Hi Dev.to community 👋
I recently started diving deep into AI agents — systems that can reason, decide, and act autonomously. At first, I experimented with popular frameworks like LangChain, but I realized I didn’t fully understand what an agent actually does or how decisions and tools really work under the hood.
So I decided to build my own library from scratch: SmartAgent.
The goal was simple: make agents transparent, understandable, and easy to experiment with. I wanted a library that clearly separates the agent’s reasoning steps so anyone (including myself!) could actually learn how an agent works.
How SmartAgent works
SmartAgent uses a three-phase flow:
- Analysis – the agent reasons about the problem
- Execution – the agent decides what to do and uses tools
- Response – the agent produces a final answer
By designing it this way, I could finally understand:
- What an agent really is (not just prompts)
- How decisions are made step by step
- How tools fit into the reasoning loop
- How to design my own agents intentionally
Why I’m sharing it
I built SmartAgent not just for myself, but as a learning tool for others. If you’re curious about AI agents, want to experiment, or even contribute, it’s approachable and educational.
It’s also open-source, so anyone can explore, tweak, or add new tools.
Try it out:
I’d love to hear how other people are experimenting with agents, and any feedback or ideas are very welcome!
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