Docs drift sentinel
Compare merged changes with the documentation they affect and prepare evidence-backed update tasks.
What this workflow does
Compare merged changes with the documentation they affect and prepare evidence-backed update tasks. It separates observed facts from inference, surfaces conflicting evidence, and delivers a review-ready finding set instead of an opaque answer.
What you gain
Customers and teams encounter fewer instructions that no longer match the product.
What the AI agent changes
How this worked before
Traditional automation could collect records, but a person still had to compare sources, resolve conflicts, and write the conclusion.
What the AI agent changes
The agent can plan a search, inspect multiple sources, distinguish facts from inference, and return a cited report.
Agent trigger
A pull request touching a documented product area is merged.
Inputs
- Process context: merged changes, affected code paths, current docs, ownership, and recent support questions
- Approved policies, ownership, and exception rules
Agent flow
- 1
Collect source material from the approved systems and record its timestamp.
- 2
Cross-check conflicting signals and separate facts from inference.
- 3
Prepare ranked documentation gaps, confidence, exact evidence, and proposed owner with citations, unknowns, and confidence.
- 4
Deliver the approved report and preserve its evidence set.
Human decisions
After step 3
The accountable process owner approves ranked documentation gaps, confidence, exact evidence, and proposed owner.
Outcome
- Reviewed documentation update queue
- Evidence, exceptions, and audit trail
Guardrails
- Label inference separately from observed facts.
- Do not close the investigation while required sources are unavailable.
Risks and mitigations
Missing or stale evidence can produce a confident but incomplete finding.
Show source coverage, conflicts, timestamps, and unanswered questions.
Sources and evidence
Sources establish feasibility or impact. Not every metric comes from an identical implementation.
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The incoming responder regains context faster and fewer risks disappear between shifts.