The teams shipping the best AI features in 2026 mostly aren't ML teams. They're product teams with a clear use case and a fast loop from idea to user feedback.

Start with the narrowest valuable task, wrap a strong general model, and only get fancy when the data tells you to.

A pragmatic starting stack

Pick one task, one model, and one evaluation you can run on every change.

  • A frontier model behind a thin API layer
  • Retrieval over your own docs for grounding
  • A handful of golden test cases you grade on each deploy

Avoid the common traps

Don't fine-tune first โ€” prompt and retrieval get you 80% there.

Don't ship without an eval; vibes don't survive contact with real users.

The Bottom Line

Treat AI features like any product bet: smallest useful slice, measured, then expanded.