AI & Agent WorkflowsOpen accessPublished 3 Oct 2026
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies
(supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent
messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows,
synchronization and consensus, conflict resolution, fault tolerance and retries across agents,
cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment
(queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents,
and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer),
strategy-only whiteboard …
