After years in the trenches of Silicon Valley, I've seen firsthand how the right AI hardware can make or break a company. I'm sharing the hard-won lessons and contrarian insights I wish I had when I started, from navigating the GPU shortage to building our own custom silicon.
The Reality Nobody Talks About
A lot of the advice on quantum computing 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 customer feedback is the only metric that matters. Once they make the switch, everything changes.
The Counterintuitive Truth
In quantum computing, the best practitioners often do less, not more.
The lesson: most founders overthink this and underspend on execution. It sounds simple. It's incredibly hard to execute.
Real Talk: What Actually Matters
Here is what actually matters in quantum computing.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on quantum computing. 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 quantum computing in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around quantum computing, GPU shortage, NVIDIA that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in quantum computing, but there are smarter paths.
The strongest teams treat quantum computing 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 quantum computing, 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
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 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: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.