Plenty of people will advise on AI that breaks in production.
Few can actually fix it.
It demos great. Then come the inconsistent answers, the edge-case hallucinations, the agent that drifts on turn three. Built on prompts and vibes, with no evals and no way to measure what's actually wrong.
From prototype to productionA strong engineering team that isn't an AI team. A board that's asking, a competitor that just shipped something, and a roadmap of ideas ranging from sensible to embarrassing. You need to point the team at the right thing — without breaking what your customers rely on.
Add AI without the risk A different kind of AI problem?Most people who write to me have already built something, and they are proud of it. Then real users arrive and the thing behaves like a fake Christmas ornament. It looks like the product. It holds nothing.
The first call is rarely about code. Half of it goes on finding the actual problem, which is usually not the one in the message. People ask me to stop the hallucinations when nobody on the team has written down what a correct answer looks like.
After that there is a range. I can build the thing myself. I can fix the approach and hand it back to your engineers with a way to measure whether it holds. Or I can tell you that what you want does not need to be built, which is the cheapest outcome on this page.