The cloud AI world is a mess of hype and broken promises. As a founder, your time is everything. I'm sharing the 5 cloud AI services I'm personally betting my career and company on.
The Framework That Actually Works
Here is a simple framework for evaluating cloud AI services. It's not complicated, but it requires discipline.
Step 1: simplicity beats complexity every time
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the best solutions are often the simplest ones
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 cloud AI services right treat it as an ongoing process, not a one-time project.
The Counterintuitive Truth
In cloud AI services, the best practitioners often do less, not more.
The lesson: customer feedback is the only metric that matters. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
Before deciding anything about cloud AI services, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around AI infrastructure costs, serverless AI, SaaS metrics, AI APIs that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in cloud AI services, but there are smarter paths.
The strongest teams treat cloud AI services 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 cloud AI services, 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 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'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.
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.