Parallel / Swarm / Networked Architectures

Contrast with supervisor: no central decider. Agents read a shared event bus, pick up work asynchronously, write results back. LangGraph explicitly supports "Swarm Architecture" for decentralized, dynamic environments. Matrix (arXiv:2511.21686) represents both control and data flow as serialized messages passed through distributed queues to eliminate the orchestrator bottleneck. The tradeoff is explicit: determinism and traceability for scalability. Swarm fits tasks with many independent sub-problems; it does not fit tasks that need a single coherent plan.

Learn + Build 1.3 hr Python (stdlib, `threading`, `queue`)

Prerequisites: Phase 16 · 05 (Supervisor Pattern), Phase 16 · 04 (Primitive Model)

#Problem

Supervisor scales to a few workers. What about hundreds? The supervisor itself becomes the bottleneck: every decision about who does what funnels through one agent. One slow plan step stalls the whole system.

Swarm architectures flip the design. Instead of a central planner dispatching work, workers pick work off a shared queue. The "coordination" is baked into the event bus semantics. No orchestrator; the system scales until the queue does.

#Problem

Keep going. The rest of this lesson is one step away.