7:17
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.
