How are you monitoring intermediate steps and quality drift in local workflows?

I’ve been experimenting with local agentic coding and multi-agent setups (mostly using 35B–70B models), and the biggest bottleneck I’m hitting isn’t inference speed—it’s traceability. When a local agent gets stuck in a loop or starts hallucinating a non-existent package, it’s often impossible to see where it lost the plot until it outputs the final failure.

I’m currently mapping out a conceptual, monitoring platform to solve this by making the 'invisible' visible.

For those of you running local agents (n8n, OpenClaw, or custom loops), what are you using to 'see' inside the run? If you had a dashboard for drift and reliability, what are the top 3 things you’d need to see to actually trust a model for production?