What context drift actually is
Context drift is what happens when each AI tool inherits a slightly different version of the business, repo, rules, memories, and current mission. Nothing explodes immediately. The outputs just become inconsistent, expensive, and harder to trust.
The real issue is not one weak model. It is a fragmented operating layer.
The five common drift sources
Duplicate rule files
AGENTS, CLAUDE, Cursor rules, and prompt snippets say overlapping but different things.
Stale memories
Old decisions remain in one client while another client never sees the correction.
Tool assumptions
Each tool has a different default for planning, coding, browsing, or memory.
Handoff summaries
Summaries start replacing source truth instead of pointing to it.
Mixed lanes
Research, build, QA, and sales happen in the same bloated thread.
Symptoms founders notice first
- You keep re-explaining the same project facts.
- Different tools contradict each other.
- Token cost rises without better output.
- Old instructions quietly override current decisions.
- You become the manual router and QA layer.
The clean operating layer
Use one portable source of truth for durable rules, one tiny run-state for what is active now, mission briefs for each task, lane separation for workers, and deterministic QA gates before trust.
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