Practical architectures for agentic systems — from simple chains to full mesh.
Building an agentic system means deciding how agents communicate, who controls the flow, and what happens when an agent fails. These patterns are the building blocks.
The simplest pattern. Agent A passes its output to Agent B, which passes to Agent C. Each agent has a single responsibility. Works well for linear pipelines — extract, transform, validate, output.
Pros: simple to debug, predictable latency.
Cons: any agent failure breaks the chain; no parallelism.
A supervisor agent delegates subtasks to worker agents and aggregates their output. The supervisor decides the routing and can retry failed workers, switch strategies, or escalate.
Pros: central error handling, clear authority.
Cons: supervisor is a bottleneck and a single point of failure.
Agents broadcast and subscribe to topics. Any agent can publish results or request help. No central coordinator — the system converges through peer coordination.
Pros: fault-tolerant, naturally parallel.
Cons: hard to debug; can produce redundant or contradictory outputs without careful design.
Combine patterns. A supervisor delegates to sub-teams that internally use mesh coordination. Or a chain ends with a verifier agent that can loop back to an earlier stage.
Most production systems are hybrids. The question is not which pattern but where each pattern applies.
Start with the simplest pattern that could work. Add complexity only when you have evidence that it's needed.