Field notes
LLMsEngineering

Production LLM Integration Beyond the Demo

Engineering boundaries, evaluation, observability, and failure handling for useful LLM features.

Constrain the model’s role

Define what the model may propose, which tools it may call, what must be validated, and which actions require explicit confirmation. Typed tool contracts matter more than elaborate persona prompts.

Evaluate outcomes

Latency and token cost are easy to measure. Usefulness, groundedness, recovery behavior, and unsafe action rates need curated scenarios and ongoing review.

Observe the whole interaction

Trace prompts, tool calls, validation results, model versions, timing, and user-visible failures—with privacy boundaries designed in from the start. Production AI becomes manageable when failures are inspectable.

Draft article placeholder: replace generic guidance with reviewed production examples before publication.