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Executive summary

The problem

The internal runbook is hand-maintained and drifts out of date. Truth is scattered across Ansible repos, SharePoint, ServiceNow, Power BI and Teams. Senior engineers lose hours re-deriving and searching procedures — and P1s are slowed by stale runbooks across EMEA, Brazil, China and on-prem.

The proposal

A self-updating Code wiki: when a source changes, Azure OpenAI drafts the documentation update and opens a pull request; a human owner reviews and merges. A weekly drift report keeps documentation debt visible and shrinking. Phase 2 adds an "ask-the-runbooks" assistant.

  •   Pros


    • Runbooks stay accurate — changes become reviewed PRs in minutes.
    • Faster incident response; on-call finds the right procedure fast.
    • Better onboarding; canonical, current map of the estate.
    • One search box across wiki + reports + comms (Phase 2).
    • Extensible: new source = one adapter.
    • Vendor-neutral: pluggable LLM.
  •   Cons


    • Reviewer load — owners must review auto-draft PRs.
    • Prompt/template tuning is a small ongoing effort.
    • Needs a named owner per section (some teams resist).
    • Content debt becomes visible on day one (feature, looks noisy).
  •   Risks (see fixes)


    • AI hallucination → PR-gated + cited + confidence-scored.
    • Confidential leakage → link-only, never sent to the LLM.
    • Runaway cost → quotas + budget alerts + circuit breaker.

    All risks & fixes

Why now, and why this project

It fixes a pain senior+ staff feel weekly, it rides on assets we already own (near-zero cost), and it produces a compounding asset — a clean corpus — that later powers an AI assistant. Ideal first win for the Automation Observatory.