I'm building a dead-simple monitoring tool for AI agents — would you use it?
Hey r/LangChain,
I'm working on a lightweight tool to help developers monitor their AI agents in production.
The problem I'm trying to solve: when your agent fails or behaves weirdly, you currently have no easy way to see exactly what happened — which steps it took, where it went wrong, what it cost you in tokens.
My solution is basically a "black box recorder" for AI agents. You add one decorator to your code:
python
u/trace
def run_my_agent(user_input):
# your existing code, untouched
And you get a dashboard showing:
- Every step your agent took
- Where it failed and why
- Cost per run
- Alerts when something breaks
Works with any model (OpenAI, Claude, Gemini, Llama) and any framework (LangChain, LangGraph, raw API calls).
Before I build this — would you actually use it? What's your biggest pain point when debugging agents in production?
Genuine feedback only, happy to be told this already exists or nobody wants it!