An experiment exploring how to build autonomous agents powered by LLMs, capable of reasoning, planning, and using external tools.
The idea
AI agents represent a qualitative leap over traditional chatbots. Instead of just answering questions, an agent can decompose a complex problem into sub-tasks, execute them, and verify the results.
Stack
- LLM: Claude as the reasoning engine
- Tool use: function calling to interact with external APIs
- Orchestration: reasoning loop with short-term memory
Results
The approach works surprisingly well for structured tasks. The main challenges remain error handling and computational cost for very long tasks.