Few investors can talk about AI startups with the grounded specificity of someone who has both shipped product and taken a company public. Itamar Novick, Founder and General Partner at Recursive Ventures, has been scaling startups for 25 years as a repeat entrepreneur, operator, and investor. In this interview, he walks through the lessons that shaped him at Gigya and Life360, the criteria he uses to fund AI at inception, the “antipatterns” that quietly sink promising companies, and why the center of gravity is returning to Silicon Valley. He also gives a clear warning about the social gap AI could widen, and closes with direct advice for founders: when you see a new wave, jump early.
From Builder to Backer
Itamar’s career starts with hard-earned humility. His first startup in 2001 had one customer and seven employees. When that customer canceled, he had to let everyone go. The experience taught him to learn quickly and not mistake activity for progress.
He later joined Gigya early, working with the company through its $350 million sale to SAP. Then came Life360, where he did something unusual: he left a Sand Hill VC seat, took all his savings, borrowed against it, and bought out a departing co-founder because the usage metrics convinced him families wanted the product. He started as VP of Product, moved to COO, then CBO, and ultimately became CFO for the IPO. His advice to ambitious operators? Once or twice in a career, swing for the fences. If you are talented, you can recover from the downside. If it works, it changes your trajectory.
“Once, sometimes even twice, in your life, you want to swing for the fences.”
~ Itamar Novick
Why AI Now? From Productivity Booster to Work Substitutor
Itamar has been investing in AI since 2012, well before today’s model explosion. What changed in 2022 is the arrival of generative AI, which he sees as fundamentally different from the internet, mobile, and cloud waves. Those made people more productive. This wave replaces portions of human work. He calls ChatGPT “an amazing demo” that still has issues like hallucinations, but believes that what we see in demo form today will become solid reality within a decade.
You can already see the shift in org charts. Teams are experimenting with AI agents that take on portions of marketing, sales support, and operations. The exact timeline is uncertain. The direction of travel is not.
What VCs Like Novick Look For in AI Startups
Itamar evaluates AI companies in two buckets: the timeless venture fundamentals and the AI-specific questions that determine durability.
Timeless Fundamentals
- Team and Talent. He looks for a complete founding “DNA” that matches the go-to-market: technical depth, enterprise sales if needed, or growth hacking skills on the consumer side. He values curiosity, first-principles thinking, coachability, and the ability to sell to every stakeholder: customers, employees, and investors.
- TAM and Fit for Venture. Venture capital makes sense only if the market can support a multi-billion-dollar outcome. A great team in a small market may produce a healthy business, but it is not a venture case. He has no issue with “owner’s-pay” companies; he just wants founders to be honest about which path they are on.
AI-Specific Defensibility
When it comes to AI startups specifically, Itamar encourages founders to ask themselves the following question: “You’re ahead today. Explain to me why and how you’ll still be at least a year ahead of the competition five years from now?”
“You’re ahead today. Explain to me why and how you’ll still be at least a year ahead of the competition five years from now?”
Thin wrappers on foundation models fail this test. With “vibe coding,” work that once took a year for 20 engineers can be replicated in a weekend, which pushes prices and margins down. Durable AI companies tend to show one or both of the following:
- Data moats with learning loops. Unique and permissioned first-party data, plus the ability to use it in reinforcement learning and human-supervised systems so agents reliably improve with use.
- Human-in-the-loop product design. Machines move at AI speed; humans do not. Winners design the moments where the system asks a person, communicates confidence, and builds trust so the software fits how people actually work.
Recursive Ventures has already backed 31 companies in its current fund that exhibit these properties.
Antipatterns: How Startups Fail in Predictable Ways
Borrowed from computer science, “antipatterns” are startup behaviors that feel smart but usually backfire. Itamar argues that success is path-dependent and hard to copy, but failure is teachable. He and collaborator Simeon Simeonov have cataloged 75 startup antipatterns drawn from operating experience.
Two examples that he shared during our discussion:
- Elephant Hunting. Chasing a single mega-logo for a year or two drains energy and stalls learning. By the time procurement limps along, the company has lost momentum and missed dozens of faster feedback cycles with smaller customers.
- Platform Risk. Building on someone else’s platform without an escape route invites sudden disruption. If the platform changes APIs or priorities, the startup can be stranded. Founders should show credible paths to independence and direct relationships with users.
Itamar is publishing his 75 startup antipatterns one by one on his blog, with examples and fixes for each. Follow along at ItamarNovick.com.
The Ecosystem Reset: Back to Silicon Valley, and Hard Tech
During the SaaS boom of the last decade, the frontier was business model innovation rather than hard tech. Cloud delivery, usage-based pricing, bottom-up adoption, and marketplace mechanics could be cloned and localized, so new hubs flourished. Austin, New York, Seattle, London, Berlin, and Miami all produced credible SaaS winners because the core ingredients were talent, product sense, and go-to-market playbooks more than frontier research.
Itamar emphasizes that AI is different. The scarce inputs today are research talent, frontier-scale compute, model evaluation and safety expertise, and the platform companies that supply and coordinate those resources. Those inputs are disproportionately concentrated in the Bay Area. As a result, founders who want faster learning cycles, earlier access to partners, and proximity to the infra layer are relocating, and capital is following. In Itamar’s view, the center of gravity is shifting back to Silicon Valley as AI pulls the ecosystem from business model innovation toward hard tech and deep R&D.
He also sees a shift from “Uber-for-X” style plays to hard tech and deep R&D. Training, evaluation, and deployment are complex. The companies that win combine scientific rigor with strong product instincts. He expects unprecedented value creation over the next decade, with the potential for 10 to 20 new trillion-dollar companies emerging from this wave, and tech’s share of global GDP climbing significantly.
The Warning: Haves, Have-Nots, and Our Responsibility
Itamar doesn’t sugarcoat what he sees coming. In his view, AI is creating a sharp divide between the haves and the have-nots, and it’s happening fast. Funding is flowing unevenly: elite researchers and engineers spinning out of OpenAI, Anthropic, and Stanford are raising massive rounds on pedigree alone, while experienced repeat founders tackling less “sexy” but highly practical AI problems often struggle to get basic seed funding. The imbalance mirrors a broader economic split between those who build and own AI systems and those whose work will be reshaped or replaced by them.
As automation moves from factories and warehouses into offices, service businesses, and creative industries, the prospect of widespread displacement is no longer theoretical. Novick calls it “a tsunami coming that could rip us apart” if society fails to prepare. He criticizes the tendency among industry leaders to downplay these effects, arguing that denying job loss is both dishonest and dangerous.
His call to action is clear and pragmatic: start preparing now. Companies, investors, and policymakers need to reskill and upskill at scale, not as an afterthought but as part of the innovation process itself. That means designing entry-level access to AI tools, building on-ramps for adjacent technical talent, and funding programs that help workers adapt rather than fall behind. Expanding access to AI literacy and opportunity enlarges the addressable market, drives new demand, and reduces the social friction that could slow innovation.
Parting Advice: Jump Early
Itamar leaves founders with a simple directive: when a disruptive wave appears, jump in. Don’t wait for perfect timing. Pivot if you must. Early engagement compounds learning, and learning compounds advantage. He’s watched pre-generative-AI companies try to sit it out; in his view, that’s the surest way to fall behind.
Thank you, Itamar Novick, for joining Startup Success and sharing such candid, actionable guidance for founders and investors.
Intro 00:01
Welcome to Startup Success, the podcast for startup founders and investors. Here, you’ll find stories of success from others in the trenches as they work to scale some of the fastest growing startups in the world, stories that will help you in your own journey. Startup Success starts now.
Kate 00:18
Welcome to Startup Success today. We have Itamar Novak in studio, who is the founder and general partner of Recursive Ventures, who is not just a VC. He’s been a longtime operator. He’s been named by Business Insider for being a top 100 global seed investor for the past five years. Very impressive. Welcome to the show.
Itamar 00:44
Thank you so much, Kate, thank you for having me, and thanks everybody for listening in. Excited to be here today.
Kate 00:50
Yeah, we’re excited to have you because you have a very unique background, which I love because you’ve done so much in the startup ecosystem. Would you mind walking us through that background? Because I think it sets the stage for what you’re doing now at Recursive Ventures.
Itamar 01:09
Yeah, well, that’s so nice of you. You’re giving me way too much credit. But the short version of the story of it is, I’ve been in startups for my entire career, so that’s, that’s almost 25 years now. And I’m a repeat entrepreneur and startup executive, and I’m an investor, so I’ve been on all sides of the table, kind of operating, building, investing, supporting others in doing that. And, yeah, it’s been a fun ride. So as an operator, my last company is a company called Life360 which is now publicly traded on the NASDAQ, around an $8 billion market cap. So kind of helped take it from the very, very early days like pre seed, all the way to the IPO and beyond. Over, gosh, it was a 12 year journey, so it took a while. It takes a while to build a public company, apparently. Yeah, gotta do a bunch of stuff. And then before that, I was an early employee at a company called Gigya, which got sold to SAP for $350 million. So I’ve been part of two big exits, like from the very start right all the way to the end. And yeah, before that, I had a bunch of kind of startups that didn’t go necessarily very well. My first one, I was a founder, and I had a single customer. It was a billing software solution back in 2001 and then the customer called me up one day, and they were like, Yeah, you know, but nobody’s actually really using your billing software. We’re still doing all the invoices by hand, like in writing. Can we just cancel the agreement with you? And this is like my only customer, and I have seven employees, so, you know, they canceled, I had to let go of all the employees. I hand picked and hired. And learned, you know, that I have a lot to learn.
Kate 02:56
Well, you obviously learned it, because then you went on to two successful exits, which, and like you said, you were there from the early days, which not many VCs can say that from the operating side, which is why I think your background is so interesting, right?
Itamar 03:14
And, yeah, with Life360 especially, I came in and I bought out a co-founder, which is something that’s even more rare. It’s like what Elon did with Tesla.
Kate 03:22
Tell us about that? Because I read that, that’s fascinating. How did that come about?
Itamar 03:27
I was a VC on Sand Hill Road at that time, learning from some of the best on how to make great investments in startups. And I came across Life360 and it was not very well understood back then, like 2010, 2011. People were like, Oh, kids are never gonna have smartphones. Oh, this is tracking. It’s weird. And like, and I was listening to all the VCs, and then I did all diligence work, and I looked at like, what, you know? What’s the demand? Is this thing working? Are people using it? Engagement and so on and so forth. And some of the stats that I saw off the charts, I was like, Wow, people want this thing. I don’t care what VCs say. It’s like people are voting with their thumbs, I guess, you know, downloading the app and using it. So I decided to make a crazy move and move into the company. I was first VP of product, and doing all in by basically taking all of my net worth at the time, borrowing more money that I didn’t have against it, and buying a third co-founder that wanted to leave, buying him out.
Kate 04:26
Wow. You went all in. And it paid off. You saw the vision, and you understood it.
Itamar 04:36
Well. It’s something that I tell younger professionals early in their career, I’m like, You know what? Once, sometimes even twice, in your life, you want to swing for the fences, like, if you’re in startups, you want to swing for the fences. You want to go all in. And, you know, worst case, you’ll probably land up on your feet. If you’re a great engineer, or if you’re a great, you know, tech business person, you’re going to find the job. You’re going to be okay, especially if you’re here in Silicon Valley or one of the major entrepreneurial hubs like New York, Austin, London, whatever, like, you’ll find a job and you’ll recover. But if, if you do go all in, if you, if you take that big swing and works out, it will be, you know, career changing, and potentially also life changing, right? So I think if you won’t, if you don’t try, like, maybe once, you might regret it. I don’t know it’s individual, like, I just give advice. I’m not saying it’s the right thing for everybody, but for me, it was the right move. And I was like, Okay, I’m putting all my money into this. I’m taking a loan. Like, if it doesn’t work out, what’s gonna happen? I’m gonna find another job. I’ll be in a little bit of debt, and I’ll recover.
Kate 05:37
Incredible. So you came in, you helped out with, like, product and the whole go-to-market strategy?
Itamar 05:46
Well, actually, I came as VP of Product, and I switched to COO, and then I switched to CFO and CBO. So I moved over from the product side to the business side, and I eventually was the CFO that took the company public. So I did every single role in Life360 other than being the CEO or CTO.
Kate 06:00
You did. What an incredible ride, and congratulations. It is. I’m an avid user, and even more so with kids in college. You know, these young parents think they need it. Well, let me tell you, you really need it in college. When our kids are in college. It’s a great app. It’s incredible. And I pay for it.
Itamar 06:20
You’d be surprised how many college kids use us. You know, I’m a visiting professor at the Haas School of Business. I live next to Berkeley, and that’s where I graduated from. And I always start like, when I’m in class, as a guest –I always start by asking, with a show of hands, how many like their kids, right? They’re undergrads. It’s like Business 101 courses, or Entrepreneurship 101 course. With a show of hands, how many kids here know or have Life360 and it’s 90%. So many college students now use us. It’s great.
Kate 06:54
I believe it. I believe it because we won’t pay for their phones unless they use it. Okay? So what an incredible background. So this must make you really well suited for investing, because you’ve done it all. Tell us about Recursive Ventures.
Itamar 07:24
Yeah, absolutely so. So I’ve been investing in startups for the last 15 years, while I was building Life360 because I came from a VC background. And then I started Recursive Ventures back in 2014 and I kept deploying capital.
Kate 07:25
Oh really. So you’re doing both. (I was doing both.) You are a go-getter.
Itamar 07:31
I’ve been very fortunate to have been early on investing at the pre-seed stage actually at the inception, into two decacorns and another five unicorns. So, you know, multiple hits, I guess, that I was lucky to be part of early on as a small investor. It’s like a snowball, right? I started in 2014 and the first fund did really well. And then in 2018 a bunch of other people, I wasn’t even fundraising like a bunch of other people approached me in 2018 and they’re like, Oh, this is great. Like, you invested in HoneyBook and Placer and, like all these unicorns, Main Mobility, why don’t you do more of that? And I was like, Yeah, but I got a full time job, so I”ll do it on the side, like I do evenings and weekends, and I’m not going to take any fees, because I don’t think that’s fair. It’s not my full time job. And I ended up doing another fund in 2018 and then in 2022 after I was at Life360 for over a decade, and it’s a public company already, I just saw this huge opportunity that’s happening with AI. Coincidentally, I was at Burning Man, and I was next to Sam Altman’s camp, and I saw chat GPT before he came out, and I already had companies that were working with GPT-2 and 2.5 so I knew kind of I didn’t know exactly how big it’s going to get, but I was like, Wow, this is Game Change. So I decided to leave Life360 and go all in on scaling up Recursive Ventures, a venture fund that’s focused on supporting AI founders at inception stage. And sort of double down on that, because I believe what we’re seeing now with AI is unprecedented. Like, we haven’t seen anything like this before. This is like, this is like, the like, the equivalent is the invention of personal computing.
Kate 09:09
I think I agree. I saw a PitchBook presentation this morning, and it was all about AI and it’s just, it’s everything right now. So much to ask you about this. First of all, so you were early on AI, if you were at Burning Man. And tell us, like what you saw, how you like your thoughts around AI, because rarely do you get a chance to talk to somebody who is this early on it.
Itamar 09:33
Yeah. So I’ve actually been investing in AI since 2012 but, yeah, I did. I have multiple AI companies, pre-generative AI pre-LLMs, right? I’m not the only one. There’s been a lot of amazing investors who have been supporting AI projects for a while now. We had like, old school machine learning and NLP, natural language processing, computer vision, right? Companies like Mobileye have been around for a while. AI is not new, but what’s happened since 2022 is absolutely insane and is new. And that is that this kind of generative AI technology, if you will, has really completely transformed this space, and has basically took all the AI that preceded it to a whole next level, and then it also enables so many more things. But here’s what’s fundamentally different, I think, with what happened, what started happening in 2022 and what’s happening right now. We’re moving from an era where we have computers helping people get more productive to an era in which AI is actually replacing the work that humans do. That’s the fundamental shift. So like, you know, you have, like, the internet made us all connected so we can more productively, you know, communicate and transact, right. Then mobile made that really like you have that in the palm of your hand. You have the internet with you, anytime, anywhere. And then Cloud came about, and that enabled, like, delivering software very easily in a cheap way, way that makes it accessible, usable for everybody. So all those waves basically made us more productive and made software better for us to leverage, right.This thing is different. That’s why I think it’s like the invention of the personal computer, because now we have machines basically doing the work for us. That’s the big shift, and it’s happening as we speak. It’s not going to happen overnight, but it is happening. And we should prepare across the board, as a society, culturally, businesses, individuals, it’s going to be a wave like, like we’ve never seen before.
Kate 11:36
I think you’ve summed that up so well. I mean, I’m seeing org charts now with AI agents instead of people, like in marketing and for, like, sales support. I mean, it’s coming. You’re absolutely right.
Itamar 11:50
Yeah, if it’s five years or 10 years out or 20, I don’t have a crystal ball, maybe you have, but it is coming, and we can show it right? Basically the way I think about it, so I’m a little bit more sarcastic about some of those things. I don’t think it’s ready for showtime yet. I think, in a way, ChatGPT is just like an amazing demo of what it would be, because it still has all those issues, right, hallucinations and quality and like we’re seeing them. So it’s an amazing demo, but guess what? That demo is going to be a reality in 10 years, and it will work. It will work well.
Kate 12:22
So well said. So let me ask you this, because you know you have such a good handle on AI and you’ve been investing in this space for so long. What do you look for? I’m sure you get asked this all the time because you’ve had so much success, like, what are you looking for with your investments?
Itamar 12:39
Yeah, absolutely. So I’ll put respond to that in two different buckets. First bucket is the same stuff that all VCs look for when they want to back founders that they believe in. And that is, you know, having the right team in place, which is, you know, do we do we have the right DNA? Like, do we have the technical person? Do we have the salesperson if we need that, if it’s an enterprise sales company or whatnot. Do we have the growth hacker, if it’s a consumer company. Whatever the company needs, like, the key pillars that are needed for success, they need to be there, right? So, complete list. The second thing is, obviously just like, subject matter, expertise, like, Are these people, like, top notch, the best, the best in X, right? Whether it’s AI, whether it’s enterprise sales, whatever it is, right? We want to have, I mean, for startups to succeed, you want to have the best people around, like the a plus players, and it all starts with the founding team. So we want to see that. And then we also look at things like, you know, fundability, Can They Sell? Because eventually, no matter how you want to, like, skin the cat as a founder, you are selling. You’re selling to investors, you’re selling to customers, you’re selling to employees, you’re selling to every stakeholder in the company. So you got to be, you know, fundable. I think that’s that’s important for us to kind of see that you can grow up. And you need to be curious and intellectually honest and thinking ‘first principles’ and coachable, right? Because starting a company and writing code to ship a product is very, very different than running 1000 people public company. And you need to be able to do both, right? So it’s a journey, and you need to embrace it. So that’s in the team. We also look at TAM, which is total addressable market. What I’ve found the hard way is even you have, if you have the best team and the best product, but it’s really addressing a small market. Yeah, it’s never really going to get big. It shouldn’t be be venture backed. So we’re very critical in understanding on like, is this big enough right to warrant venture. And it’s perfectly okay if it’s not. I mean people like, have all these bad connotations around, like, lifestyle businesses. I don’t think about things this way. Like, if you can put a million dollars in your pocket as a business owner every year, that’s amazing. And who cares if it’s venture backed or not, just go ahead and do it. But there’s a class of businesses that need venture and it makes sense, like you’re investing in R&D ahead of time, you’re investing in grabbing market share, like whatever, then, yeah, go raise venture capital money, but only do it because you’re looking at a $10 billion price, right? So TAM has to line up. And then the last thing, this is the second bucket, which is more unique to us, is how we think about AI. And we have a whole thesis around AI moat. And the basic idea is, if you don’t have a moat, if you’re just like a thin rapper on top of ChatGPT, then the music is going to stop at some point. I don’t know if it’s going to happen now or 10 years from now, but you’ll just have like, 20 competitors who replicate what you do with vibe coding over a week, and they’re going to push the price on this thing to zero or zero margins, and you won’t have a valuable company. So we focus on understanding it’s a lot of stuff, but I’ll just try to distill it into like, one question of like, Okay, dear CEO, you’re ahead today. Explain to me why and how you’ll be ahead five years from now, like, at least one year ahead of all the competition. Why?
Kate 15:45
You’re absolutely right because in that space, there’s so much competition that can come about. So you have to be…
Itamar 15:52
And especially with vibe coding, it’s like something that took a year for 20 engineers to build can now be built over a weekend. How do you deal with, like, basically, an endless number of new entrants into your market?
Kate 16:03
Yes, and so are you finding a lot of companies still that meet all this criteria? So you’re excited about what’s out there?
Itamar 16:12
Absolutely. I mean, I’ve already backed 31 companies in this fund, in Recursive Ventures 3. Some of them have data moats, so they have unique data, or they have unique ways of processing data. They’re extremely good at getting customers’ data, first party data, and using it in various ways to do reinforced learning, which is a very important piece of what we need to get done to get agents going – beyond models, go to agents, right? How do we get that done? We need to teach those agents what works and what doesn’t. They need human supervision. So that’s kind of one type of moat that we see. Another type of moat that we see, which is a little bit more subjective, but I think it’s important, is, the machines, the AI is going to move at AI speed. But us humans, we’re going to keep you moving at human speed. And we’re the bottleneck. And it’s okay. It’s like, so whoever figures out in each and every vertical how to best, you know, engage, how to have AI engage best with humans, best user experience, how to get feedback, how to get humans involved, what’s the decision point for the AI where it stops and it’s like, Okay, I’m gonna go ask my human, because I’m not sure, right? I’m gonna give that human confidence, trust, like, I’m 99% sure that this is the answer, but you should check, right? Or no, I’m 100% sure this is right, don’t you don’t have to check your human, I got you right. Whoever figures out those pieces, it’s basically user experience and product, could also win, right? Because it’s really about building trust and about moving at human pace, not AI pace.
Kate 17:43
That is really well said. I’ve never thought about it that way, but you’re exactly right. You have such a great mind around what works at a startup. So I want to switch gears, because you caught my attention, because you have a way of explaining it as anti patterns. I want to delve into that. So explain to the audience what you mean by anti-patterns, and we can go from there. I find this fascinating and really helpful, right?
Itamar 18:12
So first of all, anti-patterns is a concept in computer science, and what we’re talking about here probably is specifically startup anti-patterns. And startup anti-patterns are basically all the things that your gut would say, Oh, this is a great idea, but actually, in many cases, can be very bad for your business mid and long term. So your intuition is like, Yeah, this is great, but actually, no, you should watch out. And the more fundamental idea here is, if you try to learn about success and replicate success in startups, it’s actually not going to be that helpful for you, because every company has its own unique path and its own like combination of things and trends, and sometimes it’s just pure luck that got it where it is. So studying startup success is actually not that effective. However, there are 75 startup anti-patterns that me and a friend jotted down, and we believe that, but that actually failure is you can teach failure. You can teach how to avoid failure. It is repeatable. If you make sure that you don’t make those 75 mistakes in your startup, your odds of success are higher to the degree that’s higher than trying to learn why Brian Chesky Airbnb succeeded. That’s basically the point that we’re trying to make.
Kate 19:36
I love this because so many you’re right, so many founders study like these successful startups, but the market conditions, the you know, the product, they’re all so different. That’s not the way to go about it. So I love this.
Itamar 19:50
But the 75 anti-patterns, many of them apply to any startup company, and if you avoid them, you’re de risking your startup. And here’s one thing that I tell my founders very often, it’s like startups is such a risky business, I mean, gosh, like 99% of companies go out of business. It’s just reality, right? Even if you’re great, you’re likely to go out of business. So in a way, especially with the CEO/founder, because this thing is so risky to begin with, part of your job is actually de-risking.
Kate 20:21
So you’ve identified these 75. Do you have them somewhere where everyone listening can go read them all?
Itamar 20:30
Oh, absolutely, they’re all up on my blog at itamarnovick.com.
Kate 20:33
Perfect. Okay, great. So I’m going to encourage everyone to go check it out. Second, can you give us an example or two of an anti-pattern?
Itamar 20:44
Yeah. So this is something that I see pretty often, especially with younger founders, and we call it elephant hunting. Not actually elephants. We don’t want to do that. That’s a bad thing. You know, it’s like that shiny pie in the sky, million dollar contract with Google – pick some elephant, some big company. And you know, you have your entire team focused on it. They’re on it. They’re working. Obviously, it’s Google, there’s like five different departments involved in the procurement of this thing. And you’re just, like, going through a two year sales cycle, and, you know, a year in, you just figure out that this thing has sacked all of your team’s time, it still has low probability of actually landing, right. You’ve devoted all your time and all your energy, like a given portion of it, to this one contract. And by doing that, even though it’s this pie in the sky, amazing contract, you’ve actually really slowed down your company instead of working with, you know, faster, more nimble potential customers, learning from them, getting the wheel of like, you know, insight, right, like, what’s working, what’s not, with customers. You have been so focused on this one big customer that basically you lost your company in the process. And this happens very often, right? Sometimes founders do it because they really feel like that Google contract is going to motivate the team and we’re going to raise more money in the back of it and stuff like that. And sometimes they’re right, it’s not a black and white, it depends. But very often I see them dragging into spending so much energy, and then, you know, the thing doesn’t work, and then they’re out of business, right?
Kate 22:19
That’s an excellent example, because there’s a time and there still is when it was all about getting that logo, those few logos, and you’re right, if you find yourself hunting that one logo, and it’s slowing everything else down, it becomes – I love that analogy.
Itamar 22:38
Don’t put all your eggs in one basket.
Kate 22:40
Yeah. It’s great advice. Okay, can you share one more and then I’ll promise everyone will have to go to your blog to read the others.
Itamar 22:47
Yeah, sure. Another classic one is platform risk. So this is like, if you were Zynga and you were building on top of the Facebook platform. What does that mean? It means that they can shut you down any day. So there are platform businesses like businesses sitting on top of platforms that work, but the risk is there. So I always ask founders, how do you de-risk that? Is there a way to get out of Facebook? Get out of you know, iPhones? Like, how do you make sure that, as you scale, you have a direct and independent, you know, line to your customers, that doesn’t rely on other people, because other companies, because they might not be there for you, right? They might change gears. I mean, we’ve seen this with LinkedIn. We’ve seen this with Twitter, where there’s like, somebody wakes up one day. It’s like putting out all my developers, I don’t care about my APIs and platforms anymore. And then when that happens, you see who’s actually prepared ahead of time and has alternatives and workarounds, and who’s kind of, you know, left their standing like we’re out of business. So platform risk is another one to take into account.
Kate 23:52
So helpful. And did you come up with these through your work as an investor and an operator?
Itamar 24:00
Yeah, yeah, it’s a combination, but at the same time, I should also give credit to my colleague, Simeon Simeonov, who’s the one that originally mapped all this and has been working with me and writing all these down, like showing folks real world examples of it. It’s born out of his and mine experience as operators, less as a VC, but more as an operator.
Kate 24:22
That’s great. I can see where that would be very helpful. How are you feeling about the startup ecosystem today? Like, are you feeling pretty excited about it still? We get mixed signals.
Itamar 24:33
Yeah, it’s interesting. There’s a bunch of things happening all the same time. So the first one that I think is true is that everything is now getting sucked back into Silicon Valley. This is the epicenter of AI. Everything is here, OpenAI is here, Databricks is here. Like all that infrastructure, all the building blocks of AI are all here. And that made a lot of AI companies, even at the application layer, who leverage all those platforms, move here, because this is where everything’s happening. And kind of, it’s interesting because if you look at the 2010, 2012 to 2021 SaaS bubble, if you want to call it that, sort of, it was actually based more on business model innovation of like Cloud or marketplaces, right? Uber, Airbnb, it’s a business model, right? You can replicate that anywhere in the world. So like suddenly Austin pops up, and even Miami is a startup destination, Berlin and London and all those places. And now I think we’re seeing the reverse. I think we’re seeing everything getting sucked into Silicon Valley and the rest of those entrepreneurial ecosystems are kind of lagging behind. And I think that’s the new normal. Further, it’s no longer about business model innovation. It’s about hard tech, like PhDs sitting there and training models. It’s complicated. The technical expertise, this is back to basics, back to deep tech, back to R&D.
Kate 25:52
Right. It’s so true. We have these founders come on with their AI startups, and the really good ones, I have to have my A game to interview them, because it’s so complicated, right, you know?
Itamar 26:05
Yeah, you got this. I know you do.
Kate 26:07
It is. It’s like four years ago, you’re talking like you said about just things that are kind of intuitive. This is hard stuff.
Itamar 26:15
Super hard. So I’ll get back set, back into Silicon Valley, deep tech, hard tech, too. The third thing is, we like this is so every disruptive wave builds on top of the previous waves, right? So, like, again, mobile, internet, like this one, AI is the biggest. It will go the fastest and will be the most impactful. So what I mean by that is there are people, and I sort of subscribe to that notion of like, okay, so tech today is 15% of global GDP – 12 to 15, pick a number, something in that range. With AI actually replacing labor, both white collar and blue collar, can it be 50% of GDP? And all that in Silicon Valley. So I actually think we’re going to wake up 10 years from now, and there will be 10 to 20 new $1 trillion plus companies in Silicon Valley that did not exist before. Like, the amount of value creation is going to be unprecedented.
Kate 27:14
I love that you’re calling this out this way, because I think you’re really on to something.
Itamar 27:20
And then let me add the fourth dimension, which is worrisome, especially for us as a society. That value creation and wealth generation is going to be concentrated in a smaller number of companies, which is what’s hard. And that leads me to what is happening now today in Silicon Valley in startup funding, which is, you have the have and have nots. And it’s so clear, right? You have people spinning out of OpenAI with no idea or a dumb idea, but have the right research skills. And investors putting millions and tens of millions of dollars behind them, really, for no reason yet. And then you have amazing, bright, experienced, repeat entrepreneurs who are doing something that’s not, quote, unquote sexy in AI, and they can get, like, basic funding. So I think this kind of era of ‘have and have not’ I think is going to keep going. And I think it means that we’ll have leadership, value creation, wealth generation, concentrating a smaller number of people. At the same time, we have people losing their jobs because of robotics and AI. And that is a disaster. That is a recipe for disaster from a society perspective.
Kate 28:40
No, you’re right.
Itamar 28:43
We’ll have a lot to deal with. I’ve already voiced my concerns and even pointed out, you know, people like Sam Altman going to Congress and saying, No, people are not going to lose their jobs. That’s, that’s digging your head in the sand, man. Like as a society, we should step up, and we should understand that there’s this tsunami coming that could rip us apart. Right? We already have enough controversy and extreme views in this country. This is not about politics. This is about how do we as a society make sure that we don’t, don’t dig our head in the sand and understand that we have to reskill and upskill people here before they’re going to find themselves without a job and wondering what they’re going to do with the rest of their lives.
Kate 29:24
I think it’s a great point. And, you know, we have examples in history when we didn’t do that around industries and it was, you know, the impact was significant and negative. So I think it’s a great point, and I think I appreciate you speaking about it candidly. This is, yeah, super helpful. We’re at time, and I could talk to you forever, but we always wrap up the show one last question, last parting words of advice, wisdom for those early stage startup founders listening, if you could leave them with one other thing.
Itamar 30:00
Yeah, maybe. I mean, there’s a few, but I’ll pick one. Whenever you see a new disruptive wave of technology come in, you just jump in the wave. And you jump in the wave first, and that’s how you win. And even if it completely undermines everything that you’ve been doing so far. You need to find a way to navigate and pivot and figure it out. I have founders who are like, pre-generative AI running those companies, and they’re like, Oh, we’re going to be okay. We don’t have to pivot into this – Nope, that’s the wrong approach. You just need to jump in that wave. The sooner you jump in that wave, the sooner you embrace it, the sooner you change your company to embrace that wave, the better off you’ll be, and no, punting this down the road is not a solution.
Kate 30:39
I love how you’ve spoken so real. You’ve gotten real with us. Really, very, very helpful. Thank you so much. So for those listening, tell us your blog again.
Itamar 30:50
ItamarNovick.com
Kate 30:51
Okay, and then tell us where listeners can go learn more about Recursive Ventures.
Itamar 30:56
Well, there’s obviously the RecursiveVentures.com website, but the best way I am on LinkedIn daily writing about VC horror stories, about startup anti-patterns, about what’s going on in AI. Just follow me on LinkedIn. Itamar Novick, I’m the only Itamar Novick. I, T, A, M, A, R, N, O, V, I, C, K, out there, so should be pretty easy to find.
Kate 31:17
Thank you. I follow you on LinkedIn. That’s how you caught my eye. So wonderful to have you on the show. I know you’re super busy. Really appreciate your time. You shared so much. Thank you.
Itamar 31:28
Thank you so much, Kate. Thanks for having me and thanks for everybody listening. Hope to catch up with everybody soon.
Intro 31:35
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