutherland: https://www.amazon.com/Alchemy-Dark-Art-Science-Persuasion/dp/0062388428Ahrefs: https://ahrefs.com#SocialMediaStrategy #MarketingMarketing #SocialMediaMarketing #AhrefsPodcast

Send us Fan MailGuest: Ivan Lee, Founder & CEO of DatasaurWe're looking at what happens when AI changes the market faster than the old SaaS playbook can keep up.Ivan Lee, founder and CEO of Datasaur, joins SaaS Backwards to share how his company navigated one of the most dramatic shifts in enterprise AI. Datasaur started as a data annotation platform before ChatGPT changed customer priorities, paused AI roadmaps, and forced the company to rethink its product, GTM strategy, and business model.Ivan explains why out-of-the-box tools like ChatGPT Enterprise and Microsoft Copilot can be useful starting points, but often hit a ceiling for regulated enterprises that need private AI trained on their own data, workflows, and processes.He also shares how Datasaur moved from a traditional SaaS model toward end-to-end AI solutions, what founders can learn from disrupted marketing channels, and why the future of SaaS may depend less on selling software access and more on solving the customer's actual job to be done.Key Takeaways:Why enterprise AI often breaks down when it lacks access to private data and internal workflowsHow ChatGPT disrupted Datasaur's original AI roadmap and customer baseWhy old SaaS GTM channels stopped working in a crowded AI marketHow Datasaur rebuilt around private, secure AI for regulated industriesWhat SaaS founders should measure when marketing “best practices” stop producing results---Stalled pipeline? Lost deals? Diagnose your GTM gaps with a free, actionable checkup. 

Carl Piehl och Vidar Trojenborg, medgrundare Emfas, gästar podden Framtidens E-Handel. Det blir ett djupt och strategiskt samtal om de senaste månadernas tekniska revolution, hur framtidens P&L-analys förändras i realtid och varför den traditionella B2B SaaS-modellen utmanas. Dessutom diskuterar vi varför mänsklig storytelling och kreativ vision blir den sista vallgraven när agenter tar över rutinarbetet.02:20 - Nya rekord sätts varje månad för AI-bolagens omsättningstillväxt.03:50 - Emfas grundades för att automatisera tråkig hantering av produktdata.06:37 - Det skedde ett revolutionerande teknikskifte mot smarta AI-agenter.11:05 - Traditionell B2B SaaS utmanas av lägre rörliga byteskostnader.13:49 - Nya integrationer gör att du installerar PIM på fem minuter.14:35 - Kontext och datastruktur är svårast när man bygger egna verktyg.19:34 - Kundtjänstbolag med traditionella prismodeller per agent möter svåra tider.22:00 - Duktiga utvecklare blir mer produktiva och efterfrågan förblir hög.25:44 - E-handlare måste först kartlägga sina processer för att lyckas.28:56 - Mindre bolag kan ställa om mycket snabbare än trögrörliga jättar.36:03 - Människor är dramatiskt mycket bättre på att hantera tvetydighet.37:35 - Kreativ vision och genuin storytelling blir varumärkets viktigaste konkurrensfördel.52:20 - E-handeln kommer att gynnas absolut mest av AI-driven effektivisering.Här hittar du Vidar, Carl & Emfas:https://www.linkedin.com/in/vidar-trojenborg-289059106/ https://www.linkedin.com/in/carl-piehl-1a3064163/ https://emfas.ai/ Sponsor Mimir:https://trymimir.com/ Framtidens Berns Event:https://framtidensehandel.se/products/roast Följ Björn på LinkedIn:https://www.linkedin.com/in/bjornspenger/ Följ Framtidens E-handel på LinkedIn:https://www.linkedin.com/company/framtidens-e-handel/ Besök vår hemsida, YouTube & Instagram:https://www.framtidensehandel.se/ https://www.instagram.com/framtidens.ehandel/ https://www.youtube.com/channel/UCEYywBFgOr34TN8NtXeL5HQPoddproducent och klippare Michaela Dorch & Videoproducent Fredrik Ankarsköld:https://www.linkedin.com/in/michaela-dorch/ https://www.linkedin.com/in/ankarskold/ Tusen tack för att du lyssnar!Support till showen http://supporter.acast.com/framtidens-e-handel. Hosted on Acast. See acast.com/privacy for more information.

#361 | In this episode, Matt Carnevale, Head of Community at Exit Five talks with three marketers doing impactful work in AEO. AI search is changing how buyers find products, and most B2B teams are still figuring out where to start. In this session, each marketer shares what's working and wins they've experienced — from earned media and technical audits to homepage fixes and tracking AI visibility. Whether you call it AEO, GEO, LLMO, or EIEIO – this one's for you. This session features guests Matt Dzugan, VP of Data Intelligence at Muckrack, Brett Bernath, Director of Product at Webflow, and Jess Joyce, Founder of Inbound Scope – an SEO and AI Search consultancy.Timestamps(00:00) - - - Why 80% of CMOs say AEO is a top priority — and most don't know where to start (02:48) - - - How Muckrack used original research to get cited in ChatGPT before their product launch (02:50) - - - Why top-of-funnel content is getting eaten by AI — and where to focus instead (02:53) - - - Quick win #3: authority — how to show up in Reddit and third-party platforms (02:56) - - - The sleeper tip: Bing Webmaster Tools is already giving you first-party AI data (03:07) - - - How to handle competitor comparison content without verifiable claims falling flat (03:23) - - - The four-bucket AEO maturity model: content, technical, authority, measurement (03:24) - - - Why your homepage is your worst-performing page for AI discoverability (03:27) - - - Quick win #1: technical hygiene — schema, meta descriptions, and structured data (03:28) - - - How to identify which journalists get cited most by AI in your niche (03:29) - - - Quick win #2: are you actually answering what your customers are asking? (03:34) - - - Why 1 in 3 B2B SaaS sites have technical blockers killing AI discoverability (03:36) - - - Why original research is the single best content type for earning AI citations Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Optimizely - A no-code AI platform where autonomous agents execute marketing work across webpages, email, SEO, and campaigns. Learn how to deploy agents on your marketing team at Agents in the Mix. Learn more at optimizely.com/exitfive. Vector - A contact-level ads platform that lets you build audiences from actual people on your site, clicking your ads, and checking out your competitors. Learn more at vector.co, and get their new MCP server by clicking here. Customer.io - An AI powered customer engagement platform that help marketers turn first-party data into engaging customer experiences across email, SMS, and push. Learn more at customer.io/exitfive.Join us in Stowe, Vermont for Drive 2026 - three days away from your desk to learn what's working in B2B marketing from the people who are actually doing it. Grab your ticket at exitfive.com/drive.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

Send us Fan MailIn this jam-packed “mini” episode, Amith Nagarajan and Mallory Mejias break down a whirlwind of recent AI model releases—from Anthropic, Alibaba, Microsoft, and beyond—and what they signal about the rapidly evolving AI landscape. Then, they dive into Microsoft's 2026 Work Trend Index Report, unpacking the “agency equation” and what it really means for organizations navigating AI adoption. From the rise of agents and the four modes of working with AI to the growing gap between employee readiness and organizational culture, this episode explores why AI transformation is less about tools and more about leadership, systems, and mindset. Plus, they introduce the concept of “owned intelligence” and what it takes to become a true learning organization in the age of AI. 

Join Angel Horvat, Founder and CEO of AI Readi, for a candid evaluation of why the corporate rush into generative AI is grinding to an unexpected halt. Despite massive infrastructure investments, the enterprise journey is hitting a hard wall: while 88% of organizations have initiated AI pilots, a staggering 94% remain permanently trapped in pilot purgatory. Drawing on his years leading AI and data strategy at Nike (EMEA) and Gartner, Angel reveals that these failures are almost never a failure of the tech—they are structural failures of the organization itself. In this episode, we discover how to bridge the gap between initial demo and scaled business value.

In this episode, recorded out in the New Mexico desert at ChiliPalooza, Jordan Crawford makes a blunt case to B2B SaaS: the methodologies you built your career on are about to age out, and the only way through is to get your hands on Claude Code.Jordan's spent his whole job lately doing one thing: teaching clients to work with AI. And what he's found cuts against almost everything sales and marketing teams currently do.What this episode covers:Why the constraint on building things isn't budget or headcount anymore, it's imaginationThe SDR question every revenue leader is asking today: we went all-in, we see the volume, and we don't know what's working...so now what?How Jordan rebuilds prospecting strategies from what customers actually did, not what a rep thinks they wantWhy being wrong fast and cheap beats being right slowly: "you can beat any grandmaster if you get two moves to their one"The truth about a sloppier world, and why polish is no longer the pointWhy the gap between people who are great at this and people who are bad at it comes down to how you think, not skillWhy the "graybeards" built on ten-year-old playbooks are going away, and what replaces themThe people who get in the tool will build things the graybeards can't imagine. The ones who don't will spend the next few years explaining a methodology nobody's buying.-----------------------------------------------------

"A CRO told us the word our customers cared about most was extensibility. I'm a marketer — I've never used that word in my life."When was the last time marketing had a real say in what got built? In most B2B SaaS companies, engineers and founders own the product, and marketers inherit whatever comes out the other end. Matt Sciannella and Liam Moroney explore what it would look like for marketers to genuinely influence product direction — not by taking over, but by asking the questions nobody else is asking. Keywords: B2B marketing strategy, product marketing, market research, customer discovery, SaaS go-to-market.

Most founders think they have a sales problem. According to Lou Shipley, they usually have a customer understanding problem.Lou is a 3x CEO, Senior Lecturer at Harvard Business School, former CEO of Black Duck Software, and co-author of Unlikely Entrepreneurs.During his time at Black Duck, Lou repositioned the company from open-source compliance to open-source security, quadrupled revenue, and helped lead the company to a $565 million acquisition by Synopsys.In this conversation, we discuss: Why founders should not hand off sales too early  The real purpose of your first 100 customer conversations  How to know if you're solving a painful enough problem  Why competitive markets can be better than new markets  The go-to-market framework that helped scale Black Duck  How to identify product-market fit before building too much  What causes churn and how to spot it before it happens  Why most founders misunderstand scaling a sales team  The reality of AI and what founders should pay attention to  Lessons from six startups, multiple exits, and decades of leadership This is a practical conversation about sales, positioning, product-market fit, scaling teams, and building companies that customers actually want.00:00 Introduction to Lou Shipley and Black Duck Software02:00 The Black Duck acquisition story and repositioning strategy04:30 Why founders should own sales longer than they think09:10 Learning from customers before chasing revenue12:00 Why competitive markets are often better opportunities15:00 The myth of the young founder and why experience matters18:40 Understanding customer pain deeply enough to build a company21:20 Signs you're building a solution nobody truly needs22:45 Building software for yourself vs guessing what customers want25:00 How Lou repositioned Black Duck around security27:30 Managing vs leading as your company scales31:00 Escaping the weeds and thinking like an investor33:10 The sales framework behind Black Duck's growth39:00 Churn, product-market fit, and customer retention43:30 AI, software startups, and what founders should watch51:30 What Lou learned after running multiple companies57:20 The one message every founder needs to hearUnlikely Entrepreneurs: Wins, Losses, and Crucial Lessons on Building Great Companies: https://a.co/d/0fPfhi1D

If you're only using AI to write blog posts or social media content, you're leaving serious value on the table, especially if you're in B2B SaaS marketing. In this video, I break down the 3 ways I use AI tools day-to-day as a B2B growth marketer consultant, and I will go through how you can start embedding them into your own marketing workflow.If you're a SaaS founder trying to scale your marketing output or an aspiring B2B marketer building your AI skillset, these practical, and immediately actionable use cases will help you immediately increase the value AI has on your operation.

In this episode, we're joined by George Storm, CRO at N.rich, for a conversation about why traditional B2B SaaS forecasting is no longer good enough in today's market. George shares how N.rich, the European ABM platform, helps sales-led companies influence complex buying committees, warm up priority accounts, and progress accounts before sales ever reaches out.  We spoke with George about why forecasting can't be treated as a static quarterly exercise anymore, why revenue leaders need to account for macro signals like layoffs, budget freezes, acquisitions, interest rates, and market turbulence, and how to move from fixed-number forecasting to ranges, probabilities, and continuous forecast loops. He explains why CROs should think in “regimes” like calm, turbulent, and stormy markets, and how that changes the way you model win rates, sales cycles, ACV, and pipeline coverage. Here are some of the key questions we address: Why is traditional SaaS forecasting broken? Why should forecasts be modeled as ranges instead of fixed numbers? How do macro signals like layoffs, acquisitions, and budget freezes impact pipeline confidence? Why can historical win rates be misleading in today's market? What does it mean to forecast in calm, turbulent, or stormy weather? How can CROs build a continuous forecasting loop instead of relying on quarterly updates? What should revenue leaders monitor weekly to avoid surprise misses?

Send us Fan MailIn this episode of Sidecar Sync, Mallory Mejias welcomes Dr. Jessica Miles, founder of The Informed Frontier, former VP of Strategy and Investments at Holtzbrinck, and advisory board member for Johns Hopkins University Press, for a fascinating look at how AI is transforming publishing, research, and trusted content ecosystems. Jessica explains what happens when AI becomes a “reader” instead of just a writer or assistant, why associations and scientific societies may already be part of AI training pipelines, and how organizations should think about crawl-based access, bulk licensing, and runtime access as the emerging gold standard. The conversation also explores AI's impact on research integrity, peer review, content metrics, and the irreplaceable role of human accountability in an AI-driven knowledge ecosystem.

Salesforce made waves in February 2026 by introducing the Agentic Work Unit, or AWU, as a new way to measure and potentially price AI agent activity. The Metrics Brothers, Ray "Growth" Rike and Dave "CAC" Kellogg dig into whether the AWU is a legitimate step toward outcome-based pricing, a vendor-specific adoption metric, or just another awkward intermediate measure in the long, messy history of software pricing models.Episode Highlights:Tokens are not business metrics. Ray and Dave open by drawing a clear line: tokens measure text processing and compute consumption, not business outcomes. Nobody walks into a board meeting announcing they processed 14 billion word fragments, and enterprise buyers should not be priced on that basis.What Salesforce is actually trying to do with the AWU. Defined as "one discrete task accomplished by an AI agent," the AWU is Salesforce's attempt to bridge the gap between low-level compute metrics and business outcomes. The hosts debate whether it is a pricing metric in waiting, an AI adoption signal, or simply the best available approximation of work performed by agents.A short history of bad pricing units. From CPU counts to MIPS to kilocharacters to gigabytes, Ray and Dave trace the long, humbling history of software vendors searching for a pricing metric that maps to value. The Soviet chandelier analogy makes an appearance, courtesy of Appian CEO Matt Calkins.Activity versus outcome: the core tension. Ray argues the AWU is directionally right but fundamentally an activity metric, not a true economic outcome. Dave is more skeptical that outcome-based pricing can scale broadly, pointing out that customers say they want value-based pricing until a vendor actually tries to take a cut of the upside.Vertical AI applications have the clearest path. Both hosts agree that verticals with well-defined, countable outputs, such as cases resolved in customer support or claims processed in insurance, are best positioned to price on outcomes and may not need the AWU at all.The AWU needs a new name, and probably a new definition. Ray and Dave close with the observation that just as NRR took nearly a decade to emerge as a standard SaaS metric, meaningful AI metrics will take time to mature. The AWU, as currently defined, is a Salesforce-specific construct and unlikely to become an industry standard.If you are a B2B SaaS or AI-Native software operating executive, this conversation on one of the first agentic AI metrics to measure work activity is a great listen.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Aidan Madigan-Curtis's path to becoming a partner at Eclipse hinges on fundamental and generalizable takeaways about the U.S. economy that are coming to the fore again. When she was on the manufacturing team at Apple, helping to launch the first Apple Watch, she realized many of the best minds in the world where whittling away at B2B SaaS even as 85% of global GDP, concentrated on how we make, move, and power things, would require step-changes in both hardware, production processes, and decarbonization and sustainability. To address that gap, Aidan and partners have built Eclipse Capital into a $10 billion venture firm that invests in and support companies combining novel approaches to both atoms and bits-focused businesses to rebuild American manufacturing, energy infrastructure, and industrial capacity.Fast-forward to 2026, and the results validate the insight into the core needs and the opportunity to address it: Eclipse recently raised another $1.3 billion across two new funds to back everything from sodium-ion battery storage (Peak Energy) to next-generation nuclear reactors to radiopharmaceutical manufacturing facilities. The firm's portfolio also spans advanced metal 3D printing (Vulcan Forms), autonomous construction equipment (Bedrock Robotics), and cell therapy manufacturing (Solaris). And the thesis remains largely the same, namely that physical-world companies with durable advantages will define the next market cycle, especially as AI demand collides with infrastructural realities.There's a lot more to Nick and Aidan's convo than this, too. Nick and Aidan also zoomed out to examine topics such as: • How data center build-out could accelerate renewable deployment and other elements of the push to decarbonize and advance sustainability prerogatives• How and why public market narratives are shifting to reward companies with physical assets whereas these were less privileged even a few years ago• The power of manufacturing scale to create geopolitical advantages whether economically or in terms of national security. Tune in for all that and more! To learn more about Eclipse and to explore their portfolio, you can also explore their website here: https://eclipse.capital/Plus, to learn more about their recent fundraising and their theses moving forward, catch up on news articles like this one: https://www.manufacturingdive.com/news/vc-firm-eclipse-raises-1-b-physical-industries-university-endowments/818546/Timestamps:00:02:21 - Eclipse's New Funds and Capital Raising00:03:34 - Eclipse's Focus on Industrial Technologies00:05:47 - Watching the Market Catch Up to Eclipse's Theses00:07:03 - Aidan's Experience at Apple00:08:43 - How COVID and Supply Chain Disruptions Catalyze Change00:09:14 - The Need for Domestic Manufacturing00:11:07 - Company Case Study: Peak Energy and Battery Storage00:12:23 - Company Case Study: The Nuclear Company and "Pre-approved Nuclear"00:15:38 - Geographic Dispersion of Technological Innovation and Impact00:18:23 - Grassroots Resistance to Data Centers00:22:14 - The Opportunity Inherent to Data Centers and Decarbonization00:24:46 - The Industrial Revolution and Rapid Transitions of The Past00:27:09 - The Role of Venture Capital in Sustainability00:28:27 - Shifting Public Market Appetite for Physical Companies00:31:13 - Public Market Dynamics and Narratives00:34:07 - Industrial Innovations and Manufacturing00:38:23 - Advanced Manufacturing in the U.S.00:40:01 - U.S. vs. China in Manufacturing Scale00:43:23 - An Eye Towards the Future of Energy and Climate Tech00:45:01 - Non-linearity in Climate ChangeFinal notes:To keep up with Aidan and her work, you can also follow her on LinkedIn: https://www.linkedin.com/in/aidan-madigan-curtisPlus, you can stay up to date on all things Keep Cool here: https://keepcool.co/ and follow Nick on LinkedIn: https://www.linkedin.com/in/nicholasvanosdol/Thank you so much.

Host: Annik Sobing Guest: Niki McKinnell Published: May 2026 Length: ~22 minutes Presented by: Global Training Center Niki McKinnell on Sales, Marketing, and the Story Behind Supply Chain Growth Annik Sobing welcomes Niki McKinnell to the Simply Trade Roundup for a conversation about what happens when sales and marketing break down in B2B SaaS supply chain companies. Niki shares how her career began in public sector communications and crisis press offices, how she learned to build a story with limited resources, and how that foundation shaped the way she approaches marketing, messaging, and go-to-market strategy today. What You'll Learn in This Episode How Niki built a career around storytelling Niki explains how her path started in government communications, where she worked in press offices and crisis environments. She talks about how those early experiences taught her to think strategically about messaging, audience, and impact. Why sales and marketing break down The episode explores the most common reasons sales and marketing teams lose alignment in supply chain SaaS companies. Niki describes how different definitions, assumptions, and metrics can create friction even when everyone is working toward the same goal. What makes supply chain different Niki breaks down why supply chain has its own flavor when it comes to go-to-market strategy. Buyers are focused on their operations, not your product, which means credibility, timing, and intentional messaging matter more than ever. How to bring teams back into alignment One of the most useful parts of the conversation is Niki's framework for stronger execution: alignment, coordination, and visibility. She explains how teams can work more intentionally before, during, and after GTM activity so they are moving with the same goals in mind. Why long sales cycles need a different approach Niki and Annik discuss how complex buying committees, long sales cycles, and deeply rooted habits make this industry especially challenging. Niki shares how companies need to adapt their strategy to meet buyers where they are. What to do when pipeline stalls Niki offers advice for founders and leaders who are struggling with pipeline. Her recommendation is to focus on the brand, demand, expand framework, with brand awareness, demand generation, and customer growth all working together to support revenue. Who this episode is for This episode is especially valuable for marketing leaders, sales teams, founders, and GTM professionals working in supply chain or B2B SaaS. It is also a great listen for anyone trying to understand how strategy, communication, and alignment shape growth in a complex industry. This podcast is presented by Global Training Center.  Subscribe & Follow Stay connected with the Simply Trade community and never miss an episode that helps you trade smarter.

Send us Fan MailGuest: Anthony Nitsos, Founder of SaaS GurusA SaaS company doesn't become fundable because it's growing—it becomes fundable when the financial engine underneath that growth can withstand scrutiny.In this episode of SaaS Backwards, Anthony Nitsos, founder of SaaS Gurus, joins us to discuss what actually makes a SaaS company fundable. Revenue, customer growth, and cash in the bank are all important signals, but they do not always reveal whether the business is healthy, scalable, or ready for diligence.Anthony breaks down the difference between accounting and strategic finance, why ARR and NRR are often misunderstood, and how metrics like cash flow, CAC, and gross margin can give founders a clearer view of their company's health.Key takeaways:Why finance is forward-looking while accounting is backward-lookingThe five SaaS metrics every founder should understandHow ARR can be overstated through discounts, services, or transaction revenueWhy NRR is becoming more important to investors and acquirersHow strong financial infrastructure can improve fundability and valuation---Stalled pipeline? Lost deals? Diagnose your GTM gaps with a free, actionable checkup. 

From years in the SEO trenches, today's guest knows what it takes to run successful strategies. Adrian Dahlin is the Founder & CEO of Search to Sale, an SEO analytics SaaS company providing automatic content intelligence for B2B, SaaS and marketing agencies.Adrian Dahlin is the Founder & CEO of Search to Sale, an SEO analytics SaaS company providing automatic content intelligence for B2B SaaS and marketing agencies. He began his entrepreneurial journey in 2020 after leaving corporate marketing to launch a startup consultancy, later evolving it into Search to Sale in 2023. Previously, Adrian worked in data science and marketing analytics after earning a Master's in Applied Data Science from NYU, and earlier in his career founded and led sustainability-focused ventures. CONTACT DETAILS:Email: gerardo@searchtosale.io Business: Search to SaleWebsite: https://www.searchtosale.io/ Social Media:LinkedIN: https://www.linkedin.com/in/adriandahlin/ LinkedIN Company: https://www.linkedin.com/company/search-to-sale-seo-revenue-generation-software/ Remember to SUBSCRIBE so you don't miss "Information That You Can Use." Share Just Minding My Business with your family, friends, and colleagues. Engage with us by leaving a review or comment. https://g.page/r/CVKSq-IsFaY9EBM/review Your support keeps this podcast going and growing.Visit Just Minding My Business Media™ LLC at https://jmmbmediallc.com/ to learn how we can help you get more visibility on your products and services. 

Send us Fan MailIn this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias unpack Google I/O 2026 and what it signals for the future of AI-powered work, search, and member engagement. They explore Google's push toward proactive, agentic AI across Gemini, Workspace, Search, and new infrastructure like Antigravity and TPU chips, while digging into what these changes mean for associations trying to protect their content, improve digital experiences, and stay relevant as members increasingly expect voice, multimodal interaction, intelligent search, and personalized service. The conversation also covers AI's impact on career advice, leadership, web traffic, SEO, smart glasses, privacy, and why associations may need to double down on trust, niche expertise, and human connection in an increasingly agent-driven world.

Dan Balcauski is the founder of Product Tranquility, where he helps B2B SaaS companies improve pricing, packaging, and monetization strategy.  In this episode, Dan breaks down the uncomfortable reality behind today's AI gold rush: buyers are tired of "AI-powered" hype, SaaS companies are struggling to monetize features nobody uses, and pricing teams are rewriting their strategies in real time. If your company is trying to monetize AI without becoming another forgettable AI feature, this episode will change how you think about pricing, adoption, and customer value.   Why You Have to Listen: Learn why AI features alone don't drive purchases — and how to position AI around customer outcomes people actually value. Discover the biggest AI pricing mistake SaaS companies are making — charging for features before customers build adoption habits. See how smart SaaS companies roll out AI strategically — using adoption-first pricing, early access models, and workflow-driven product design.   "Prove value with your new AI features before you throw a paywall in front of it." — Dan Balcauski    Topics Covered: 02:10 - "Freemium Is a Terrible Idea for Most SaaS Companies". Why most freemium models fail before companies fully understand the real costs behind them. 06:48 - Why AI Can't Automatically Set Your SaaS Prices. Dan explains where AI can help pricing teams and where human judgment still matters most. 09:53 - The Dangerous Truth About AI Pricing Advice. Most LLMs learned pricing strategy from bad SEO content and outdated thinking. 13:35 - The Adoption vs. Monetization Framework. The simple 2x2 model every SaaS company should use before pricing AI features. 17:34 - Margin Percentage vs. Margin Dollars. A smarter way for CFOs and SaaS leaders to think about AI profitability. 18:32 - "Buyers Don't Care That Your Product Uses AI". Why customers care more about outcomes and workflows than your AI technology. 24:31 - Why SaaS Companies Keep Changing AI Pricing. Most AI pricing models don't survive their first 18 months. 26:07 - The "Early Access" AI Pricing Strategy. How smart SaaS companies introduce AI features without hurting adoption. 29:24 - "Earn the Right to Monetize". Why proving customer value should happen before putting up a paywall.   Key Takeaways: "We need to prove our value first before we can monetize it." – Dan Balcauski   People / Resources Mentioned: Steven Forth — Mentioned as a trusted source of pricing expertise and strategic thinking. Anthropic Claude Code — Dan's primary AI workspace for research synthesis and pricing analysis. Readwise — Tool Dan uses to ground AI outputs using trusted expert highlights and notes. Salesforce — Referenced as an example of rapidly evolving AI pricing strategies. Pragmatic Institute — Mentioned during the discussion on product adoption and feature prioritization.   Connect with Dan Balcauski: Website: https://www.producttranquility.com/ LinkedIn: https://www.linkedin.com/in/balcauski/ X: https://x.com/dan_balcauski Podcast: https://podcasts.apple.com/us/podcast/saas-scaling-secrets/id1682338188   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

Most founders treat 'scale' like a switch you flip after raising a round: hire 14 reps, 10x the ad spend, and pray. About half scale too early and burn the runway, while the other half scale too late and get caught by a more aggressive competitor. Almost nobody can tell you, in measurable terms, when they're actually ready.In this episode, Yaniv Bernstein is joined by Mark Roberge - founding CRO at HubSpot (where he scaled the company from $0 to $100M ARR), senior lecturer at Harvard Business School, cofounder of Stage 2 Capital, and author of the new book 'The Science of Scaling'. Mark walks Yaniv through his impressive data-driven framework for scaling that he's spent a decade refining, covering how to objectively define product-market fit, why customer retention is the only honest measure of PMF, and how to instrument a Leading Indicator of Retention you can act on in week one.In this episode, you will:Learn why retention is the only honest measure of product-market fit, and why most founders are flying blind without itDiscover Mark's framework for building a Leading Indicator of Retention (LIR) you can measure in week one, using Slack, HubSpot, and Facebook as worked examplesHear Mark coach Yaniv through Vera's LIR in real time, and pick up a repeatable method for designing one for your own businessLearn the 'Stay/Go/Slow' model for pacing hires and spend post-raise, and why startups should reassess monthly or quarterly rather than locking in an annual planGet Mark's take on why 'paranoid optimism' is the trait that correlates most strongly with founder success, and the link between that trait and founder mental healthTimestamps00:00 Coming Up00:26 On Today's Show: The Science of Scaling01:47 Guest Intro: Mark Roberge02:31 Why Scaling Needs Data04:20 Eric Ries and Product Market Fit06:56 Retention as a North Star10:15 What Makes a Good Leading Indicator?15:00 Case Study: Vera (Yaniv's Startup)17:41 Choosing Frequency and Event23:55 Instrumenting and Unique Value31:12 Blitzscaling and Defining PET34:41 ICP Denominator Rules37:28 Segmenting By Product40:40 Go To Market Fit45:25 Dealing with Revenue-Focused Investor Pressure50:33 The Pace of Scaling56:07 About the Book, The Science of Scaling57:45 Founder Mental Health01:02:28 Closing ThoughtsResources in this episode:Mark Roberge on LinkedIn: https://www.linkedin.com/in/markroberge/‘The Science of Scaling: Using Data to Decide When — and How Fast — to Scale Revenue' by Mark Roberge: https://www.amazon.com/Science-Scaling-Revenue-Mark-Roberge/dp/1394319428Stage 2 Capital (Mark's B2B SaaS-focused venture firm): https://www.stage2.capital/Vera (Yaniv's startup): https://vera.guide/The PactHonor the Startup Podcast Pact! If you have listened to TSP and gotten value from it, please:Follow, rate, and review us in your listening appFollow us on YouTube for full-video episodes: https://www.youtube.com/@startup-podcastGive us a public shout-out on LinkedIn or anywhere you have a social media followingKey linksThis episode of the Startup Podcast is sponsored by .tech domains. Forget weird prefixes and creative misspellings; the availability for .tech domains is simply way better than .com. For a clean and memorable name, go to https://⁠get.tech/tspThis episode of the Startup Podcast is sponsored by Vanta. Vanta helps businesses get and stay compliant by automating up to 90% of the work for the most in demand compliance frameworks. With over 200 integrations, you can easily monitor and secure the tools your business relies on. For a limited time offer of US$1,000 off, go to ⁠⁠⁠⁠https://⁠www.vanta.com/tsp⁠⁠⁠⁠⁠ The Startup Podcast website: https://www.tsp.show/episodes/Follow Yaniv on Linkedin: https://www.linkedin.com/in/ybernstein/Producer: Justin McArthur https://www.linkedin.com/in/justin-mcarthurAssistant Producer: Steph Hefferan https://www.linkedin.com/in/steph-heff/Intro Voice: Jeremiah Owyang https://web-strategist.com/

Consumption pricing puts pressure on the forecast in places traditional SaaS models rarely exposed. Total usage may be easier to model from the CFO's seat, but the field still has to answer harder questions: which customer, which channel, which rep, and when. In this replay segment, Devavrat Shah explains how AI can help teams learn across cohorts, spot patterns in uneven data, and create more trust in a forecast that would otherwise depend on isolated judgment calls.  Devavrat Shah is an MIT professor, director of MIT's Statistics and Data Science Center, and co-founder and CEO of Ikigai Labs. He brings a data science and operator's perspective to forecasting, consumption pricing, and enterprise AI. Connect with Devavrat: LinkedIn Listen to the full episode here: Understanding AI Through History and Practical Application with Devavrat Shah Hosted by five-time CRO John McMahon and Force Management Co-Founder John Kaplan, the Revenue Builders podcast goes behind the scenes with the sales leaders who have been there, done that, and seen the results. This show is brought to you by Force Management. We help companies improve sales performance, executing their growth strategy at the point of sale. Connect with Us: LinkedInYouTubeForce Management

Get the 3 prompts (research + classify, gift ideas, note writer) in my paid newsletter here.---In this episode, I break down the 2-step ABM gifting system you can run on your top 200 accounts. How to find the clue. How to classify the prospect into one of four buckets (Identity, Passion, Milestone, or No Gift). How to pick a gift that maps to the specific niche. And how to write the note that proves the research wasn't AI-generated.--If you're new here, I'm Elric Legloire, founder of Outbound Kitchen. I help B2B SaaS companies between $2M and $50M ARR fix and scale their outbound system. My view: in 2026, productivity is the multiplier to scale outbound teams.Menu:- Why a $300 researched gift is cheaper than the cold email sequence you'd run into a $200K to $1M ARR account- The 4-bucket prospect classification: Identity, Passion, Milestone, No Gift (and why ~70% land in No Gift)- The specificity ladder: vague vs. niche vs. Passion vs. Signature clues, and which two qualify for a gift- Where to find Signature clues: LinkedIn About sections, podcast appearances, keynotes, blogs, book forewords- A worked example on Kyle Norton (CRO at Owner.com). From clue ("former MMA gym co-owner, black belt") to gift (personalized oak belt display from Etsy with his "Slow is smooth. Smooth is fast." quote)- The 5-part note template: research proof, rabbit hole, gift bridge, pitch + proof, soft ask- Why Perplexity beat ChatGPT for clue research this round, and why you should keep benchmarking AI modelsReferenced:- Stevie Case (CRO, Vanta), Quake rocket launcher gift, sent by Brennan- Tom (CMO, Incident.io), signed vinyl gift- Newsletter with the 3 prompts (research + classify, gift ideas, note writer): https://newsletter.outbound.kitchen/p/abm-how-to-gift-your-top-200-accountsChapters(00:00) Why Gifting Works(01:37) ABM Outbound Fit(02:41) Step One Find Clues(03:29) Clue Buckets Framework(04:41) Avoid Creepy Research(05:38) Make Clues Specific(06:55) Where To Research(07:17) Kyle Norton Example(09:51) Decision Tree Choices(10:40) Step Two Gift Ideas(11:56) Personalized Gift Build(13:24) Write The Note(14:58) Note Template--When you're ready⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Want to work with me? Send me a DM⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ---Connect with me⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Today, we're joined by Dan Balcauski, Founder and Chief Pricing Officer of Product Tranquility, a consulting firm that helps high-volume B2B SaaS CEOs define pricing and packaging for new products. We talk about:How adding AI doesn't always increase valueThe growing importance of discerning what you should buildWhy you should expect to get the pricing of AI capabilities wrong out of the gateWhy charging per tokens is pouring sand in the gas tank of your GTM engine How it's also showing your customers your underpantsCommon bad pricing decisionsThis is Dan's second appearance on SaaS Scaled. You can watch his first episode, “Pricing is Simple, But Not Easy. Dan Balcauski Answers Hard Questions.

For Mother's Day, Tye DeGrange hands the mic to his mom — Ginger DeGrange. Rodeo queen. Horse trainer. Summer camp founder. 36-year instructor who's taught 10,000+ students the art of horsemanship at Santa Rosa Junior College. This one's full of great stories: the OJ Simpson trail ride, a student who went on to dine with the Queen of England, competing at the Grand National, and the old reinsman who taught Ginger that quiet confidence beats loud energy every time. Plus real lessons on building confidence, earning trust, and leading with feel — on and off the horse.

This week's throwback episode guest studied Sociology, Cultural Relations and Global Politics at University of Montana before taking the jump into B2B Sales and Marketing where she has spent most of her career. She has been a Sales Director, Head of Sales, Employee #1 to CRO all leading up to the work she does now as the Founder of Sales-Led GTM Agency. At Sales-Led GTM Agency, she focuses on building the outbound sales strategy, processes & skill sets your sales-led organization needs to thrive, and provides B2B Sales Training & GTM Consulting for B2B SaaS & Service orgs between 15 - 50 M in annual revenue. Last time we spoke, she just left corporate, but since then has been building in public, and now we are 2 years in and will be talking about her journey today! Please join me in welcoming Leslie Venetz to The 20% Podcast. In this week's episode, we discussed:Trusting Your Gut Why Become An EntrepreneurA New Wave of EntrepreneursGet Clear On WorkGetting Specific With Your AsksMuch MorePlease enjoy this week's episode with Leslie VenetzI am now in the early stages of writing my first book! It will cover my journey into sales, the lessons learned, and include stories and advice from top sales professionals around the world. I'm excited to share these interviews and bring you along on this journey!Like the show? Subscribe to the email: Subscribe HereI want your feedback! Reach out at 20percentpodcastquestions@gmail.com or connect with me on LinkedIn.If you know anyone who would benefit from this show, please share it! If you have suggestions for guests, let me know!Enjoy the show!

Dave "CAC" Kellogg and Ray "Growth" Rike dig into the Redpoint Ventures 2026 Software and AI Market Update - a 69-page report built on proprietary CIO survey data from 141 respondents, plus public market data from Qatalyst, Pitchbook, Goldman Sachs, RBC, and McKinsey. Big report with even bigger implications. Ray and Dave unpack the data that matter most for B2B SaaS and AI-native software operators.WHAT WE COVER IN THIS EPISODEThe AI Build-Out Is Real and It's Not the Dot-Com BubbleHyperscaler CapEx is projected to hit $765B in 2026, up nearly 50% year over year. More than 90% of new data center capacity is already pre-committed. Compare that to the dot-com era when fiber utilization was under 3%. The other critical difference: today's infrastructure spend is funded primarily by free cash flow, not debt. The more important signal is demand. AI has reached 1 billion monthly active users in four years. The internet took far longer to reach 70 million. The demand is real. The risk of speculative overbuild is also real.The Agent Maturity Curve and Why Most of the Value Is Still AheadPage 7 of the report maps the four phases of agent maturity by runtime: co-pilots (seconds), task agents (minutes), workflow agents (hours), autonomous agents (days). Co-pilots represent roughly $500B in software spend. Task agents, where coding tools live today, push that to $1.2T. Workflow agents expand the TAM to $2.8T. Autonomous agents take it to $6.1T. Coding has been the beachhead use case for good reasons: structured training data, instant verification, self-improving feedback loops. The real enterprise revenue opportunity is still in phases three and four.What the CIO Survey Actually Says This is the buried lead of the report. 54% of CIOs are actively consolidating vendors. 45% of AI budgets are coming from existing software budgets, not net-new spend. 58% say AI feature additions are the top driver of incremental software spend. 54% prefer to stay with incumbent vendors if they deliver on AI. Only 13% have a strong preference for AI-native software. The 33% who are neutral are the swing vote. Incumbents are winning the preference battle but losing the execution battle — the CIO feedback on Agentforce, Copilot, and ServiceNow AI in the survey is not flattering.Terminal Value Is the Real SaaS Valuation StoryThe public SaaS median NTM revenue multiple sits at 4.1x (Meritech says 3.1x), the lowest since the global financial crisis. In a SaaS DCF, 85 to 95% of enterprise value comes from terminal value, not the five-year forecast. The implied long-term growth rate embedded in current SaaS valuations has collapsed from 4.7% to 1.1%. Short-term beats like ServiceNow's recent quarter do almost nothing to move the stock because the market's concern is not next year. It's year ten and beyond. That is a terminal value story, not a growth story.ARR Per Employee - The Benchmark EvolvesCursor and Anthropic hit $100M ARR in roughly two years. Slack took three. Salesforce and Adobe took four to five. ServiceNow took seven to eight. AI-native companies have made $1M revenue per FTE the new floor. The P&L transformation model in slide 39 projects R&D costs down 15 to 20%, sales costs down 15 to 20%, COGS increasing due to inference spend but offset by reductions in customer support and customer success. Net result: potential EBITDA expansion of 100 to 250% on the same revenue base over three to five years.Private Markets Are in an AI Love FestAI-native deals represent nearly 100% of new VC activity in Q1 2026. Deal concentration is accelerating: the top 20 deals captured 44% of total funding in 2025, up from 31% in 2024 and 7% in 2022. At the model layer, dollars and valuations are concentrated while deal volume belongs to the application layer (61% of deals). The model competition is effectively over. The only question is rank order. The application layer is where the volume plays out, and AI-native vendors are winning that battle.Redpoint 2026 Software and AI Market Update: https://www.redpoint.com/reports/2026-market-updateABOUT THE METRICS BROTHERS Ray Rike is the Founder and CEO of Benchmarkit, the leading B2B SaaS and AI-native software benchmarking company. Dave Kellogg is an EIR at Balderton Capital, independent consultant, and author of Kellblog. Together they bring a CFO-meets-GTM lens to the metrics and benchmarks that drive efficient revenue growth and enterprise value.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Is the Marketing Qualified Lead (MQL) dead, or are marketing teams stuck in a cycle of high-volume, low-return efforts?Marketing economics have undergone significant structural shifts in recent years. With the disappearance of global labor arbitrage and the rise of AI-generated content, the costs of customer acquisition and inbound marketing have skyrocketed. Because of these changes, the once-dominant metric of the MQL is rapidly losing its relevance in today's B2B SaaS environment.In this episode of B2B SaaS Marketing Snacks, Brian Graf, Executive CMO of Kalungi, sits down with Stijn Hendrikse, Kalungi's co-founder and ex-Microsoft product marketing leader, to unpack the risks of over-reliance on MQLs. They talk through why marketing teams can no longer win on sheer quantity and speed alone, and how AI and globalization have completely changed the playing field.You'll hear why focusing on "big plays"—low volume, high depth strategies like flagship events or deep partnerships—is key to sustainable growth. Brian and Stijn also detail practical frameworks for shifting away from the high-volume "MQL trap" and moving toward metrics that actually matter: pipeline value and signal-to-noise ratio. By focusing on these deeper, quality-led strategies, marketing teams can flatten the problem of labor arbitrage and AI ubiquity.In this podcast, you'll learn:Why the once-dominant MQL is losing its relevance in the B2B SaaS environment.How the end of global labor arbitrage and the rise of AI have heavily inflated marketing and customer acquisition costs.The dangers of the "MQL trap," where teams are forced to execute high-volume, high-depth campaigns with diminishing returns.Why shifting to "big plays"—low volume, high depth strategies—is the key to sustainable growth.How to transition your tracking from MQLs to measuring the actual dollar value created in your pipeline.The importance of structuring a leaner marketing team that focuses on signal-to-noise ratio and quality-led strategies.By the end, you'll have a clearer view of why the old inbound playbooks are failing and how to build a quality-led, pipeline-focused go-to-market strategy that cuts through the noise.Chapters:00:00 The Death of the MQL08:20 Shifts in Marketing Economics15:29 The Big Play Quadrant20:49 New Metrics for Success25:44 Team Dynamics and Marketing CostsABOUT B2B SAAS MARKETING SNACKSSince 2020, The B2B SaaS Marketing Snacks Podcast has offered software company founders, investors and leadership a fresh source of insights into building a complete and efficient engine for growth.Meet our Marketing Snacks Podcast Hosts:  Stijn Hendrikse: Author of T2D3 Masterclass & Book, Founder of KalungiAs a serial entrepreneur and marketing leader, Stijn has contributed to the success of 20+ startups as a C-level executive, including Chief Revenue Officer of Acumatica, CEO of MightyCall, a SaaS contact center solution, and leading the initial global Go-to-Market for Atera, a B2B SaaS Unicorn. Before focusing on startups, Stijn led global SMB Marketing and B2B Product Marketing for Microsoft's Office platform.Brian Graf: Executive CMO at KalungiAs a CMO at Kalungi, Brian provides high-level strategy, tactical execution, and business leadership expertise to drive long-term growth for B2B SaaS. Brian has successfully led clients in all aspects of marketing growth, from positioning and messaging to event support, product announcements, and channel-spend optimizations, generating qualified leads and brand awareness for clients while prioritizing ROI. Before Kalungi, Brian worked in television advertising, specializing in business intelligence and campaign optimization, and earned his MBA at the University of Washington's Foster School of Business with a focus in finance and marketing. Visit Kalungi.com to learn more about growing your B2B SaaS company.

In this podcast episode, Diane Wiredu, Founder and Messaging Strategist for Lion Works, underscores the significance of this key element. Diane breaks down a step by step guide on effective messaging, while also providing insights on engaging customers and growing products.Our HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath.Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

Stage 2 Capital General Partner Liz Christo joins the show to discuss the disconnect between venture expectations and reality in the software market. The conversation covers the hidden costs of the new build versus buy debate, the structural changes happening within modern sales organizations, and whether traditional B2B SaaS go-to-market strategies and moats still matter when AI coding tools make software replication cheaper than ever. Key Takeaways: -The shift toward building internal AI tools instead of buying SaaS products overlooks long-term technical debt, as Liz Christo points out that "there's like a huge amount of cost buried behind the scenes that we're not really talking about today because it's still like sexy and fun." -Founders are artificially inflating their Total Addressable Market to meet new venture capital baseline expectations, with Liz Christo noting that "pitch decks read like really ridiculous right now where everybody wants to tell the story of like a $10 billion outcome because that's the new milestone that got set." -Revenue Operations is becoming the most direct path to the Chief Revenue Officer seat in AI-first organizations, which Sam Jacobs explains is "because as we use fewer humans and more agents, the sort of the half technical, the semi-technical capabilities of most RevOps people will translate into orchestrating armies of agents." -Delegating analysis and writing to AI risks destroying strategic judgment across go-to-market teams, a trend Liz Christo summarizes by stating, "I think we are producing an incredible amount of content that's not getting consumed... I just think we're like losing the ability to think and we're not teaching junior employees how to do it." Connect with the Hosts & Guests: Host: Sam Jacobs - https://www.linkedin.com/in/samfjacobs/  Host: AJ Bruno - https://www.linkedin.com/in/ajbruno3/  Host: Asad Zaman - https://www.linkedin.com/in/azaman1/  Guest: Liz Christo - https://www.linkedin.com/in/lizchristo/   Topline is more than a YouTube Channel: Subscribe to Topline Newsletter: https://toplinemedia.substack.com/ Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack   Chapters:  00:00 Intro and Cold Open 02:41 The New Build vs Buy Debate 06:10 Engineers in Every Department 10:48 Pitch Decks and 10B Dollar TAMs 17:53 Venture Capital Funding Quiz 23:43 AI Memos and Critical Thinking 42:41 Software Moats and Switching Costs 47:46 Bulls vs Bears Segment 48:23 RevOps as a Path to CRO 51:25 The Future of SDR Managers 55:14 Is Clay Actually Undervalued 59:12 Odds of Hitting 50M ARR  

Evan Spiegel, the co-founder and CEO of Snap, is one of the very few people in the world who has successfully built and scaled a lasting consumer social product. Snapchat has nearly 1 billion MAUs, and Evan and his team invented some of the most important consumer products and features, including Stories, AR glasses, swipe-based navigation, the camera as the primary UX, and a lot more.In our in-depth conversation, we discuss:1. Why distribution is now the biggest challenge for creating a consumer technology business2. How Snap innovates at scale with a 9-to-12-person design team: no titles, no hierarchy, hundreds of ideas reviewed weekly with the CEO3. Why a pure software business is no longer a moat, and what actually creates durable competitive advantages today4. How AI is changing the way designers work and why they're now shipping code5. Why every major Snap feature was copied and how that forced the company to work differently6. Evan's prediction that humanity's comfort with AI will be a bigger bottleneck than the technology itself7. This year's crucible moment for Snap—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://workos.com/lennyVanta—Automate compliance, manage risk, and accelerate trust with AI: https://vanta.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/snapchat-ceo-why-distribution-is—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Evan Spiegel:• X: https://x.com/evanspiegel• Snapchat: https://www.snapchat.com/@evan• LinkedIn: https://www.linkedin.com/in/evan-spiegel• Website: https://www.spiegelfamilyfund.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 Evan Spiegel(02:28) Why consumer social products are so hard to build(04:31) How Snapchat cracked distribution with close friends, not network size(05:50) Why distribution is the new moat in the AI era(08:39) Snapchat's innovation track record (and why software isn't a moat)(11:39) Why Snap is betting on two of the hardest businesses: consumer social and hardware(16:00) Specs use cases(17:56) The innovation process(21:34) The velocity of design work at Snapchat(25:07) Why Evan says you must talk to customers(26:06) The origin story of Stories(28:25) How screenshot detection saved early Snapchat(31:03) Why they waited to hire PMs—and what role they play now(34:41) How AI is shifting the designer-PM-engineer triad(36:10) Design as an intentional bottleneck for product cohesion(37:24) Why staying close to customers matters for any leader(39:39) What Evan looks for when hiring designers(41:57) How to develop young design talent(44:16) Designers shipping code with AI—and the guardrails needed at scale(47:20) Using jobs-to-be-done to organize AI transformation(48:50) How the CEO job has changed over 15 years(51:30) Learning to communicate(54:08) Why this year is Snapchat's “crucible moment”(56:22) Being the “middle child” in tech(57:51) Screen-time philosophy with four kids (ages 2 to 15)(1:01:08) AI Corner(1:04:02) Contrarian Corner(1:06:04) Lightning round and final thoughts—References: https://www.lennysnewsletter.com/p/snapchat-ceo-why-distribution-is—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

Cat Wu is Head of Product for Claude Code and Cowork at Anthropic, building one of the most important AI products of this generation. Before joining Anthropic, Cat spent years as an engineer and briefly worked in VC. Today, she's interviewing hundreds of product managers who are trying to break into AI—and seeing firsthand what separates those who thrive from those who fall behind.We discuss:1. How Anthropic's shipping cadence went from months to weeks to days2. The emerging skills PMs need to develop right now3. Why you need to build products that don't yet fully work, so you're ready when the next model closes the gap4. Cat's most underrated AI skill: asking the model to introspect on its own mistakes5. Why Claude's personality is core to its success6. Why Anthropic's mission alignment eliminates the friction that slows most large organizations7. Why “just do things” is the most important principle for working at AI-native companies—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVanta—Automate compliance, manage risk, and accelerate trust with AI—Episode transcript: https://www.lennysnewsletter.com/p/why-half-of-product-managers-are-in-trouble—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Cat Wu:• X: https://x.com/_catwu• LinkedIn: linkedin.com/in/cat-wu• Newsletter: https://catwu.substack.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 Cat Wu(01:29) Working with Boris Cherny(04:29) What Anthropic looks for when hiring PMs(06:18) How to help your teams move fast(08:58) How PRDs and roadmaps have evolved at Anthropic(10:28) The Mythos model and Anthropic's shipping velocity(11:54) What happened with the Claude Code source code leak(12:53) Integrating with OpenClaw(14:19) How the PM team is structured at Anthropic(15:42) How engineer and PM roles are merging(17:54) Why product taste is the most valuable skill(20:10) Where human brains will continue to be useful(22:23) How to stay sane in constant chaos(24:16) What gets sacrificed when you ship so fast(27:47) The /powerup command(28:32) Why Anthropic has been so successful(32:28) When to use Claude Code vs. Desktop vs. Cowork(35:58) Tips for getting started with Cowork(38:44) Demo: Using Cowork to build slide decks overnight(41:48) Cat's PM tech stack and internal tools(46:47) Which teams use the most tokens(51:15) The emerging skills PMs need for AI companies(55:00) Why building evals is underappreciated(58:44) Why Claude's character and personality matter so much(1:00:44) How new models force product changes(1:05:11) The vision for Claude Code and Cowork(1:07:22) Advice for thriving in an AI-driven world(1:09:18) Why 95% automation isn't good enough(1:11:58) Build apps you use every day, not prototypes(1:13:41) The divide between AI skeptics and believers(1:15:19) Lightning round—Referenced: https://www.lennysnewsletter.com/p/how-anthropics-product-team-moves—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

Nikhyl Singhal is the founder of The Skip, a community for senior product leaders; a former product exec at Meta, Google, and Credit Karma; and a many-time founder. He's also one of the most honest, unfiltered voices on what's actually happening in product management right now.In our in-depth conversation, we discuss:1. Why the next two years will be the most chaotic period in product management history2. Why half of current product managers are at risk, and what separates those who'll do well3. Why you need to find your “moments of joy” with AI4. The “smiling exhaustion” he's seeing across the product community5. The psychological barriers that prevent people from reinventing themselves6. Why your resume's fancy logos matter less than ever, and what matters now7. His prediction that companies will shed 30,000 people and rehire 8,000—all AI-first—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVanta—Automate compliance, manage risk, and accelerate trust with AI—Episode transcript: https://www.lennysnewsletter.com/p/why-half-of-product-managers-are-in-trouble—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Nikhyl Singhal:• LinkedIn: https://www.linkedin.com/in/nikhyl• X: https://x.com/nikhyl• Podcast & Newsletter: https://skip.show• Skip Community: https://skip.community• Skip Coach: https://skip.coach• Skip.help: https://skip.help—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 Nikhyl Singhal(02:25) The big picture: what's changing for product managers(10:00) Are product leaders doing better than 2-3 years ago?(11:44) What will change in the next couple of years(14:23) How companies are changing the way they build products(15:51) What “judgment” really means for PMs(17:46) Why there won't be any more bad software(20:25) The skills you need to be effective today(23:31) Why there are more PM roles than ever(24:27) The builder versus information-mover divide(30:14) The non-builder problem(30:53) Should PMs code?(34:15) Why experienced leaders still matter(35:44) The diversity setback nobody's talking about(37:21) Why your brand doesn't matter as much anymore(39:54) How valued skills are flipping upside down(40:49) Why change is so hard for humans(43:53) The “equal disappointment” algorithm(46:39) You must cross the threshold(48:37) This chaos will settle(53:19) Finding your moment of joy(58:50) Nikhyl's AI stack and what he's building(1:00:53) The obsolescence mindset(1:05:24) Specific advice for PMs right now(1:08:58) The four jobs that will exist in the future(1:11:59) Why alignment is changing (but not disappearing)(1:15:40) How engineering is changing even more than PM(1:17:04) The surprising design plateau(1:18:49) Finding optimism in the chaos(1:21:12) Lightning round—Referenced:• Building a long and meaningful career | Nikhyl Singhal (Meta, Google): https://www.lennysnewsletter.com/p/building-a-long-and-meaningful-career• COBOL: https://en.wikipedia.org/wiki/COBOL• United Airlines: https://www.united.com• State of the product job market in early 2026: https://www.lennysnewsletter.com/p/state-of-the-product-job-market-in-ee9• Head of Growth (Anthropic): “Claude is growing itself at this point” | Amol Avasare: https://www.lennysnewsletter.com/p/anthropics-1b-to-19b-growth-run• Demis Hassabis on X: https://x.com/demishassabis• Sam Altman on X: https://x.com/sama• Dario Amodei on X: https://x.com/DarioAmodei• Cross on Prime Video: https://www.amazon.com/Cross-Season-1/dp/B0D6X7ZZHC• Jack Ryan on Prime Video: https://www.amazon.com/Tom-Clancys-Jack-Ryan/dp/B0CNDCMN8R• 24 on Prime Video: https://www.amazon.com/24-Season-1/dp/B000HPF85A• Claude Code: https://code.claude.com• Codex: https://chatgpt.com/codex• Lovable: https://lovable.dev• Sonos: https://www.sonos.com• “There are only four jobs” on X: https://x.com/yrechtman/status/2039012253341495462• Paradise on Hulu: https://www.hulu.com/series/paradise-2b4b8988-50c9-4097-bf93-bc34a99a5b4f• Lioness on Paramount+: https://www.paramountplus.com/shows/lioness• Tesla: https://www.tesla.com• Albert Einstein's quote: https://www.goodreads.com/quotes/115696-genius-is-1-talent-and-99-percent-hard-work—Recommended books:• James: https://www.amazon.com/James-Novel-Percival-Everett/dp/0385550367• The Adventures of Huckleberry Finn: https://www.amazon.com/Adventures-Huckleberry-Finn-Unabridged-Uncensored/dp/195483943X—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

Keith Rabois was an early executive at PayPal (part of the famous PayPal Mafia), COO at Square, VP of Corporate Development at LinkedIn, and an early investor in Stripe, DoorDash, Airbnb, YouTube, Ramp, and Palantir. Currently he's managing director at Khosla Ventures. Also, he hasn't touched a computer since September 2010 (he does everything from an iPad).In our in-depth conversation, Keith shares:1. The barrels vs. ammunition hiring framework (and how to spot barrels)2. Why talking to customers is actively harmful for consumer products3. How to identify undiscovered talent4. Why the PM role is dying5. The three traits of the best-performing companies right now6. The specific interview question he asks every senior candidate7. Why CMOs (not engineers) are becoming the #1 consumer of tokens—Brought to you by:WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUsVanta—automate compliance, manage risk, and accelerate trust with AI—Episode transcript: https://www.lennysnewsletter.com/p/hard-truths-about-building-in-the-ai-era—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Keith Rabois:• X: https://x.com/rabois• LinkedIn: linkedin.com/in/keith• Website: https://www.khoslaventures.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 Keith Rabois(01:59) Why Keith hasn't used a computer since 2010(04:52) The team you build is the company you build(07:40) How Keith learned to identify talent at PayPal(10:05) Tactics for getting better at hiring(15:31) The barrels vs. ammunition framework(18:52) What makes someone a barrel(22:36) How to attract the best talent(26:18) Building companies on undiscovered talent(27:53) Why better performance requires more pressure(32:36) Career advice in the age of AI(35:14) The future of the product triad(41:03) Why design and code are merging(49:35) What practicing law taught Keith about entrepreneurship(51:22) Contrarian takes on customer feedback(1:02:33) Identifying great AI opportunities(1:05:13) Advice for evaluating statrups (1:12:36) Criticizing in public vs. private(1:15:05) Failure corner(1:17:29) Lightning round—Referenced:• Square: https://squareup.com• Jack Dorsey on X: https://x.com/jack• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens• Simon Willison's Weblog: https://simonwillison.net• Vinod Khosla on X: https://x.com/vkhosla• Peter Thiel on X: https://x.com/peterthiel• Max Levchin on X: https://x.com/mlevchin• David Sacks on LinkedIn: https://www.linkedin.com/in/davidoliversacks• Tony Xu on X: https://x.com/t_xu• David Sze on X: https://x.com/davidsze• Faire: https://www.faire.com• Max Rhodes on X: https://x.com/MaxRhodesOK• Jeffrey Kolovson on LinkedIn: https://www.linkedin.com/in/jeffreykolovson• Uncapped | Comparative Advantages w/ Keith Rabois: https://www.khoslaventures.com/posts/uncapped-comparative-advantages-w-keith-rabois• Lattice: https://lattice.com• Taylor Francis on LinkedIn: https://www.linkedin.com/in/taylor-francis-4ba49640• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• The art of hiring: insights from Khosla Ventures, Airbnb, Ramp and Traba: https://ramp.com/velocity/the-art-of-hiring-insights• Eric Glyman: Seek out super individual contributors (ICs): https://ramp.com/velocity/the-art-of-hiring-insights#Eric-Glyman:-Seek-out-super-individual-contributors-(ICs)• Eric Glyman on X: https://x.com/eglyman• Mike Moore on LinkedIn: https://www.linkedin.com/in/mike-moore-802223177• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Why you should work much harder RIGHT NOW: https://marginalrevolution.com/marginalrevolution/2026/03/why-you-should-work-much-harder-right-now.html• Opendoor: https://www.opendoor.com• The Craft of Early Stage Venture | Peter Fenton, General Partner at Benchmark | Uncapped with Jack Altman: https://www.youtube.com/watch?v=vRiblwiXt-Q• Lovable: https://lovable.dev• The rise of the professional vibe coder (a new AI-era job) | Lazar Jovanovic (Professional Vibe Coder): https://www.lennysnewsletter.com/p/getting-paid-to-vibe-code• 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• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• Jeremy Stoppelman on X: https://x.com/jeremys• The design process is dead. Here's what's replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead• Andy Warhol: https://en.wikipedia.org/wiki/Andy_Warhol• Curation and Algorithms: https://stratechery.com/2015/curation-and-algorithms• Ernest Hemingway: https://en.wikipedia.org/wiki/Ernest_Hemingway• William Shakespeare: https://en.wikipedia.org/wiki/William_Shakespeare• Evan Moore on X: https://x.com/evancharles• Andrew Mason on X: https://x.com/andrewmason• Read Taylor Swift's Full Viral Speech After Record-Breaking Awards Sweep: https://www.newsweek.com/entertainment/read-taylor-swift-full-acceptance-speech-record-breaking-awards-sweep-11745941• The Chainsmokers: Stories Behind the Songs, AI's Impact on Music, and Venture Investing | Uncapped with Jack Altman: https://www.youtube.com/watch?v=9GMSC-2pYnw&list=PLtpH7YnTL8ihy0nR2BV32n5VkRtqlDAS1&index=16• How to spot a top 1% startup early: https://www.lennysnewsletter.com/p/how-to-spot-a-top-1-startup-early• David Weiden on LinkedIn: https://www.linkedin.com/in/davidweiden• Alfred Lin on LinkedIn: https://www.linkedin.com/in/linalfred• Keith's post about vertical integration on X: https://x.com/rabois/status/870673635375104000• Jon Chu on X: https://x.com/jonchu• Kanu Gulati on X: https://x.com/KanuGulati• Rogo: https://rogo.ai• Profound: https://www.tryprofound.com• Basis: https://www.getbasis.ai• Spellbook: https://www.spellbook.legal• Roelof Botha on X: https://x.com/roelofbotha• Delian Asparouhov on LinkedIn: https://www.linkedin.com/in/delian-asparouhov-87447742• Lessons From Keith Rabois, Essay 1: How to become a Venture Capitalist: https://delian.io/lessons-1• Velocity over everything: How Ramp became the fastest-growing SaaS startup of all time | Geoff Charles (VP of Product): https://www.lennysnewsletter.com/p/velocity-over-everything-how-ramp• Nuremberg on AppleTV+: https://tv.apple.com/us/movie/nuremberg/umc.cmc.3sg4y0382byupy76bfy7307k4• Eight Sleep: https://www.eightsleep.com• “NO DAYS OFF”—Bill Belichick on X: https://x.com/SNFonNBC/status/829036279069364224—Recommended books:• Creativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration: https://www.amazon.com/Creativity-Inc-Overcoming-Unseen-Inspiration/dp/0812993012• The Jordan Rules: The Inside Story of One Turbulent Season with Michael Jordan and the Chicago Bulls: https://www.amazon.com/Jordan-Rules-Sam-Smith/dp/0671796666• The Upside of Stress: Why Stress Is Good for You, and How to Get Good at It: https://www.amazon.com/Upside-Stress-Why-Good-You/dp/1101982934—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