Practical repository guide
Find and fix AI context drift.
Recognize stale AI coding instructions, review evidence against the repository, and verify updates after code changes.
Check a repositoryPrompterJack editorial · Updated 11 September 2026
What is AI context drift?
AI context drift is the mismatch between repository instructions and the current codebase. An agent may follow the instructions correctly and still make a bad change because the instructions describe an older system.
Look for specific mismatches
Examples include a package manager changed from npm to pnpm, a removed API client still recommended in instructions, a renamed test script, or a tool configuration referencing an unpinned dependency. Each finding needs a code reference and a reason it matters.
Use a repeatable review loop
Inspect the repository and instruction files. Prioritize findings by impact. Review a small proposed update. Run the project checks. Rescan and record what remains unresolved. A score change alone does not prove a fix.
Make upkeep part of changes
Add context review to pull requests that alter architecture or developer workflows. For a fleet, combine scheduled scans with checks triggered by code changes and assign responsibility for unresolved findings.
Questions, answered
Should every detected difference be fixed automatically?
No. Some instructions are intentional constraints or future migration guidance. Review the evidence, preserve deliberate decisions and ask the owner when the meaning is ambiguous.