Split the Brain: Build an Issue Triage Bot with the Router Strategy

Agentspan’s router strategy separates task classification from specialist execution by using a dedicated router, such as a lower-cost LLM or deterministic Python function, to select the appropriate agent before work begins. The example issue-triage workflow routes bug reports, feature requests, and documentation questions to specialized GPT-4o handlers while a GPT-4o-mini classifier returns only the relevant agent name, reducing costs and making routing explicit compared with the handoff strategy, where a parent model both interprets and delegates tasks. Agentspan supports durable server-side workflows that preserve routing decisions across crashes, provides execution observability through a dashboard, and allows router-based workflows to be combined with sequential pipelines or nested research processes. The strategy concludes an eight-part overview of Agentspan coordination patterns, presenting routing as a configurable option within the same Agent class rather than a separate framework.

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