Founder's Story
AI Made MVPs Instant. So Why Are Most Startups Still Losing | Ep. 401 with Eric Ries
22 May 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: How has AI democratized access to entrepreneurship?
Every couple of years, there's like lean startup is dead. AI is going to be so dominated by this MVP thinking and the acceleration. We've been predicting this for a long time, like for $20 a month or $200 a month, you're accessing these like world-class transformative technologies. And you can use that to build products, to release and deploy and compete with the world's largest company.
You get accelerated and you get faster, but so do all your competitors. What can founders do besides exiting or selling? This is a classic wrong thinking. So what we need to do is think about what I call the architecture of institutional longevity. And the first thing we have to do is...
Eric, it's great to have you today. I read The Lean Startup. I don't know if it's like 15 years ago, 14 years ago. Probably, yeah.
Chapter 2: What challenges do startups face with accelerated competition?
Crazy, right? Like how time flies. And obviously, the MVP is the thing that stuck with me. And I've since every business, I've really gone into like, I need to only start with the MVP. It doesn't have to be perfect. I need to get it out there. Nowadays... With vibe coding, I mean, AI can basically create an MVP in five minutes.
How validating is this for you since you basically wrote the playbook on this?
Chapter 3: Why is human oversight crucial in AI applications?
Oh, that's nice of you to say. Yeah, it's funny because for 15 years, but it has been 15 years since the book came out. People have been every couple of years, there's like lean startup is dead. This new trend means we don't need the lean startup.
And people are not really writing that for this wave because it's just so clear, you know, AI is going to be so dominated by this MVP thinking and the acceleration. We've been predicting this for a long time. So to me, AI is an extension of the macro trends I've been writing about for 20 years now.
That what, you know, what the communists, what Karl Marx used to call the means of production, right? Like the power flows to those who control the means of production. Well, we live in an era where anybody can access the means of production as long as you can have a credit card.
So the idea that like for $20 a month or $200 a month, you're accessing these like world-class transformative technologies and you can use that to build products to release and deploy and compete with the world's largest companies, I think is super exciting.
So on one end, you have this democratization, like you're saying, that like anyone around the world that has $20 a month can basically create something that can compete. On the other hand, you also have a lot of people now that will create massive competition and possibly drive the cost down. What do you think about that?
Well, you know, so it's interesting from the point of view of an individual entrepreneur, this is great.
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Chapter 4: What governance structures can protect a company's mission?
These tools are great, but people always assume this is a classic wrong thinking. People always assume that when a sub step of a process becomes more efficient, therefore the overall process becomes more efficient, or even the whole industry becomes more efficient, but not necessarily because many processes are adversarial.
So yeah, you get accelerated and you get faster, but so do all your competitors. And it's worse this time around because not only does every person with an idea have the same acceleration that you do, but also every incumbent has the same tools too. There truly is no differentiation. And the pressure on incumbents to adopt AI is really intense, whether they actually do it or not.
So we'll see whether like net-net, it will take a few years to really understand the impact of these tools on entrepreneurship in general. But my personal feeling is just to be extremely bullish. Even when this hype cycle passes and the current bubble bursts, I still think the infrastructure that is laid will create lots and lots and lots of entrepreneurial opportunity.
Because there's this whole thing around jobs and what's going to happen. Are you pessimistic or optimistic for the future? Now that AI has been at least generative, AI has been advancing like every five seconds, something new comes out.
It's exciting. If you're an entrepreneur, you can't help but be optimistic about things like this. But there's plenty to worry about, both in the short term and in the long run. And I think it's really important.
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Chapter 5: Why do mission-driven companies often fail despite profitability?
People tend to engage in fatalistic thinking with AI, making predictions about what will definitely happen. And it just, as a result, people forget that we actually have a lot of agency over what happens.
And if we don't exercise that agency to have oversight, accountability, what I call in the new book, civic infrastructure, like build out the institutions that will make sure that this technology actually serves for the benefit of all humanity, like there's no guarantee that those things will happen.
My optimism comes from my belief in the power of entrepreneurs to create the new institutions that we so desperately need.
I mean, I'm so excited. Like you said, somebody on a small island in Asia can create something that somebody sitting in San Francisco and Silicon Valley, they can create the same thing at the same time using the same app.
And I don't know if we've ever maybe Shopify, you know, like I don't know if we've ever really been there where where these tools can do this at the cost that almost, you know, millions or if not billions of people can afford. So let's go to, there's obviously this race of AGI. I know you've co-founded answer.ai. How do you see this?
It's like an AI gold rush in itself around like everyone's chasing AGI, but I know you're looking at this differently.
Yeah. Well, I get asked, I've been doing a lot of lectures in universities and in the university setting, I always get asked by the students, is it a bubble or is it a transformational technology? And I always say like the old meme, why not both? So like clearly it can be both.
We've in history seen many situations like you have like the tulip bubble kind of bubbles, but there's also like the telecom bubble. You know, we laid out tremendous amount of fiber in a bout of irrational exuberance during the telecom bubble, but all that fiber is being used today.
So one of the ways that societies build needed infrastructure, especially at times when, you know, you have kind of institutional and governmental dysfunction, as we obviously do right now, sometimes you have to build the infrastructure through these irrational moments.
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Chapter 6: What alternative structures exist for company longevity?
So like, yeah, are we building, you know, is all these data centers investments like actually going to pay off? Is there going to be fraud? Is there going to be some of these companies revealed to be, you know, kind of more like a WorldCom or Enron? For sure. I mean, we really have to be prepped. for a lot of financial fraud.
When this much money is flowing this quickly, you're going to see bad stuff. But the underlying technology is genuinely useful. And I try to get away from phrases like AGI. Even AI, I think, is very misleading because diffusion and LLMs are two totally different technologies.
uh and i think one of the things i think is really misunderstood about llms um the famous paper that that established the transformer the technology that makes llms possible is called attention is all you need and that's that was a really important breakthrough but i think people don't understand is that attention is all you get that's that's only one mechanism that makes llms go which is the attention mechanism and so a lot of what we call artificial intelligence part of the reason why people can't even agree about what it's capable of doing
is it's very sensitive to how well you can focus its attention. And if that's starting to sound a little bit like human beings, then you see the problem. Like just because you have intelligence on the planet doesn't necessarily mean that intelligence can be harnessed and used for anything useful. It depends a lot on the details of the context.
And so I think we're going to have to relearn a lot of civilization scale lessons that we had to figure out with corporations and organizations and humans and their power relationships. Like all that stuff's going to have to be figured out
uh in this new in this new world now at answer ai we have a very contrarian view if we're ultimately if it if it plays out our view is that we should not use llm as a human or creativity replacement but only as a creativity augmenter so everything we do is designed to have humans in the loop and maximally increased human capabilities
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Chapter 7: How can founders design their companies to avoid losing their mission?
So that when you use these tools, you become a super learner and your ability to learn, to grow, to develop new skills is amplified. And we have seen situations where like a small team can, using these tools, can do the work, what used to require a large team. And in some ways be more effective than a large team ever could because the communication overhead is so much more compressed.
So yeah, we're very bullish about our approach, but time will tell if our contrarian bet pays off.
Have you used Claude bot or have you played around with this or what are your thoughts on like leveraging AI where basically like we'll take over everything for you and do things?
Yeah. Again, part of our contrarian view is that we're not super bullish on agents. Part of the issue with agents, it was two, two really like fundamental issues. One is a lot of researchers who like are a little closer to the code than the people making all the headlines really don't think agents can work.
It's not just like they're not working right now, but that there's like a fundamental problem and it has to do with the reliability of each of the sub steps. So yes, we're seeing agent like behavior like work most of the time, some of the time, but like for a lot of mission critical applications, first of all, it has to work all the time.
And as you get into real world situations, agents more and more and more are more likely, just probabilistically speaking, to encounter situations that are out of their training data. And they can become super dumb super fast in ways that people find very confusing and counterintuitive. But it's not because I'm not an anti-agent hater because I don't think AI can do autonomous stuff.
I use the tools that we've built at AnswerAI. I have basically a custom rig for all of the repetitive tasks that I have to do in my life, and it's exceptionally powerful. But calling it an agent, I think, is misleading because in every one of the tools that I use, I, as the human being, am the driver of the process. So I have complete shared understanding with the LLM about what's going on.
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Chapter 8: What are the implications of 'exit' in the entrepreneurial journey?
I can see everything that it sees. It sees everything that I see. And when it makes a mistake or when I make a mistake, we have an opportunity for mutual learning and correction. That's really difficult when the agents are running unsupervised. So the people who are kind of running 10,000 unsupervised agents are
you know, there's going to be some cool stuff come out of that, but there's also going to be a lot of surprising disasters as we get into situations where there's fundamentally not possible to have accountability over what happens. And that's quite scary.
That's why I have not got, I'm not going to go out and get the computer. I'm not going to use it yet. For some reason, when you talk about it, I can't help think about the matrix and like the agents and the matrix. And it's a fascinating world. Like it's, it's incredibly fast moving and your new book that has just come out incorruptible. And you talk about governance as a design problem.
Can you explain why now is this book so important?
Well, thanks for asking. I've been at this a long time now, and I've helped a lot of people create a lot of companies, hundreds or maybe thousands at this point, and make a lot of money, have a lot of success. I'm very proud of everything that we've accomplished as a startup movement to bring new companies to life and to democratize access to companies.
But there's a dark side to it, an underside to it that I think is really quite sad, which is I've also watched a lot of these companies be ruined. I call it in the book them being surgically deboned. And if you look at these big, big companies, they get larger. They start to get more bureaucratic. They start to get lame.
I don't know what the right word is for it, but they kind of just succumb to what we call in Silicon Valley, we call it big code disease. where they're just putting out the same press releases. They become very focused on quarterly returns. They're more interested in serving themselves than serving customers. And it's really sad.
And now a lot of times that happens because the founders lose control of the company. They get ejected, they get taken over, you get private equity involved. But a lot of times, even if the founder has control, they still lose control of it because the culture and the ethos, the character of the company deviates from its intended purpose.
So this is an actually surprisingly large problem as I started to dig into it. I obviously have encountered it in my own life personally. But when I started to really understand the history of how we got here and the scale and scope of this problem, I felt like, oh, no, we have to try and do something about it.
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