I've had this conversation about the 5 unspoken rules of building a defensible with at least 50 founders. Here's the distilled version.
I've got the scar tissue to prove it. A decade in the Valley, with a focus on healthcare AI, has taught me a few things. Here are the lessons from my wins, my (many) failures, and what I'm investing in now.
The Reality Nobody Talks About
Most people approach the 5 unspoken rules of building a defensible 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 you should focus on one thing and do it exceptionally well. 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 best solutions are often the simplest ones. Once we made the switch, everything changed.
What I've Learned From 116 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with the 5 unspoken rules of building a defensible.
The biggest misconception is that you need to customer feedback is the only metric that matters. That's backwards. The companies that win are the ones that you need to move fast and break things.
I remember sitting with the Anthropic team early on and discussing how they thought about the 5 unspoken rules of building a defensible. Their approach was counterintuitive but brilliant.
The AI Angle
I can't talk about the 5 unspoken rules of building a defensible in 2026 without mentioning AI. As someone who's invested in Anthropic, OpenAI, Scale AI, and Hugging Face, I have a front-row seat to how AI is transforming this space.
The short version: AI makes good practitioners better and bad practitioners worse. It's an amplifier, not a replacement.
I've seen companies use AI to 10x their the 5 unspoken rules of building a defensible capabilities. I've also seen companies waste millions on AI solutions that solved the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around AI diagnostics, AI mental health, AI radiology, medical AI, healthcare automation that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about the 5 unspoken rules of building a defensible: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at the 5 unspoken rules of building a defensible share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
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.
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.
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.