Small Models, Big Systems

Model quality matters, but the product around the model decides whether the feature feels reliable. The strongest AI systems usually look less like a single prompt and more like a chain of ordinary engineering choices.

Inputs are normalized. Context has a budget. Outputs have a schema. Risky operations require a second check. Logs tell you what happened without leaking what should stay private.

Constraints Are Product Surface

Users notice when a system knows what not to do. A narrow tool can feel smarter than a general one because it has a clear contract. It asks for the right data, uses the right vocabulary, and stops at the boundary of its responsibility.

That boundary is not a limitation. It is part of the interface.

Build The Harness

The harness is where a model becomes a feature: fixtures, evals, retries, fallbacks, and traces. None of it is glamorous. All of it compounds. When behavior changes, the harness lets you see if the change is improvement, noise, or regression wearing a nice hat.