
Agentic loops, a technique allowing AI to run continuously towards a measurable goal, are now being applied beyond software engineering into knowledge work. NLW and Nufar Gaspar have demonstrated how to structure tasks so that AI agents can self-check and continue working autonomously until completion. This approach involves loop design and graph engineering, enabling agents to function as a cohesive group.
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