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Every ticket as the root of its provenance graph — goal, patch, approval, runs and (as the ticket-class build lands) mandate, manifestations, guarantees, journey, artifacts and children. Rendered through the <<<TicketGraphList>>> tag.

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REQUESTED#172 jazz-agents

Research: model the ticket-authorization lifecycle as a LangGraph state machine

goal

Investigate whether/how LangGraph replaces pair_loop.py's hand-rolled control flow. Current lifecycle: brake(stops) -> register pair -> assign -> ACTIVE -> work -> validate -> settle(DONE|respawn) -> harvest. Map each to LangGraph nodes/conditional-edges with: (a) persistent CHECKPOINTING (resume a ticket killed mid-run), (b) human-in-the-loop INTERRUPT (the wallet-signed approval gate), (c) conditional edges (pass->settle, fail->respawn, dry-count->stop). Key question: LangGraph's checkpoint/state vs our DB-as-source-of-truth (append-only ticket_events) — complement or duplicate? OUTPUT: node/edge diagram + recommendation (adopt LangGraph wholesale, or keep pair_loop and use LangGraph only for local-model flows). Cite LangGraph checkpointer + interrupt docs. Spawns a build ticket.

patch

none

approval

unapproved

runs

no runs recorded

mandate (clauses)

not yet recorded — lands with the ticket-class build

manifestations

not yet recorded — lands with the ticket-class build

guarantees

not yet recorded — lands with the ticket-class build

journey (blunders & successes)

not yet recorded — lands with the ticket-class build

artifacts (forge)

not yet recorded — lands with the ticket-class build

source (forge tree)

browse congruency source (forge-parked tree)

children

#177 Build: LangGraph orchestrator for the ticket-authorization lifecycle (spawned · DONE)