Large Language Models

Agentic AI: Comparing New Open-Source Frameworks

By looking at functionality and learning curves

Looking at mentions and github stars for various open-source agentic frameworks | Image by author

We’ve all heard of CrewAI and AutoGen, but did you know there are dozens of open-source agentic frameworks out there — and many of them have been released in the last year.

I’ve briefly tested some of the more popular ones to get a feel for how they work and how easy they are to get started with. So follow along as I go through what each one brings to the table.

The focus will be on LangGraph, Agno, SmolAgents, Mastra, Pydantic AI, and Atomic Agents. We’ll also compare them to CrewAI and AutoGen.

How we can compare the different frameworks | Image by author

We’ll look at what a framework actually does, the different design choices, how they differ from one another, and a bit about the schools of thought behind them.

Agentic AI

Agentic AI is basically about building systems around LLMs so they can have accurate knowledge, access to data, and the ability to act. You can think of it as using natural language to automate processes and tasks.