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Graph Engineering: A practical guide to building agents that branch, verify, recover and stop
Your agent follows the prompt perfectly. It still fails. One researcher misses the source. A second repeats the same mistake. The reviewer sees a polished answer and approves it. By the time the result reaches you, nobody can explain which decision poisoned the run. That is not a prompting problem. It is a control-flow problem. Graph Engineering is the practice of designing the shape of an AI job before asking models to execute it. You decide what can run in parallel, what must wait, what evidence crosses between steps, where failure goes, and which decisions still belong to a human.…
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