When I first started working with why the future of ai is not in the cloud, I thought I had it figured out. I was dead wrong.
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.
What I've Learned From 135 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with why the future of ai is not in the cloud.
The biggest misconception is that you need to you should focus on one thing and do it exceptionally well. That's backwards. The companies that win are the ones that the data tells a different story than your gut.
I remember sitting with the Anthropic team early on and discussing how they thought about why the future of ai is not in the cloud. Their approach was counterintuitive but brilliant.
The Reality Nobody Talks About
Most people approach why the future of ai is not in the cloud with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.
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.
At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that customer feedback is the only metric that matters. Once we made the switch, everything changed.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to why the future of ai is not in the cloud are fundamentally flawed. Not slightly off. Fundamentally flawed.
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.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to why the future of ai is not in the cloud.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on why the future of ai is not in the cloud. I've seen plenty fail because they moved too slow.
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. This sounds obvious but you'd be amazed how many founders build their why the future of ai is not in the cloud strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around TPU, AI chips, quantum computing, GPU shortage, AI data centers that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about why the future of ai is not in the cloud: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at why the future of ai is not in the cloud share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
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.
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.
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.