Delegation

One agent can't do everything. Delegation is how agents manage complexity. Break a big task into subtasks, assign to specialized agents. A research agent might delegate literature search to a search agent, delegation to an analysis agent, writing to a synthesis agent. Each specialization does what it's good at. The coordination challenge is real though. How do subtasks talk to each other? How does failure in one subtask cascade? What if one agent is much slower than others? Do you wait or timeout? Supervision matters. An intelligent delegating agent doesn't just hand off tasks and disappear. It monitors progress, checks intermediate results, redirects if things go wrong. But that adds complexity. The incentive alignment problem is interesting. If you give agents partial scores for partial work, they might delegate everything. If you give full scores only for complete work, they might hoard and fail. The economic models matter. Delegation models: task decomposition (break into subtasks explicitly), hierarchical (manager delegates to subordinates), peer (equal agents collaborate), opportunistic (agent delegates when it encounters something outside its expertise). Each has different properties. The latency impact is important. Delegation is often serial. Task A starts, it delegates to B, waits for B's result, then continues. That's slow. Parallel delegation is faster but more complex. Three subtasks run in parallel, their results combine. Synap's delegation framework enables agents to break down complex problems, coordinate with specialized agents, and combine results effectively.