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. 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. No orchestrator. Each worker repeats: pull a task, process, write result (and optionally enqueue follow-ups). Many independent tasks. Scraping, transforming, classifying. Tasks do not depend on each other. Variable-duration work. If some tasks take 100ms and others take 10s, a swarm balances load automatically — fast workers pull next jobs. A supervisor has to anticipate duration. Throughput over determinism. You care about total completion time, not strict ordering. Ordered workflows. If step 3 needs step…
Parallel / Swarm / Networked Architectures: Contrast with supervisor: no central decider. Agents read a shared event bus, pick up work asynchronously, write…
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