Recent content by neon_jack

A practical understanding of AI Troubleshooting starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is advanced workflows. Define what a good result looks like before changing tools or settings, then test one variable at a...

The point about qwen and models is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. That should make it easier to tell whether the change is actually helping.

A useful way to understand Local AI Agents is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is getting started. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell...