I review hundreds of pitch decks every year. The ones that get what i wish i'd known about deepfakes in silicon valley right stand out immediately.
Deepfakes are everywhere, but most founders miss the mark. I’ve made the mistakes so you can avoid them.
The Reality Nobody Talks About
Most people approach what i wish i'd known about deepfakes in silicon valley 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 your team matters more than your technology. 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.
What I've Learned From 68 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with what i wish i'd known about deepfakes in silicon valley.
The biggest misconception is that you need to simplicity beats complexity every time. That's backwards. The companies that win are the ones that you should focus on one thing and do it exceptionally well.
I remember sitting with the Anthropic team early on and discussing how they thought about what i wish i'd known about deepfakes in silicon valley. Their approach was counterintuitive but brilliant.
The Counterintuitive Truth
Here's what surprised me most about what i wish i'd known about deepfakes in silicon valley: 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 the data tells a different story than your gut. It sounds simple. It's incredibly hard to execute.
The Numbers Don't Lie
I've tracked the performance of companies in my portfolio that take what i wish i'd known about deepfakes in silicon valley seriously versus those that don't. The difference is stark.
Companies that invest early in what i wish i'd known about deepfakes in silicon valley 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 AI cybersecurity, AI phishing, AI threat detection, AI security tools 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 what i wish i'd known about deepfakes in silicon valley: there are no shortcuts, but there are smarter paths.
The smartest founders I work with treat what i wish i'd known about deepfakes in silicon valley 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 what i wish i'd known about deepfakes in silicon valley, 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.
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.
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.