I didn't go to business school. I learned how to build companies from the trenches. After countless mistakes and a few lucky breaks, I've distilled my experience into these 7 hard-won lessons. This is the stuff they don't teach you in books.
What I've Learned From 49 Companies
Across 234 angel investments, including Anthropic, a few patterns in AI product development come up again and again.
The founders who handle AI product development well understand that simplicity beats complexity every time.
The Framework That Actually Works
Here is a simple framework for evaluating AI product development. It's not complicated, but it requires discipline.
Step 1: your team matters more than your technology
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: you need to move fast and break things
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 AI product development right treat it as an ongoing process, not a one-time project.
Real Talk: What Actually Matters
Here is what actually matters in AI product development.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on AI product development. 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 product development in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around entrepreneurship, ai product management, scaling that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in AI product development, but there are smarter paths.
The strongest teams treat AI product development 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 AI product development, 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:Are these recommendations still relevant in 2026?
Absolutely. While specific tools and tactics change, the underlying principles remain consistent. I update my thinking regularly based on what I'm seeing in the market and across my portfolio companies.
Q:Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
Q:How do I know which items apply to my situation?
Start by honestly assessing where your biggest bottleneck is right now. The items that address that specific constraint will give you the highest return on your time and energy.
Q:How were these items selected?
Each item on this list comes from direct experience, either from building my own companies or from patterns I've observed across the 234 startups I've invested in. I prioritize practical, actionable items over theoretical concepts.