I spent half a year testing 10 SaaS pricing models, from per-seat to usage-based and hybrids. The model that worked best caught me off guard and helped our company grow in a new way. Here’s the full method and all the data I gathered.
Why Most Approaches Fail
Many common approaches to AI infrastructure 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.
What I've Learned From 47 Companies
A few patterns in AI infrastructure come up again and again.
The founders who handle AI infrastructure well understand that customer feedback is the only metric that matters.
Real Talk: What Actually Matters
Here is what actually matters in AI infrastructure.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on AI infrastructure. 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 AI infrastructure in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around serverless AI, usage-based pricing, AI pricing models, AI infrastructure costs 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 you don't need to get AI infrastructure right on day one. You just need to get started and keep improving.
Founders who do well at AI infrastructure tend to 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
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.
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: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.