Start with a task that has an answer key
Triage is a practical starting point. Ask a model to label crash reports against an existing taxonomy, link candidate duplicates, and quote the evidence it relied on. Measure it against a set labeled by the team before creating any automation. A plausible summary alone does not show whether the label was right.
Follow the same route for retrieval, QA notes, and design documentation. The output should be easy to verify and cheap to reverse. This turns prompt changes into an engineering comparison instead of a taste contest.
Keep gameplay authority in the simulation
A model might propose dialogue, but inventory, quest flags, cooldowns, rewards, and multiplayer state belong to authoritative game code. Return a constrained response such as a candidate line and a small enumerated intent. Validate intent against game state and route it to a reviewed fallback when it is invalid.
The practical reason is replayability. Given the same authoritative input and state, a save, bug replay, or multiplayer client should agree on what happened even if a model service is slow or unavailable.
Treat latency, cost, and data as design inputs
Budget the request at the level of a whole session, including failures and retries. Stream or cache suitable draft content away from the critical gameplay path. Set a deadline after which the game chooses its default rather than waiting. Use scoped data: test identifiers and the relevant lore passage are more useful than a raw dump of player details.
Write evaluations that can surprise you
Include published lore collisions, prompt injection in imported notes, missing context, malformed structures, and contradictory tool output. Report correctness separately from style and review failures by category. Keep a small set that runs on every change and a larger set for releases. Expand the capability only after you know what regression would force a rollback.