Agent architecture switchyard

Route the same work through six agent topologies

Agent architecture decides where control lives, which contexts are shared or isolated, how work can run in parallel, and where messages cross a boundary. More agents do not automatically produce a better system.

Keep the teaching workload fixed while switching topology. The simulator counts the labeled model nodes, longest sequential chain, explicit messages, and isolated contexts—without inventing a universal quality score.

A switchyard of single-agent, router, fan-out, orchestrator, evaluator, and handoff topologies
Agent architectures · Control flow shapes calls, messages, and failure domains
Six patterns
Single · router · fan-out · orchestrator · evaluator · handoff
Exact counts
Calls · critical depth · messages · contexts
Not predicted
Quality · latency · price
Topology simulatorOrchestrator + workers
goalorchestratordecomposeworker 1isolated contextworker 2isolated contextworker 3isolated contextworker 4isolated contextsynthesize
Model calls61 plan + 4 workers + 1 synthesis
Sequential depth3longest call chain
Messages8explicit inter-node transfers
Contexts5isolated working windows

Exact counts for the labeled teaching graph above, assuming one model call per node. They are structural counts—not quality, latency, or price predictions.

Primary research

Inspect the mechanism at its source.

Project architecture and terminology were checked against official documentation on August 10, 2026. Research papers are linked to their original publication records.

Composable production patternsBuilding effective agentsOriginal source ↗Orchestrator-worker implementationMulti-agent research systemOriginal source ↗Multi-agent conversation framework paperAutoGenOriginal source ↗Isolated child-agent contextsHermes delegationOriginal source ↗Isolation and deterministic bindingsOpenClaw multi-agent routingOriginal source ↗

Keep experimenting

Change the layer, keep the system visible.

AI Lab indexSee every interactive laboratoryBrowse the suite →Transformer microscopeGo beneath the agent runtime into the modelInspect the matrices →