How to catch AI hallucinations before they reach production

LLMs hallucinate. That's not news. What's underdiscussed is how that failure mode behaves in long working sessions: confident reconstruction that looks fluent, cites specifics, and feels right — until three sessions later when something supposed to be true turns out not to be.

This is week 5 of an 8-week deep dive on CRAFT for Cowork, a structured working environment for Claude. The QA framework treats AI reliability as a measurable engineering problem.

The four gates

CRAFT's verification core is a reusable sub-routine — RCP-CWK-024 — that any recipe can call before reporting a result:

Gate 1: File-pointability

        Can the claim be traced to a specific file?

Gate 2: Read-vs-reconstructed

        Was the data read this session, or recalled from memory?

Gate 3: Lessons-Learned conflict

        Does the claim contradict a documented LL entry?

Gate 4: Untested assumption

        Is this verified or assumed?

A claim that fails any gate gets flagged — visibly to the user, not buried in the answer.

Confidence scoring with decay

Every claim also gets a 0-100 confidence score, graded against a source hierarchy:

• 
  80-100 — Evidence read directly from files


• 
  50-79 — Behavioral observation of tool output


• 
  30-49 — Design intent inferred from documentation


• 
  0-29 — Pure reasoning, no source

A 10-point penalty applies once the session passes 70% token usage — the late-session decay correction. The scoring isn't there to make you suspicious of the AI. It's there to give you a calibrated read on a specific claim.

Real receipts

The framework caught nine Week-1 content files in this campaign that referenced CRAFT as "open source" — incorrect (it's a dual license: BSL 1.1 spec, proprietary content). The factual claim validator flagged the mismatch with documented license language. All nine corrected pre-publication.

The cross-file audit recipe (RCP-CWK-036) runs every 5-10 sessions and has caught ~40% drift in tracking-file state tables. Drift that would otherwise propagate as silent ground truth into every subsequent session.

Try it

CRAFT for Cowork: free public beta on GitHub.

🔗 https://github.com/CRAFTFramework/craft-framework

🔗 License: https://craftframework.ai/craft-license/ (BSL 1.1 → Apache 2.0 on Jan 1 2029 for the spec; proprietary for content)

Last week: device switching across desktop and laptop. Next week: the project structure that makes verification possible.