Orchestrating Multi-Agent Swarms: Beyond Simple Chains
Moving from linear pipelines to dynamic state machines where specialized LLM agents negotiate and delegate tasks autonomously.
Simple LLM pipelines fall short when handling complex, non-linear workflows. By modeling agents as nodes in a state machine, we can let them run self-correcting loops, audit each other's outputs, and run tools conditionally.
We break down state consensus patterns, task routing mechanisms, and how we handle token usage budget limits inside autonomous developer agents.