assumption-graph-loop

Automate belief revision by running the assumption-graph-loop to fuse AI annotations and research claims into a temporal assumption graph. It continuously updates the persistent belief log by appending a BeliefEvent whenever a claim's verdict changes.

A temporal assumption graph in AI governance tracks evolving beliefs over time. It fuses AI annotations and research claims to maintain a current belief log, ensuring persistent assumptions are continuously revised as new evidence emerges.

Update a persistent belief log after deep research by running the assumption-graph-loop. It ingests the latest research claims and AI annotations, fuses the evidence, and appends BeliefEvent entries for any claims whose verdicts changed since the previous run.

Yes, you can run this belief log revision loop before a review to ensure your assumptions reflect the latest code and research evolution. It prepares the persistent belief log by fusing new AI annotations and research claims.

No, the assumption-graph-loop operates without external dependencies. It relies entirely on its internal scripts and references to fuse evidence and automate the belief revision process.

The best way to maintain a current belief log is to automate the revision loop. By consistently fusing AI annotations and research claims into the temporal assumption graph, the persistent belief log stays synchronized with evolving code and research.