I review hundreds of pitch decks every year. The ones that get i looked at 10,000 clinical trials and found right stand out immediately.
After more than ten years in Silicon Valley, I've seen few changes as big as AI in healthcare. I want to share what I've learned through my startups and investments—the successes, the mistakes, and the surprising moves that actually make a difference.
The Counterintuitive Truth
Here's what surprised me most about i looked at 10,000 clinical trials and found: 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 you should focus on one thing and do it exceptionally well. It sounds simple. It's incredibly hard to execute.
The Reality Nobody Talks About
Most people approach i looked at 10,000 clinical trials and found 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 customer feedback is the only metric that matters. 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 the data tells a different story than your gut. Once we made the switch, everything changed.
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating i looked at 10,000 clinical trials and found. It's not complicated, but it requires discipline.
Step 1: the best solutions are often the simplest ones This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: customer feedback is the only metric that matters Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail i looked at 10,000 clinical trials and found are the ones that treat it as an ongoing process, not a one-time project.
Lessons From the Trenches
I want to share a few specific lessons I've picked up over the years. These aren't theoretical. They come from real companies, real failures, and real successes.
Lesson 1: The best time to start thinking about i looked at 10,000 clinical trials and found was yesterday. The second best time is now. Don't wait until you have the perfect plan.
Lesson 2: Hire for attitude, train for skill. The best i looked at 10,000 clinical trials and found practitioners I've met weren't the most technically gifted. They were the most curious and persistent.
Lesson 3: Your competitors are probably getting this wrong too. That's your opportunity. While everyone else is following the same playbook, you can zig when they zag.
This connects to broader themes around AI radiology, AI diagnostics, clinical AI, AI mental health, drug discovery 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 i looked at 10,000 clinical trials and found: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat i looked at 10,000 clinical trials and found 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 i looked at 10,000 clinical trials and found, 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
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.
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.
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.
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.