Four agent frameworks, four philosophies, one decision. The choice isn't which is "best" — it's which fits the shape of the workflow you're building.
Agent framework debates are FOMO-driven. Each framework is good at something, and the decision is matching the framework's strength to your workflow's shape — not chasing the one with the most stars.
The Issue Tree: What Each Is Good At
- **CrewAI.** Role-based, opinionated, fast to ship multi-agent "crews." Wins on simplicity and time-to-demo; loses on control.
- **Agno.** Performance-oriented, lightweight, component-based. Wins on speed and flexibility; loses on the opinionated ergonomics.
- **LangGraph.** Graph-based, explicit state, full control. Wins on complex stateful workflows; loses on simplicity.
- **OpenAI Agents SDK.** First-party, minimal, model-tied. Wins on simplicity and OpenAI integration; loses on portability and control.
The Pattern: Match the Framework to the Workflow
The pattern behind the choice: pick the framework whose abstraction matches your workflow. Role-based crews → CrewAI. Performance and components → Agno. Complex stateful graphs → LangGraph. Minimal, OpenAI-first → OpenAI Agents SDK.
- Simple multi-agent, fast: CrewAI or OpenAI SDK.
- Performance-critical, flexible: Agno.
- Complex stateful workflows: LangGraph.
- OpenAI-only, minimal: OpenAI SDK.
What to Refuse
- Choosing the framework with the most stars.
- Choosing for a future workflow you don't have yet.
- Choosing a complex framework for a simple workflow (and vice versa).
- Choosing without a prototype in two of them.
The Real Question
The real question isn't which framework — it's whether you've prototyped your actual workflow in two of them and compared. The framework that fits shows up in the prototype, not in the comparison table. See when to roll your own (/blog/when-to-roll-your-own-agent-framework) for when none of them fit.
Conclusion
CrewAI, Agno, LangGraph, and OpenAI Agents SDK are four philosophies, not four ranks. Match the abstraction to your workflow, prototype in two, and choose the one that fits the shape of what you're building.
About FACTA
FACTA helps startups and growth-stage teams turn AI into production systems that keep running — not demos that impress once.
We design the architecture around the parts that actually break under real usage: tooling you own, credentials you control, failover, cost controls, observability. The boring infrastructure that keeps a system alive after launch.
Led by Matías Baglieri and Carolina Fogliato, we focus on one thing:
AI leadership that builds. Not just advises.
Tell us your workflow's shape.
We'll tell you which two frameworks to prototype in. See CrewAI vs Agno vs LangGraph for the earlier comparison.
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