// Choice · Choose tools and avoid pitfalls
Choosing an agent framework: LangGraph, OpenAI Agents SDK, Pydantic AI, CrewAI, Mastra
No framework is best in general; it depends on language, how much flow control you need, which models you use and how you deploy. We have not run a unified test; these are the questions to ask.
verified 2026-10-100 official sources
Scenario: Choose tools and avoid pitfalls →
Symptoms
- There are too many frameworks to know where to start
- Halfway through, the abstractions are too thick to debug
Common causes
- The most popular framework was picked before the requirements were clear
How to fix
- Decide the language first: TypeScript teams can look at Mastra and others; Python teams have more choice
- Flows that need explicit state, branching and human-in-the-loop: look at graph/state-machine frameworks like LangGraph
- Lightweight and close to one vendor’s native features: look at vendor SDKs like the OpenAI Agents SDK, and check support for other vendors’ models
- Type safety and structured output matter: look at Pydantic AI
- Multi-role collaboration prototypes: consider CrewAI
- Build the same small task in 2–3 candidates and compare code size, debugging and observability support, then check maintenance status in our profiles
Compiled from official documentation and public discussions on 2026-10-10; not yet reproduced in our own environment. Follow the official docs if they differ.