The method
Start with an operational process and identify the sources, responsibilities and decisions at each stage. Give specialist workers distinct review questions, a shared source context and an explicit output contract. Reconcile their available findings rather than assuming every branch succeeds.
Use fictional source packs to compare fuller and deliberately incomplete receiving contexts. Retain the actual worker outputs, inspect the structured fields separately from the prose, and replay deterministic source checks without rewriting the original response.
What the work shows
A recorded hosted-AI experiment exposed a mismatch between cautious prose and actionable fields: a worker warned that updates were missing but returned an older deadline and budget ceiling in fields labelled current. The source-manifest correction cleared unsupported current fields in the downstream projection while preserving the received values and raw response.
Source retrieval can resolve missing facts without resolving the whole decision. In more complex development cases, workers disagreed about whether updated sources and approved scalar values also established that finished documents had been reconciled. That disagreement remains part of the result.
Interpretation and limits
The recorded experiments use authored fictional cases, including a deliberately incomplete context condition. Source coverage does not prove correct interpretation, and matching a local integrity record is not independent authentication.
The next test
Develop independently reviewed cases and separate source availability, field currentness and finished-package readiness in the scoring. Compare useful completion and reviewer effort alongside unsupported decisions.