What we learn shipping AI systems, computer vision, and automation into production — written for the engineers and operators who have to run them.
The demo works, the pilot stalls, the rollout quietly dies. Four failure modes we see in almost every agent project — and what a system that survives contact with real users looks like.
You do not need an evaluation platform. You need fifty cases, a runner, and the discipline to look at the output before you ship.
Confidence, sources, and the moment a system should admit it does not know — interface patterns for products whose output is probabilistic.
Chunk, embed, search, stuff into a prompt. That pipeline gets you a convincing prototype and a support queue full of confidently wrong answers. Here is what we build instead.