How To Pick A Startup Idea

Y Combinator| 00:11:30|Jun 17, 2026
Chapters9
John explains that founders often struggle with choosing among ideas and overthinking, and offers a rubric to commit to one idea and quickly test if it’s working.

Don’t chase the perfect idea—commit to one, go deep, and validate fast by talking to customers and testing in real life.

Summary

YC partner John lays out a practical rubric for founders stuck choosing among many ideas. He warns that overthinking, whether about finding the perfect idea or the perfect founder, stalls progress because you can only learn by engaging with reality and customers. He shares the “burn the boats” concept to force deep commitment, even recounting GovDash’s multiple pivots and name changes to illustrate going all-in. As you dive deep, you should aim to understand not just customers, but how you would actually run a customer’s business, and to test the idea with real, iterative product delivery. John then reframes validation for the AI era: great ideas sit at the edge of what models can do, verticalize to own outcomes, and be the most ambitious version of themselves. He emphasizes that failing fast isn’t fatal— you gain unambiguous customer data and sometimes discover a better idea underneath. The takeaway is to pick one path, iterate in a tight loop with customers, and walk fast toward a conclusion rather than dabbling across multiple ideas. The overall message: commitment, deep customer empathy, and ambitious scope beat hedging and half-measures in the journey from idea to product-market fit.

Key Takeaways

  • Don’t look for the perfect idea in the abstract; validate by engaging with real customers and getting feedback.
  • Burn the boats: explicitly foreclose other ideas and focus single-mindedly on the chosen one to gain meaningful signal.
  • If you can run a customer’s business tomorrow, you’re likely on the right track; know daily crises, top problems, and willingness to pay.
  • In the AI era, successful ideas verticalize to own outcomes (e.g., be the insurer, not just a software supplier).
  • Aim for the most ambitious version of the idea—scale in regulated spaces or against large incumbents to create a durable moat.
  • Going deep reveals better ideas underneath the surface and accelerates learning more than spreading effort across many concepts.
  • Even a failed idea leaves you with concrete customer data and a clearer pivot path, often uncovering the real opportunity.

Who Is This For?

Founders weighing multiple startup ideas, especially those experimenting with AI or aiming for high-ambition markets. This video offers a concrete process to decide, commit, and iterate quickly.

Notable Quotes

"The most important piece of advice I'd give to founders struggling to pick a startup idea is don't overthink it."
John emphasizes avoiding paralysis by analysis as the core starting point.
"If you pick an idea you're curious about, go extremely deep and most importantly talk to customers."
Encourages deep customer engagement over surface-level exploration.
"Burn the other boats. That is, you should explicitly foreclose your other startup idea options, stop working on them, tell any customers that you've pivoted, and work with single-minded focus on the idea you've chosen."
Describes the go-deep commitment strategy."
"The idea sits at the edge of what models can do today. This might mean that your product barely works on today's frontier models, but will clearly improve as they get better."
Connects idea quality to AI capabilities and future-proofing.
"Being the full stack insurance company allows Corgi to underwrite any insurance line in any vertical with a fraction of the headcount of traditional carriers."
Concrete example of verticalization and owning outcomes in the AI/insurance space.

Questions This Video Answers

  • How do I choose a startup idea without overthinking it?
  • What does it mean to burn the boats in a startup, and when should you do it?
  • How can I validate an AI startup idea quickly with real customers?
  • What is verticalization in the context of AI startups, and why does it matter?
  • What qualifies as an ambitious startup idea in regulated industries?
YCJohn (YC partner)Startup ideasIdea validationBurn the boatsGoing deepCustomer developmentAI-era product strategyVerticalizationCorgi Insurance case study
Full Transcript
[music] Hi, I'm John and I'm a partner at YC. I often meet founders who have lots of ideas about what to work on and can't decide between them. Sometimes they're working on multiple things. Often they'll say that they're waiting to find the best idea before fully committing. But it's extremely hard to make meaningful progress on a startup without committing to a single idea. So in this video, I'm going to give you a rubric for how to stop overthinking, pick an idea, commit to it, and then figure out fast whether it's actually working. The most important piece of advice I'd give to founders struggling to pick a startup idea is don't overthink it. Overthinking a startup in the earliest days can take many forms, but here are a couple of the most common failure modes I see. The first is thinking that you need to find the perfect idea. In some ways, this is an understandable impulse. Startups are hard, so shouldn't you figure out the best idea before committing? The problem with this approach is that it's impossible to figure out the perfect idea in the abstract. You can only figure out what you should be working on by making contact with reality and getting feedback from customers. The second overthink is, am I the perfect founder for this? It's true that founder market fit matters. A non-technical founder likely won't be the right person to come up with a killer DevTools startup idea, for example. But often founders, especially second-time founders, weaponize this line against themselves. They convince themselves that they need a decade of domain experience before they can start. The truth is you don't. If you pick an idea you're curious about, go extremely deep and most importantly talk to customers. It's often possible to develop extraordinary knowledge in a short amount of time. We see incredible examples of this all the time at YC. Take Blake Scho, the CEO of Boom Supersonic. Blake spent his early career working on adtech at companies like Amazon and Groupon before deciding to work on commercializing supersonic flight. Lots of people probably thought he was crazy. But now Boom is a billion-dollar company. So don't let the question of whether you're allowed to work on something stop you from starting. Once you've stopped overthinking your ideas, it's important to commit to just one. Often I meet founders who are working on multiple ideas at once because they believe that this is the best way to figure out which one will actually work. There are a couple problems with this approach. The most serious is that it tends to produce bad data. If you don't actually go deep on an idea, but instead juggle it with several others, you won't get good signal about whether what you're doing actually works. And if you don't get good signal, then you could either prematurely talk yourself out of a good idea or convince yourself that a bad one is worth continuing. The solution to this is to go in depth first. If you're trying to decide between several ideas, all of which look equally attractive, pick one idea and go deep on it. What do I mean by going deep? The first thing is that you should burn the other boats. That is, you should explicitly foreclose your other startup idea options, stop working on them, tell any customers that you've pivoted, and work with single-minded focus on the idea you've chosen. One way to think about going deep is that it should feel like wearing a new skin. You should become an almost unrecognizable version of yourself. This could mean changing your company's name, your emails, your website, and even your internal narrative about why you're building a startup in the first place. For example, I worked with a startup called GovDash that helps customers win government contracts. They pivoted at least five times before finding this idea. And each time they explored something new, they changed their company name and how they talked about their mission. At one point, I forgot how to get in touch with them because they changed their email addresses with each pivot. By truly becoming domain experts in government procurement, their fifth idea worked so well that they could barely keep up with demand. They recently raised the series B to scale the business and meet that demand. Once you've decided to fully commit to an idea and go deep, how do you know if you're actually doing it well? The high watermark I use to help founders answer this question is, could you actually run your customers business? Say you want to build voice customer service agents for cleaning services. The question isn't just whether you've talked to 20 owners. The question is, if I dropped you into a cleaning business tomorrow, would you know how to run it? Do you know what their daily crises are? Do you know whether answering the phone is a top five problem? Do you know how much business they lose when a call goes unanswered and what they would actually pay to never lose another one? These are the kinds of questions you need to be able to answer with very high confidence. Another way to think about this is could you teach a class on the problem you're solving? Are you one of the most informed people in the world on the subject? Getting to this level will involve lots of conversations with customers and sometimes even literally doing the job yourself. But don't obsess over needing to talk to hundreds of customers before writing code. The goal is to do both at the same time in a tight loop. Deep understanding of customer needs, then product delivery, then deeper understanding of customer needs, then better product delivery. Real customers using your product produces concrete data that will complement your abstract knowledge, giving you a sense of whether what you're building is actually working. Once you're going deep on an idea, there's several ways to validate whether it's worth continuing to work on. The most obvious one is pull from customers, but there are several other qualities of good ideas in the AI era that you should look out for as you go. The first is that the idea sits at the edge of what models can do today. This might mean that your product barely works on today's frontier models, but will clearly improve as they get better. You should understand the bottlenecks impeding your product's performance intimately if a particular bottleneck doesn't clear the way you hoped. Solving that might become the company. This is a version of Paul Graham's well-known quote that you should live in the future and then build what's missing. The second quality of a good idea is that it should verticalize. By this I mean that it should ultimately sell an outcome. for example, providing insurance or medical care rather than just software. In the AI era, the cost of producing software is going to zero. So the things that actually become valuable aren't just software for X. They're customer trust, licenses, regulatory permission, and outcome ownership. So if you want to get into the insurance space, don't build software for insurance companies. Just be the insurer. Similarly, rather than selling back office software for banks, just be the bank. One example of this is Corgi Insurance, an AI powered commercial insurance company from YC's summer 24 batch. They were not content with being a tech- enabled broker or even a managing general agent because that was just owning a part of the solution. Instead, they set an ambitious goal of owning everything from underwriting to providing customer service, the entire commercial insurance stack, and even took the unprecedented step of acquiring an insurance carrier during their YC batch to make it happen. Being the full stack insurance company allows Corgi to underwrite any insurance line in any vertical with a fraction of the headcount of traditional carriers. They can offer far better pricing, much faster turnaround, and own all of the economics. That brings me to the third quality of a good idea. It should be the most ambitious version of itself. It may seem unintuitive, but the cost of pursuing a wildly ambitious startup idea and the cost of pursuing a modest one are roughly the same. They're both extremely hard. They both place extreme demands on your time. So aim at the version that if it works rewrites a sector of the economy because that's also the version that protects you from competitors, attracts the best talent and has a moat worth building. This could mean building and selling into the most regulated industries like legal, healthcare, or financial services, or taking on very large incumbents like a 10 billion dollar legacy SAS company, or building hard techch like robotics for space assembly. Now, what if you do all of this and the idea fails? The good news is that you'll be in a dramatically better position than where you started. First, you have unambiguous customer data. You know whether there's actually a hair on fire problem in this space or whether you just talked yourself into thinking there was. You'll have real conviction to base a pivot on and a better sense of how to execute going forward. But more importantly, you will often come away from the process with a new idea that will actually work. When most founders begin, they're solving surface level pain points. The real opportunities are almost always the deeper structural problems. In other words, going deep isn't primarily a process for validating the idea you started with. It's a way to find the better idea underneath. This almost always happens, especially if you're at the forefront of what models can do today. You'll notice the bottlenecks, the gaps, the dev tools nobody's built, and one of those could turn out to be the actual company. Here's what I want you to take away from this video. First, stop trying to find the perfect idea. Just pick one. Then, burn the other boats. Learn everything you can about the customer and try to execute for them. In the early idea fog, where you can only see 10 ft in front of you, the temptation is to take a few cautious steps in every direction. Sample a little here, a little there, stay close to home. The problem is that gives you almost no information. What actually works is to commit to one direction and walk fast. You're not guaranteed to end up in the right place, but you generate much more information per unit of time. And when you're walking, you might arrive at a better destination, one you couldn't have seen from the start. The worst failure mode isn't being wrong. It's not making a decision, spinning your wheels, dabbling between ideas, and never going deep enough on any one of them to learn anything. So, pick one and go deep. Thanks for watching. [music]

Get daily recaps from
Y Combinator

AI-powered summaries delivered to your inbox. Save hours every week while staying fully informed.