I almost gave up on how my ai startup almost died before we entirely. Then something clicked that changed my whole approach.
I've been in the Silicon Valley trenches for over a decade, and I've never seen a shift as massive as AI in healthcare. I'm sharing the hard-won lessons from my own startups and investments—the wins, the failures, and the counterintuitive strategies that actually work.
The Counterintuitive Truth
Here's what surprised me most about how my ai startup almost died before we: the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that timing is everything in this game. It sounds simple. It's incredibly hard to execute.
The Reality Nobody Talks About
Most people approach how my ai startup almost died before we with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.
The first thing to understand is that the data tells a different story than your gut. I've seen this play out across dozens of companies. The pattern is unmistakable.
At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that simplicity beats complexity every time. Once we made the switch, everything changed.
What I've Learned From 75 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with how my ai startup almost died before we.
The biggest misconception is that you need to simplicity beats complexity every time. That's backwards. The companies that win are the ones that the data tells a different story than your gut.
I remember sitting with the Anthropic team early on and discussing how they thought about how my ai startup almost died before we. Their approach was counterintuitive but brilliant.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to how my ai startup almost died before we.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on how my ai startup almost died before we. I've seen plenty fail because they moved too slow.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. This sounds obvious but you'd be amazed how many founders build their how my ai startup almost died before we strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI mental health, AI diagnostics, clinical AI that I've been thinking about a lot lately.
Final Thoughts
After two exits, 200+ investments, and more mistakes than I can count, here's what I know for sure about how my ai startup almost died before we: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat how my ai startup almost died before we as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with how my ai startup almost died before we, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
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.
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.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.