Agent Loop vs Graph Engineering

Agent loops and graph engineering are not opposites; they operate at different levels.

• 𝗔𝗴𝗲𝗻𝘁 𝗹𝗼𝗼𝗽: a simple, single-node, sequential “think-act-observe” cycle with implicit control and continuous context.
• 𝗚𝗿𝗮𝗽𝗵 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: a higher-level orchestration layer that connects agents, code, tools, and humans through explicit nodes, typed edges, and managed state.

𝗠𝗮𝗶𝗻 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀

• 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: loops are open-ended; graphs are bounded and explicit.
• 𝗦𝘁𝗮𝘁𝗲: loops keep history in one transcript; graphs use schemas, reducers, and checkpoints.
• 𝗙𝗹𝗼𝘄: loops are sequential; graphs can branch, parallelize, and route conditionally.
• 𝗙𝗮𝘂𝗹𝘁𝘀: loop failures can derail the whole process; graph failures are localized.
• 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: graphs support auditability and approval gates.

𝗧𝗿𝗮𝗱𝗲-𝗼𝗳𝗳𝘀

• 𝗔𝗴𝗲𝗻𝘁 𝗹𝗼𝗼𝗽𝘀 are better for exploratory, unpredictable tasks and quick setup.
• 𝗚𝗿𝗮𝗽𝗵 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 is better for predictable workflows, compliance, recovery, parallelism, and human approval.

𝗥𝘂𝗹𝗲 𝗼𝗳 𝘁𝗵𝘂𝗺𝗯

• Use an 𝗮𝗴𝗲𝗻𝘁 𝗹𝗼𝗼𝗽 for short, flexible, context-dependent tasks.
• Use 𝗴𝗿𝗮𝗽𝗵 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 for long-running, high-stakes, or multi-step workflows that need structure, recovery, and control.