Permitting status for a city AI assistant stays current through event-driven updates rather than nightly batch pulls. What integration pattern preference is this?

Choosing event-driven integration patterns so civic AI context stays fresh as statuses change is the correct preference when permitting status for a city AI assistant must stay current. Nightly batches and static exports create stale answers that mislead residents and staff about permit progress. Event-driven updates—webhooks, messages, or change events from the permitting system—push status transitions into the assistant’s context close to real time, reducing wrong “still pending” replies after approvals. The pattern works because municipal status questions are time-sensitive and stale RAG or cache layers become operational defects, not minor annoyances.

Refreshing permitting context only once a month from a static PDF export fails by concept: monthly static snapshots cannot reflect daily permit movements residents ask about. Relying on staff to paste status updates into the prompt manually each time fails by concept—manual paste does not scale, is error-prone, and bypasses system integration. Caching the first permit status forever to avoid calling source systems fails by concept: immortal caches guarantee incorrect answers after the first change.

Exam caveat: event-driven does not mean every field must stream continuously; it means status changes that matter to answers should propagate without waiting on coarse batch windows. Keep city permitting-assistant framing. Operational check: subscribe to permitting status-change events through governed APIs; invalidate or update assistant context on those events; measure staleness (time from status change to answer currency); and retire month-old PDF exports as the primary freshness strategy.