I’ve been lucky enough to have a front-row seat to the AI revolution. As an angel investor, I’ve backed over 200 companies, including some of the names you see in the headlines every day, like Anthropic, OpenAI, Scale AI, and Hugging Face. I’ve seen what this technology can do, and I’m a true believer in its potential. But I’ve also seen the hype, the smoke and mirrors, and the dangerous rush to apply AI to everything without thinking about the consequences.
And that brings me to the world of surgery. We’re being sold a story of robotic surgeons, powered by AI, that can perform operations with superhuman precision. A world where human error is a thing of the past. It’s a great story. It’s also a fantasy.
The Hype is Real, The Robots are Not (Yet)
Let’s be clear. I’m not saying AI has no place in medicine. It’s already doing amazing things in areas like drug discovery and medical imaging analysis. But when we start talking about robots cutting into people, we’re in a different league. The stakes are infinitely higher.
I remember when I was building my first company, MovieLaLa. We were trying to change the way people discovered movies. We had a vision, and we were passionate. But we were also scrappy. We had to be. We didn’t have millions in funding to burn through. We had to be smart, and we had to be focused on solving a real problem for our users. We couldn’t afford to get caught up in the hype.
That’s what I see happening in the world of surgical AI. Companies are raising insane amounts of money based on a dream, not on a proven product. They’re making promises they can’t keep, and they’re putting patients at risk in the process.
The Difference Between a Warehouse and an Operating Room
I’ve seen what advanced robotics can do. I’ve seen the videos of Tesla’s Optimus and the robots in Amazon’s warehouses. It’s impressive. But a warehouse is a controlled environment. The lighting is perfect. The floor is flat. The objects the robots are manipulating are all a standard size and shape. An operating room is the exact opposite.
Every patient is different. Every surgery is different. The human body is a messy, unpredictable thing. You can’t just program a robot to perform a surgery and expect it to work every time. There are too many variables. What happens when the robot encounters something it hasn’t seen before? A strange anatomical variation? An unexpected complication? The AI can’t call for help. It can’t improvise. It just follows its programming, and that’s when things go wrong.
We’ve seen this with self-driving cars. The technology is amazing, but it’s not perfect. And when it fails, people die. The same is true for surgical robots. The difference is that in a car, you have a driver who can take over. In an operating room, the surgeon is supposed to be the one in control. But what happens when the surgeon becomes too reliant on the robot? When they lose their skills? When they trust the machine more than their own judgment?
My Bet is on Augmented Intelligence, Not Artificial Surgeons
I’m not a doctor. I’m an engineer and an investor. But I know a good investment when I see one. And right now, I’m not investing in companies that are trying to replace surgeons with robots. I’m investing in companies that are using AI to make surgeons better.
Think of it as a co-pilot, not an autopilot. The AI can analyze medical images and provide the surgeon with more information than they could ever process on their own. It can help them plan the surgery more effectively. It can guide their hand and help them make more precise movements. But at the end of the day, the surgeon is still the one in charge. The surgeon is the one making the decisions. The surgeon is the one who is ultimately responsible for the patient’s life.
This is not just a safer approach. It’s a smarter one. It’s a way to leverage the power of AI without falling for the hype. It’s a way to build a real, sustainable business that is actually helping people, not just chasing a fantasy.
When we sold RemoteTeam to Gusto, it wasn’t because we had built some magical AI that could manage a global workforce on its own. It was because we had built a set of tools that empowered companies to do it themselves. We were providing a solution to a real problem, and we were doing it in a way that was practical and effective.
That’s the approach we need to take with AI in surgery. We need to stop chasing the dream of the fully autonomous surgeon and start focusing on the reality of what this technology can do today. We need to build tools that help surgeons, not replace them. We need to be honest about the risks and the limitations. And we need to remember that at the end of the day, there is a human life on the operating table. That’s not something we can afford to gamble with.
A Call for a Reality Check
To my fellow investors, I say this: stop throwing money at every company that has “AI” in its pitch deck. Do your homework. Understand the technology. Talk to surgeons. Find out what they actually need. And be prepared to walk away from the deals that sound too good to be true. Because they probably are.
To the doctors and hospitals, I say this: be skeptical. Don’t be afraid to ask the tough questions. Demand to see the data. And don’t let anyone sell you a solution that you don’t fully understand and trust.
And to the entrepreneurs, I say this: be bold. Be ambitious. But also be responsible. Don’t promise the moon when you can only deliver a rock. Focus on solving real problems and building real products. That’s how you build a company that lasts. And that’s how you make a real difference in the world.
The truth about AI in surgery is that it’s not a magic bullet. It’s a tool. And like any tool, it can be used for good or for ill. It’s up to us to decide which it will be.
Frequently Asked Questions
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.
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.
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.