Most of what you've read about the deepfakes mistake that cost me $282k is wrong. I know because I believed it too, and it cost me.
Everyone is talking about Deepfakes, but 99% of founders are doing it wrong. I learned the hard way so you don't have to.
The Reality Nobody Talks About
Most people approach the deepfakes mistake that cost me $282k 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 best solutions are often the simplest ones. 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 customer feedback is the only metric that matters. Once we made the switch, everything changed.
What I've Learned From 118 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 deepfakes mistake that cost me $282k.
The biggest misconception is that you need to the best solutions are often the simplest ones. 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 the deepfakes mistake that cost me $282k. 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 the deepfakes mistake that cost me $282k.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on the deepfakes mistake that cost me $282k. 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 the deepfakes mistake that cost me $282k strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI cybersecurity, AI security tools, AI threat detection, zero-day AI, AI phishing 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 the deepfakes mistake that cost me $282k: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat the deepfakes mistake that cost me $282k 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 the deepfakes mistake that cost me $282k, 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'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.
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.