Trust in a local model builds slowly

The first few times you use a local model, every answer deserves a healthy amount of skepticism. Over weeks of small, checkable tasks, you start to build a real sense of where it is reliable and where it consistently comes up short. That sense is worth more than any general claim about how good or bad local models supposedly are. I keep this kind of note myself, and looking back at a few weeks of it tells me far more than any single answer ever could.

This trust is specific to your own setup, your own model, and the kinds of tasks you actually give it. Someone else's experience with a different local model tells you very little about yours. The only way to really know is to keep testing it against work you can verify yourself.

Once that trust is earned honestly, working with a local model starts to feel less like an experiment and more like a normal part of how you get things done.

Try this today: keep a simple running note of tasks where your local model did well, so you can see the pattern build over the coming weeks.