Prompt Policy
The versioned, tested set of rules and templates that govern how prompts are assembled for an AI workflow — instructions, examples, formatting, refusal patterns, escalation language.
Production AI is not a prompt. It is a system of context, tools, permissions, traces, evals, and feedback loops.
What it is
A prompt policy is the discipline of treating prompts as governed artifacts rather than throwaway strings. Every prompt the system uses has a version, a test suite, a change-review process, and a defined relationship to the synthetic personality and the workflow it serves. The policy is what makes prompt engineering scale beyond one person's tribal knowledge.
Why it matters
Most AI quality regressions come from someone editing a prompt without anyone else noticing. A prompt policy makes those edits reviewable — and tests them against the eval set before they ship. Without one, prompts drift through copy-paste and the system gets worse without anyone being able to point at when.
How it works
Prompts live in source control. Each prompt has tests (invariant probes, regression cases) that run in the eval harness. Changes go through review and the eval gate. Common substrates: a structured prompt library (custom), DSPy programs, or a templating layer above any of the agent SDKs.
Related resources
The discipline of deciding what an AI model sees on every call — instructions, retrieved data, memory, tool definitions, examples — and how to assemble them reliably as the workflow grows.
Before an AI agent can be useful to anyone, it has to be something — a coherent identity that holds up across users, sessions, and adversarial pressure. This is the research track that defines what that means and how to keep it stable.
The test suite your AI workflows have to pass before any change reaches users — measuring quality, latency, cost, and safety on real production data instead of vibes.
The thresholds an AI change must clear before it reaches production — quality, latency, cost, memory, safety — enforced by CI, not by hope.