Rohan Paul

New Google paper shows LLM agents handle long tasks better when their workflow lives in an editable procedure graph that learns from execution, instead of being buried in chat history. The problem is: as agents run longer, they can forget where they are, repeat tools, or do steps in the wrong order. Procedural Graphs give the agent a small map of what can happen next, while still letting the LLM reason freely. After runs finish, another LLM compares successes and failures and edits the map, but an edit is kept only if it does not hurt held-out tasks. Across 24 model-and-benchmark combinations, the method ranked 1st or tied 1st in 21. It also repaired a bad human-designed workflow: on MultiChallenge, success went from 58.93% with the flawed graph to 92.86% after refinement. This guidance costs extra tokens, so it makes most sense when long workflows are the bottleneck. Overall, it recommends move critical procedures out of chat history and into an explicit, editable workflow that improves from execution. – arxiv. org/abs/2609.09153 Title: "Procedural Graphs: Self-Evolving Execution Structures for LLM Agents"