If I were starting an AI company today — with everything I know from building 250+ systems…

here's exactly what I'd do.

Week 1-2: Talk to 50 potential customers in a specific vertical. Not "people who might use AI" — people with a specific expensive problem. Listen more than you pitch.

Week 3-4: Build the simplest possible solution using existing models (not training your own). Fine-tuned open-source model + good prompt engineering + solid UX. MVP, not masterpiece.

Month 2: Get 5 paying customers. Even at $500/month. Revenue validates the problem exists and people will pay to solve it.

Month 3-6: Iterate furiously based on customer feedback. Build the custom ML only where it creates genuine differentiation. Use off-the-shelf for everything else.

Month 6-12: If you have 20+ paying customers and strong retention, raise seed funding. If not, pivot or kill the idea.

The mistakes most AI founders make: building technology before validating the problem. Training custom models when fine-tuning works. Hiring 10 engineers before finding 10 customers. Targeting horizontal markets instead of specific verticals. Spending 6 months on "stealth mode" instead of shipping.

The AI startup opportunity in 2026 is extraordinary. The tools are mature. The market is hungry. The funding is available.

But the playbook is the same as every startup: find a painful problem, build the simplest solution, and iterate with customers.

The AI is the implementation detail. The problem is the business.