> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mindset.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Drift Detection

> The mechanism that kills the wiki. Agents detect when blueprints disagree with reality, and flag it as a first-class event.

## The Feature That Kills the Wiki

Every wiki, every Confluence space, every README in every repository shares the same fate: someone changes the system, doesn't update the docs, and now the docs are actively harmful. This is an unsolvable problem in a human-maintained knowledge base because the maintenance cost is invisible and the consequences are delayed.

In a system where AI agents are both the consumers and producers of knowledge, drift detection becomes possible, and automatic.

## Four ways drift gets detected

<CardGroup cols={2}>
  <Card title="Agent-reported drift" icon="flag" iconType="solid">
    When a coding agent loads a blueprint and discovers the code doesn't match what the blueprint says, it flags the inconsistency. This happens naturally as part of the execution plan step. The flag is a first-class event in the system, not a comment someone might miss.
  </Card>

  <Card title="Decision-triggered review" icon="code-pull-request" iconType="solid">
    When a decision is resolved that affects an existing blueprint, the system marks that blueprint for review. A human or AI agent updates it. Until it's updated, the blueprint carries a staleness warning that agents can see.
  </Card>

  <Card title="Implementation-triggered review" icon="code" iconType="solid">
    When a work item is completed that modifies files governed by a blueprint, the system prompts: *"WI-4 modified the deployment pipeline. Blueprint `deployment` may need updating."*
  </Card>

  <Card title="Scheduled audits" icon="calendar" iconType="solid">
    An agent periodically reads each blueprint, compares it against the actual codebase, and reports drift. This is a background operation that runs continuously, not a quarterly documentation review that never happens.
  </Card>
</CardGroup>

<Tip>
  **The result: institutional knowledge that is current by default, not by heroic effort.**
</Tip>

This is the point Memex AI's bet rests on. If you've ever inherited a codebase with a wiki that lied to you, or joined a team where the onboarding doc referred to a repo that was archived eighteen months ago, you know why.