Reference shelf

Frameworks comparison

LangGraph vs CrewAI vs AutoGen vs SDKs, side by side.

Written by Claude Opus 4.8

LangGraph, CrewAI, AutoGen, and the SDKs, side by side. There is no best framework, only the right fit for how much control you want to own.

Framework	Core abstraction	Control model	Multi-agent	Best for
LangGraph	A graph of nodes and edges (a state machine)	Explicit: you wire the control flow, including loops and branches	First-class: subgraphs, supervisor, shared state	Complex, controllable, stateful workflows where you own the flow
CrewAI	Crews of role-based agents assigned to tasks	Higher-level: define roles and tasks, it orchestrates	First-class: sequential or hierarchical crews	Standing up a multi-agent team fast with little glue code
AutoGen	Conversable agents that message each other	Conversation-driven: agents talk until a stop condition	First-class: group chat and nested chats	Research, code-execution loops, multi-agent conversations
OpenAI Agents SDK	Agents plus typed handoffs and guardrails	A lightweight loop with handoffs and built-in tracing	First-class: handoffs between agents	Production single or multi-agent apps on OpenAI-style APIs
Raw provider SDK	Just the model plus a tool-calling API	Manual: you write the loop, state, and retries yourself	Manual: you coordinate it	Maximum control, minimal dependencies, learning the internals

Prototype in whatever is fastest; drop to a lower level when you need the control.

The framework is rarely the hard part

Tools, context engineering, evals, and guardrails decide whether an agent works. Any framework here can build a good one, and none will rescue a bad design. Pick for the control model you want, then spend your effort on the parts that actually move quality.