/self

How I Run a Weekly Eval Loop

A small review ritual for checking whether my AI workflows are getting clearer or only getting faster.

I do not trust a workflow just because it felt smooth once.

At the end of the week, I review a few runs that looked successful and a few that felt slightly wrong. I am not looking for a grand metric. I am looking for whether the system made sense at the boundaries where it chose, retrieved, or verified something.

That ritual keeps me from confusing speed with quality. A fast loop can still be weak if it depends on luck, hidden memory, or unspoken assumptions. The review is there to catch quiet drift before it becomes a habit.

I usually ask the same small set of questions: what was the intended outcome, what evidence supported the decision, where did the process feel brittle, and what should become a rule instead of a reminder. Those questions are simple enough to repeat, which is why they work.

A weekly evaluation loop moving from run review to rule update Runs Review Decision Rule
The review matters because it turns repeated friction into a better operating rule.

I think of the loop as a way to preserve judgment while the tools get faster. I do not want to become dependent on outputs I cannot explain. I want a process that leaves behind a cleaner trail than the one I started with.