How to build an agent state machine in Pixeltable

A Pixeltable-based task workflow is presented as a deterministic state machine in which each row represents a unit of agent work, with guarded Python transition functions controlling movement through states such as queued, drafting, awaiting approval, and done. Agents may propose actions through HTTP routes or MCP tool wrappers, but database predicates, ownership checks, approval rules, and computed evidence fields determine whether those actions are allowed, preventing models from directly changing state. The walkthrough demonstrates versioned task history, recovery by allowing an agent to resume its own claimed work, draft validation through rule-based or model-judge computed columns, and routes for claiming, reviewing, rejecting, approving, and completing tasks. It also identifies important constraints: Pixeltable serializes writes with table-level locking, lacks exposed compare-and-set operations, can suffer throughput limits and race conditions involving multi-update submissions, and does not provide process recovery, retries, timers, or authentication by itself. For high-throughput queues, durable execution, complex workflow graphs, or crash-resilient agent loops, the discussion recommends pairing Pixeltable with or instead using systems such as Temporal, Restate, DBOS, LangGraph, or queue products, while retaining Pixeltable for stateful artifacts, media, embeddings, and evaluations.

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