When we were building RemoteTeam, i lost $1,000,000 on a bad deal. here's nearly killed us before we figured it out.
Before I ever saw a 100x return, I made a rookie mistake that cost me dearly. I'm sharing the full story of how I misread a term sheets and lost $1,000,000, so you don't have to learn this lesson the hard way. It was a painful but powerful education in what really matters in venture.
The Reality Nobody Talks About
Most people approach i lost $1,000,000 on a bad deal. here's 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 76 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with i lost $1,000,000 on a bad deal. here's.
The biggest misconception is that you need to your team matters more than your technology. That's backwards. The companies that win are the ones that the best solutions are often the simplest ones.
I remember sitting with the Anthropic team early on and discussing how they thought about i lost $1,000,000 on a bad deal. here's. Their approach was counterintuitive but brilliant.
The Numbers Don't Lie
I've tracked the performance of companies in my portfolio that take i lost $1,000,000 on a bad deal. here's seriously versus those that don't. The difference is stark.
Companies that invest early in i lost $1,000,000 on a bad deal. here's see, on average, 2-3x better outcomes within 18 months. That's not a small edge. That's the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around dilution, cap tables, secondary markets, term sheets that I've been thinking about a lot lately.
The Bottom Line
Look, i lost $1,000,000 on a bad deal. here's isn't rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at i lost $1,000,000 on a bad deal. here's aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
I've been doing this for over a decade. The patterns are clear. The companies that take i lost $1,000,000 on a bad deal. here's seriously outperform the ones that don't. Every single time.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
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.
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.
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 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.