I wanted to share my perspective on this. Rock common idea age. Book thousand year half.
Why Most Approaches Fail
Many common approaches to robotic surgery are flawed at the root.
The root cause is usually one of three things:
Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The Reality Nobody Talks About
A lot of the advice on robotic surgery rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that most founders overthink this and underspend on execution. 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.
The Framework That Actually Works
Here is a simple framework for evaluating robotic surgery. It's not complicated, but it requires discipline.
Step 1: timing is everything in this game
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the market doesn't care about your roadmap
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get robotic surgery right treat it as an ongoing process, not a one-time project.
Real Talk: What Actually Matters
Here is what actually matters in robotic surgery.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on robotic surgery. Many fail because they moved too slowly.
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. It sounds obvious, but many founders make decisions about robotic surgery in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around warehouse robots, humanoid robots, autonomous vehicles, surgical robots, Figure AI that I've been thinking about a lot lately.
What's Next
Best practice in robotic surgery is changing fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
If you're building in this space, the best time to get robotic surgery right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
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: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.
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.