Use fewer prompt tricks. Explain the job more clearly.
Not every request needs examples, chain-of-thought, and a long system prompt. Knowing what information changes the answer is more useful than collecting templates.
A production prompt should make inputs, task, constraints, and output testable. Missing context and workflow errors are not repaired by magical wording.
Write a task contract first
State the job, allowed information, unknown handling, and downstream consumer. Delimit external documents clearly and identify them as data rather than instructions.
Use examples for real ambiguity
Add a few representative examples when labels or formats remain ambiguous, including confusing negatives. Examples consume context and can create imitation bias, so add them for evidence, not ritual.
Release prompts like code
Version prompts, model settings, and regression results. Compare old and new on a representative set and roll out gradually. Avoid changing model, retrieval, and prompt simultaneously.
Pre-release checks
- Task and prohibitions are testable
- External content cannot become privileged instruction
- Changes have versions, evaluation, and rollback
Sources
Related
Writing, extraction, long reasoning, and high-volume support do not need the same model. Cost, latency, privacy, and reliability rarely point to one name.
GPUs, operations, inference tuning, and downtime all land on the same ledger. Self-hosting only makes sense after you have done the math on volume and people.