Nolan Pierce

i try a lot of AI products and my honest hit rate is low. most of what i install is gone inside a week, and usually not because it was bad. it just never turned into a habit.

the few that stuck have almost nothing in common on paper. the only thread i can find is that they took away a step i was already doing, instead of adding a step i probably should be doing. the ones that asked me to build a new routine all died.

We ve been thinking about this a lot while building Traccia.

One behavior we ve seen with MCP workflows is an agent getting into repeated tool calls without making meaningful progress. The workflow hasn t necessarily failed it can just keep going.

That got us thinking about a different kind of agent monitoring: not just detecting errors, but defining boundaries on execution.

I ve noticed a pretty big change in my own behavior over the last year.

If I m looking for a tool for something specific, I ll usually ask ChatGPT first, then check Product Hunt or Reddit to see what real people are saying. Google has become more of a second step for me.

What I m curious about is whether thats actually changing discovery for other makers too, or if I m just unusually deep into AI tools.