I’m going to tell you something that might go against every piece of startup advice you’ve ever heard. The pivot is overrated. Sometimes, the most powerful, game-changing thing you can do is nothing at all. Just dig in your heels and refuse to budge.
I’ve seen it more than 200 times as an angel investor, and I saw it in my own companies. The pressure to pivot is immense. Your investors get nervous, your team gets restless, and you see a competitor raise a massive round for a slightly different approach. The temptation to chase the shiny new object is overwhelming. But the founders who deliver 100x returns? They have a different DNA. They have what I call the “un-pivot” mindset.
What VCs Really Want
When I sit across the table from a founder, especially in the AI space, I’m not just looking at their deck or their code. I’m looking for clues about how they think. VCs say they care about your tech, but what they’re really looking for are signals that you’re a founder with unshakable conviction. They’re looking for the patterns that scream “this person will run through walls to make this happen.”
During the due diligence for RemoteTeam, which was later acquired by Gusto, I remember an investor asking us why we weren’t building more features for synchronous communication. Slack was the darling of the Valley at the time. It seemed like a logical move. But we held our ground. I explained that our core thesis wasn’t about replicating the office online; it was about building a new, asynchronous-first way of working. We believed that was the bigger, more valuable prize. Sticking to that conviction was what ultimately made us a valuable acquisition target. We weren’t just another chat tool; we were a new philosophy of work.
The Allure of the Obvious
One of the biggest traps for founders, especially in AI, is chasing the obvious. You see a new model from OpenAI or Anthropic, and you immediately think of a dozen ways to wrap it in a thin UI and call it a product. That’s a race to the bottom. The market gets flooded, and you’re left competing on price with a hundred other startups that look just like you.
The 100x founders I’ve backed are different. They have a deep, almost obsessive understanding of a specific problem. They’ve spent years thinking about it, and they have a unique, non-obvious insight into the market. They’re not just building an “AI for X”; they’re solving a deep, painful problem for a specific set of customers, and AI just happens to be the best way to do it.
Think about it. When we were building MovieLaLa, which Gfycat acquired, we weren't just another movie discovery app. We obsessed over the social dynamics of how friends share and talk about movies. Our insight was that the recommendation itself was a social object. That focus, that refusal to become a generic movie database, is what gave us our edge.
The Talent War is a Lie
Everyone is talking about the “AI talent wars.” Founders are desperate to hire engineers with experience building large language models. But here’s the secret: the best AI companies aren’t necessarily the ones with the most famous AI researchers. They’re the ones with the team that is most obsessed with the customer’s problem.
I’d rather invest in a team of B+ engineers who deeply understand the workflow of a specific industry than a team of A+ AI researchers who are just looking for a cool technical problem to solve. Why? Because the team that is obsessed with the problem will always find a way. They’ll learn the tech, they’ll find the right tools, and they’ll be relentless in their pursuit of a solution. The tech-obsessed team will get distracted by the next new model and pivot their way into oblivion.
This is the essence of the un-pivot. It’s the deep-seated belief that the problem you’re solving is so important that you’re willing to endure the pain and uncertainty of sticking with it, even when everyone around you is telling you to change course.
When to Stick, When to Twist
So, how do you know if you’re being visionary or just plain stubborn? It’s the hardest question a founder has to answer. Here’s the framework I use:
- Are you learning? Sticking to your guns doesn’t mean ignoring data. It means you are constantly learning from your customers and the market, and that new information is reinforcing your core thesis, not invalidating it.
- Is the problem real? Are you still getting signals from customers that the problem you’re solving is a hair-on-fire, top-three priority for them? If the pain isn’t acute, your conviction might be misplaced.
- Do you have a unique insight? Can you articulate, in a single sentence, what you understand about this market that no one else does? If you can’t, you’re probably just following the herd.
I once advised a founder who was building an AI-powered tool for a very specific niche in the legal industry. His investors were pushing him to go after a broader market. The temptation was huge. But he had spent a decade as a lawyer in that niche. He had a unique, earned insight into the problem. He stuck to his guns, and within two years, he owned that market. He’s now expanding from a position of strength, not desperation.
That’s the art of the un-pivot. It’s not about being stubborn. It’s about having the courage of your convictions. It’s about playing the long game in a world that is obsessed with short-term gains. It’s the hardest thing you’ll do as a founder, but it’s the only way to build something that truly lasts.
Frequently Asked Questions
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.