Context Anchoring is a pattern for reducing drift and repetition in AI-assisted work by externalizing key decisions and context into a living, shared document. Instead of burying goals, constraints, definitions, examples, style rules, and rationale inside ephemeral chats, teams maintain an anchor doc with stable sections/IDs that the AI must reference and cite in responses. This doc is versioned, iteratively refined after interactions, and used across sessions and tools (often via lightweight RAG or explicit prompt links), enabling continuity, faster onboarding, and more consistent outputs. Practical guidance includes starting small, clarifying ownership and review, requiring the AI to flag conflicts or gaps, and avoiding anti-patterns like pasting the entire doc into every prompt, allowing unreviewed AI edits, or letting anchors grow vague/stale.

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