From Conversation to Project Core
Generating durable operational memory from captures, decisions, work, and evidence
Project memory in contemporary AI systems is usually implemented as transcript history, retrieved snippets, generated summaries, or opaque vendor memory. These forms preserve language but often fail to preserve operational distinctions: a proposal versus a decision, a worker return versus verification, a completed tool call versus human acceptance, an obsolete specification versus the active one.
Generated Operational Memory is the process of compiling raw conversation, files, tool events, and human decisions into typed durable project state. The target object is a Project Core: an event-sourced record of accepted truth, plans, constraints, permissions, artifacts, work orders, returns, evidence, receipts, dependencies, and unresolved questions. Models receive scoped views of the Core and may propose patches; no provider transcript becomes the sole authority.
The architecture preserves immutable capture, explicit promotion of intent, non-destructive accepted and working results, dependency-driven staleness, and reopen-from-state behavior. It treats memory generation as a governed compilation problem rather than a summarization feature.
Current evidence state
SPECIFIED
This label describes the strongest public-safe state of the specific paper claims. Open the paper's claim ledger for claim-level distinctions and limitations.
Publication
- Full paper:
/papers/p08-generated-operational-memory - Claim ledger:
content/papers/p08-generated-operational-memory/claim-ledger.json - Source manifest:
content/papers/p08-generated-operational-memory/source-manifest.json - Diagrams: 4
- Approximate body length: 1,509 words
Demonstrations
d07-cas-native-work-orderd14-workpage-generator
Benchmarks
b09-workpage-os
Public boundary
The research entry publishes a public-safe architecture and evidence record. It does not grant implementation rights or expose restricted claim-ready material.