Which orchestration framework should I use?

Match the framework to the workload's shape. For complex, auditable, Human-in-the-Loop (HITL) stateful workflows: LangGraph—graph execution with Checkpointing (Agent State). For the fastest multi-agent prototype: CrewAI's crews. For low-friction GPT-centric agents: the OpenAI Agents SDK. For Azure/.NET or if you were on AutoGen/Semantic Kernel: the Microsoft Agent Framework. For Claude, single-agent, minimal overhead: the Claude Agent SDK. Start with the simplest framework that meets your needs.

Do I need a framework to build an AI agent?

No. Simple agents (single LLM call + tool use) can be built with direct API calls in 50-100 lines of code. Frameworks add value when you need: persistent memory across conversations, durable multi-step workflows with error recovery, coordination between multiple agents, or production observability. Adopt one when the plumbing it removes exceeds the abstraction it adds.

AI Agent Orchestration Framework

Written by Max Zeshut

Founder at Agentmelt · Last updated Sep 9, 2026

A software framework that provides the building blocks for creating, coordinating, and managing AI agents—including prompt management, tool integration, memory persistence, multi-agent coordination, error handling, and observability. The five that matter for production in 2026 are LangGraph (graph-based, durable state), CrewAI (role-based crews), the OpenAI Agents SDK (handoffs + hosted tools), Google ADK (Gemini/Vertex-native), and the Microsoft Agent Framework (the GA'd merger of AutoGen and Semantic Kernel — standalone AutoGen is now maintenance-only). These frameworks abstract common infrastructure patterns so developers focus on agent logic rather than plumbing.

Frequently asked questions

Which orchestration framework should I use?: Match the framework to the workload's shape. For complex, auditable, Human-in-the-Loop (HITL) stateful workflows: LangGraph—graph execution with Checkpointing (Agent State). For the fastest multi-agent prototype: CrewAI's crews. For low-friction GPT-centric agents: the OpenAI Agents SDK. For Azure/.NET or if you were on AutoGen/Semantic Kernel: the Microsoft Agent Framework. For Claude, single-agent, minimal overhead: the Claude Agent SDK. Start with the simplest framework that meets your needs.
Do I need a framework to build an AI agent?: No. Simple agents (single LLM call + tool use) can be built with direct API calls in 50-100 lines of code. Frameworks add value when you need: persistent memory across conversations, durable multi-step workflows with error recovery, coordination between multiple agents, or production observability. Adopt one when the plumbing it removes exceeds the abstraction it adds.

See it as a workflow

Automated Code Review Workflow

Trigger, steps, n8n nodes, guardrails and an importable template — plus what it costs to have it built.

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Workflows from $197/month, custom agents from $2,000.

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