10 Ways to Critically Evaluate and Select the Right Multi-Agent Framework

What makes a multi-agent framework good or useful?

In a world crowded with dozens of multi-agent frameworks, a critical question for engineers, consultants or teams looking to build agentic AI applications is:

"What framework should I use?"
Other versions of essentially the same question include "Should I use LangGraph vs CrewAI vs AutoGen vs OpenAI agents vs …. ?", “Which agentic framework is the best?”

Overall, I find that static direct comparisons have limited value - all frameworks are constantly evolving (and even converging to similar apis).

More importantly, I believe it's more valuable to offer guidance on how to think about comparing frameworks, so you can choose one that best supports your specific business goals.

Why am I Qualified to Write/Reflect on This?
I am a core contributor to AutoGen, a leading framework for multi-agent applications where I've helped design aspects of the library, especially in the v0.4 release. Through this work, I've had the opportunity to discuss use cases with hundreds of developers—ranging from hobbyists to engineers working on serious production implementations. This background inevitably shapes (perhaps biases?) the perspectives I've shared below.

Additionally, my academic background in HCI (human-computer interaction)—focusing on user behavior, psychology, and applying these insights to build better interfaces—informs my approach. You'll likely notice this perspective in my reflections on developer experience throughout this post.

In this article, my main argument is that the right way to evaluate frameworks is by considering what they should help you accomplish. Rather than getting lost in feature-by-feature comparisons that quickly become outdated, let's focus on the fundamental capabilities that make a multi-agent framework valuable.

Here are 10 things a multi-agent framework should do well (and reasons you should consider adopting one):

For each dimension, I offer concrete evaluation questions you can use to evaluate a framework, and code samples with documentation links of good implementation where possible.

The TLDR; on how to evaluate and select the right framework;

1. Intuitive developer experience with both high-level APIs and low-level controls

2. Async-first design supporting non-blocking operations and streaming

3. Event-driven architecture for scalable agent communication