Why every AI agent framework eventually reinvents a workflow engine
Responsible-Dare5139 · reddit · 2026-10-14
An architectural argument: once an agent must survive its host process — documents retrieved, APIs called, waiting on human approval — 'rerun the prompt' stops being a valid recovery strategy, and you need durable state, retries, and resumability, i.e., a workflow engine. LangGraph, Temporal, and custom queue+DB setups are converging on the same questions; Diagrid Catalyst's answer is to keep the agent framework and put durable execution underneath, though side effects still need explicit idempotency. Open question: should the agent framework own the durable lifecycle, or integrate with an execution system that also runs non-AI jobs?
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