Sahin Boydas
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What I Wish I'd Known About Deepfakes in Silicon Valley

Deepfakes are everywhere, but most founders miss the mark. I’ve made the mistakes so you can avoid them.

2024-03-158 min read560 words

Founders who get deepfakes 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

A lot of the advice on deepfakes rests on assumptions that made sense five years ago. The world has moved on.

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.

Many teams spend months on the wrong path before realizing that the data tells a different story than your gut. Once they make the switch, everything changes.

What I've Learned From 68 Companies

A few patterns in deepfakes come up again and again.

The founders who handle deepfakes well understand that you should focus on one thing and do it exceptionally well.

The Counterintuitive Truth

In deepfakes, the best practitioners often do less, not more.

Trying to do everything at once is one of the most common ways to fail: even a team with strong technology and talent can spread itself too thin.

The lesson: the data tells a different story than your gut. It sounds simple. It's incredibly hard to execute.

The Numbers Don't Lie

The gap between companies that take deepfakes seriously and those that don't is usually clear.

Investing early in deepfakes can be 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

There are no shortcuts in deepfakes, but there are smarter paths.

The strongest teams treat deepfakes 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 deepfakes, 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.

FAQ

Frequently Asked Questions

Q: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 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.

Q: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.

Q: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.

Q: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.

Written by

Sahin Boydas

Serial entrepreneur, #1 angel investor, author of Becoming Top 1%

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