It stings to even write that number down. $480,000. Gone. Not because of a bad investment, a market crash, or a soured business deal. I lost it because I was a fool. I got played, plain and simple. Played by a ghost in the machine. A deepfake.
For the last decade, I’ve lived and breathed technology. I built and sold two companies, one to Gusto and another to Gfycat. I’ve written checks to over 200 startups, including some of the biggest names in AI right now, like Anthropic, OpenAI, and Scale AI. I literally wrote the book on how to get to the top of this industry. I thought I had seen it all. I thought I was immune.
That’s what made the fall so much harder. The financial hit was painful, no doubt. But the real damage was to my ego. I, Sahin Boydas, the guy who is supposed to be ahead of the curve, got duped by a technology I’ve been investing in and evangelizing for years. It was a brutal, humbling, and incredibly expensive lesson.
The Anatomy of a High-Tech Heist
It all started, as many of these things do, with an email. It seemed to come from a trusted founder in my portfolio. Let’s call him “Alex.” Alex was raising a small, opportunistic bridge round for his company. The amount was just under half a million dollars—a rounding error for some of my larger investments, but still a significant amount of money. The email had all of Alex’s usual mannerisms. The same slightly-too-formal greeting, the same way of getting straight to the point. It felt right.
He said it was an urgent, off-the-books deal to secure a critical component for their next-gen hardware. The story was plausible. In the world of deep-tech, speed is everything. Sometimes you have to move fast and break things. I’ve done it myself a dozen times. So, I replied, and we scheduled a video call for the next day.
That’s when the real deception began. The video call was flawless. I saw Alex’s face, clear as day. He was in his home office, the same one I’d seen in countless calls before. He spoke with the same passion and conviction I’d come to expect from him. He walked me through the technical specs, the urgency of the situation, and the wire details. It was a textbook pitch. I was sold.
I initiated the wire transfer right after the call. I even sent a confirmation email to Alex. The reply came back almost instantly: “Got it. You’re a lifesaver, Sahin.”
It wasn’t until two weeks later, during a regular portfolio check-in, that the truth came crashing down. I asked Alex how the new hardware was coming along. He had no idea what I was talking about. The color drained from my face. I pulled up the email thread, the wire confirmation. He had never sent the email. He had never been on that video call. The man I spoke to, the man I sent nearly half a million dollars to, didn’t exist.
The “One Simple Trick” That Changes Everything
I spent the next few weeks in a daze. I hired a team of cybersecurity experts. We dug through logs, analyzed the video file, and traced the IP addresses. It was a dead end. The attackers were ghosts. They had used a sophisticated, real-time deepfake model, likely a zero-day exploit that no existing security tool could detect. They had spoofed Alex’s email, studied his online presence, and created a perfect digital puppet.
I lost sleep for months. I questioned every email, every call, every interaction. The trust that is the bedrock of Silicon Valley, the handshake deals and quick decisions, it all felt like a liability. I was on the verge of becoming a digital hermit.
Then, one morning, it hit me. I was going about it all wrong. I was trying to fight a machine with a machine. I was looking for a technological silver bullet, a perfect AI detection tool that would never fail. But that’s a losing game. The attackers will always be one step ahead. The tech will always be a double-edged sword.
The real solution, the “one simple trick,” wasn’t about technology at all. It was about being human.
It’s about re-introducing friction into a world that has become dangerously frictionless. It’s about verification, but not the kind you can automate. I’m talking about human-to-human verification. A simple, low-tech, and surprisingly effective defense.
My New Playbook for Surviving the AI Era
This experience forced me to rewrite my personal and professional playbook. The old rules of speed and efficiency are still important, but they have to be balanced with a new set of principles for security and trust. Here’s what I’ve learned, and what I now practice religiously:
The Two-Channel Rule: For any significant financial transaction or sensitive information exchange, I now require verification on two separate communication channels. If a request comes in via email, I’ll follow up with a text message to a long-held phone number. If we have a video call, I’ll ask a question that only the real person would know the answer to, something from a shared memory that isn’t on the public internet.
The “Watercooler” Question: During video calls, I now make it a point to ask an unexpected, non-business-related question. Something like, “Hey, did you catch the game last night?” or “How was that vacation you took last month?” It’s a simple social cue, but it’s incredibly difficult for a deepfake model to handle in real-time. The slight delay, the generic response, the lack of specific detail—that’s the tell. The ghost in the machine is a great actor, but a terrible improviser.
Embrace the Phone Call: In a world of text, email, and video, the old-fashioned phone call has become a powerful security tool. A real-time, voice-only conversation is much harder to fake than a video. The subtle nuances of human speech, the hesitations, the background noise—these are all data points that are hard to replicate. For anything important, I now pick up the phone.
Trust, But Verify (Your Own Team): The biggest security vulnerability isn’t your firewall; it’s your people. I’ve implemented mandatory training for my entire team on AI phishing and deepfake detection. We run drills. We have a clear protocol for verifying any unusual requests. It’s not about creating a culture of paranoia, but a culture of healthy skepticism.
Invest in Proactive Defense: While no tool is perfect, there are emerging solutions in AI security that are worth paying attention to. I’m not talking about simple detection software. I’m talking about tools that analyze communication patterns, flag anomalies, and provide a layer of proactive defense. I’ve started backing companies in this space, and I’m advising my portfolio to do the same.
The Future is Human
Losing that $480,000 was one of the most painful experiences of my career. But in a strange way, I’m grateful for it. It was a wake-up call. It forced me to confront the dark side of the technology I’ve been so optimistic about. It taught me that in the age of AI, our greatest strength isn’t our processing power, but our humanity.
We can’t out-compute the machines. We can’t build a perfect, impenetrable digital fortress. But we can be smarter. We can be more deliberate. We can use our intuition, our shared experiences, and our human connections to protect ourselves.
The rules have changed. This isn’t just about cybersecurity anymore. It’s about a new kind of digital literacy, a new way of navigating a world where seeing is no longer believing. The deepfakes are only going to get better. The attacks are only going to get more sophisticated. But we have a defense they can’t replicate. We have each other.
Don’t be a fool like I was. Don’t wait for the expensive lesson. Start practicing this new playbook today. Your wallet—and your ego—will thank you for it.
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.
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.
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.