Runtime reliability after fine tuning

[ishita-0301]

One thing I've noticed after fine tuning models is that getting better outputs is only part of the challenge. Once those models are placed inside long running agents, you start seeing practical execution issues like repeated retries, infinite loops, or the same failed tool call being attempted over and over.

I've been experimenting with an open source project called FailproofAI that focuses on handling these runtime failures. Instead of improving the model itself, it adds safeguards around agent execution such as loop detection and recovery mechanisms.

Repository: https://github.com/FailproofAI/failproofai

I'm curious whether others using LlamaFactory have run into similar production issues after deploying their fine tuned models and what approaches you're using to make autonomous agents more reliable.