orchestration patterns

Compares five distinct orchestration models (chain-based, graph-based, retrieval-centric, pipeline-based, role-based, planner-based) as core framework differentiator

Post explicitly identifies orchestration as one of five core design components in Compound AI Systems

Introduces orchestrator-worker pattern for multi-agent coordination as architectural approach to managing context flow across specialized agents.

Course teaches 'orchestrate complex workflows' as explicit skill, indicating orchestration is moving from theory to teachable practice.

Supervisor-subagent pattern is a specific multi-agent orchestration architecture with context management implications.

Reference architecture (Router → Orchestrator → Specialists → Synthesizer → Checker) is specific instantiation of orchestration pattern with explicit context management layers

The six patterns (sequential, parallel, hierarchical, etc.) are orchestration approaches that directly affect how context flows between agents

The three-layer orchestration model (orchestrator → agents → coordination layer) is a fundamental pattern for how to structure agent systems to manage context flow and task decomposition.

Subagent architecture is a specific orchestration pattern where context flows hierarchically through a central orchestrator. The analysis of its overhead/control tradeoff extends understanding of orch

The orchestration section describes control flow, routing, workflows, and message queues—a practical taxonomy of orchestration concerns for multi-agent systems.

Solution explicitly handles orchestration tool (ntm) as special case, showing orchestration state must be managed separately from interactive sessions

MCP enables more sophisticated orchestration patterns by providing context awareness, vs stateless function calling which limits orchestration complexity

This adds a specific architectural pattern: loop-based orchestration is a meta-level context management strategy above individual agent prompts

LangGraph's graph-based node/edge model is a specific orchestration pattern for managing agent sequencing and information flow.

The hybrid approach (CrewAI task nested in LangGraph node) is a multi-level orchestration pattern. Shows composability of abstractions.

LangGraph's graph-based architecture is an orchestration pattern for coordinating how agents process and act on context; relates to multi-agent coordination