agent orchestration

Shows how MCP enables orchestrating multiple AI agents with clear context about available tools and services

The seven patterns (Parallel, Sequential, Loop, Router, Aggregator, Network, Hierarchical) are specific implementations of agent orchestration strategies.

Programmatic tool calling and multi-agent coordination are explicitly discussed as core improvements for 2026.

Core claim that agent orchestrators manage context, memory, tools, and permissions is central to the article's thesis about orchestration layers.

The planner→executor→verifier pattern is a concrete instantiation of multi-agent orchestration with explicit context routing

The article frames agents as the central pattern for managing context flow and evolution in real systems. Agents are described as both architects and users of context, which is a concrete expression o

Task assignment, dependency tracking, and message passing demonstrate orchestration patterns for multi-agent coordination.

Multi-agent systems are a specific instance of agent orchestration patterns. The article's discussion of handoff mechanisms and context transfer is orchestration implementation.

The question is fundamentally about orchestration—how to coordinate agents to maximize parallelism. This is a higher-order context engineering problem.

Multi-agent systems require orchestration of context and state across multiple agents—central to context engineering patterns.

Proposes specialist agent orchestration as architectural response to context drift—new dimension of agent design

Discusses orchestration patterns (Sequential, Hierarchical, Bi-directional) as component of multi-agent architecture; orchestration determines how context flows between agents.

This is a two-agent pipeline (Fable 5 → Opus 4.8) where output of first agent becomes context for second

The bridge between GBrain and ActiveGraph shows how to orchestrate retrieval and state management; agents are the decision layer that consumes both.

Article explicitly discusses orchestration frameworks and coordination mechanisms as core to multi-agent systems

ReAct agent implementation and tool-calling patterns are core to understanding how context must flow through decision-making cycles.

'How to use agents without losing control' directly addresses agent orchestration boundaries

MCP is presented as the infrastructure enabling orchestration of agents across multiple tools/systems, which requires context management across tool boundaries.

Article describes orchestration layer that decides what to retrieve, how to refine it, and when to iterate—core orchestration function.

Multi-agent coordination (subagents) mentioned as harness design decision; context management foundational to orchestration

Describes agentic architectures as 'specialized agents that coordinate, call tools and maintain their own memory/context' - explicit context preservation across interactions

The entire article is about orchestrating multiple agents with defined roles and sequential task flow. This is the core pattern being taught.

Articulates that agent failure is orchestration (what to do next) not execution (doing it). Orchestration is context-dependent decision-making.

The Agent SDK's mcp_servers parameter shows how context infrastructure enables multi-agent orchestration by providing shared context sources.

Introduces hierarchical orchestration pattern (lead agent + sub-agents) as specific orchestration strategy that measurably reduces hallucinations (71% improvement).

Article directly implements orchestration pattern using LangChain; shows how agents coordinate via orchestration layer

The article explicitly discusses agent architectures and orchestration patterns, which is a core component of multi-agent context engineering.

Article demonstrates CrewAI orchestration of multiple agents with distinct roles in a coordinated workflow

Harness design is presented as critical infrastructure for agent work coordination and context provisioning

The researcher/writer pipeline demonstrates sequential agent orchestration with context flow between specialized roles

Tool composition and state management are core agent orchestration patterns. The composite tools pattern is a specific orchestration strategy.

This is a lesson in why agent orchestration requires isolation and cleanup protocols. Multiple agents (Claude Code, Codex) sharing hooks on the same machine created unintended coupling and performance

By standardizing context access, MCP removes friction from multi-agent coordination and complex tool chains—enabling orchestration patterns.

Shift from isolated CLI to remotely-orchestrated nodes is a multi-agent coordination pattern allowing external steering and observation

Multi-agent patterns (subagents) are mentioned as one harness design decision, suggesting orchestration flows through context management.

Compares three orchestration patterns (independent, decentralized, centralized) and quantifies their failure modes.

The orchestrator rule (read journal first) is a coordination pattern that improves multi-cycle agent behavior

Describes a specific orchestration pattern for multi-agent systems: surround agents with constraints rather than trying to manage their code directly.

Main agent + background subagent is a multi-agent orchestration pattern with specific context responsibilities

The pattern of agents rewriting agent architecture is a form of multi-agent orchestration where an agent's role is to optimize other agents' design. This is a novel orchestration pattern.

Modular agents are a specific orchestration pattern; building multi-module agents requires coordinating context flow between modules

Curriculum covers 'orchestration' as core component alongside tools, memory, and evaluation—suggests context engineering enables effective multi-tool coordination.

Author describes specific orchestration strategy: single coordinator managing multiple agents rather than parallel independent agents

Designing loops implies orchestration of multiple prompting steps; this is a prerequisite for multi-agent patterns.

LangGraph is presented as a tool for creating agent runtimes with directed and cyclic graphs, which is agent orchestration in practice

Standardized MCP communication is foundational for orchestrating multiple agents with consistent tool access patterns.

Service registration for agents IS a form of orchestration pattern—managing how agents discover and interact with external capabilities.

Self-modifying compaction adds a meta-layer to agent architecture—agents managing their own context parameters

Reveals a failure mode in naive agent orchestration: lack of persistent execution context management.

Multi-agent systems are inherently about orchestrating multiple agents; the article likely discusses coordination patterns