Last updated June 15, 2026

I test AI tools on the work already in front of me

Aaron Makelky tests AI tools on real work and writes down what saves time, breaks, or holds up.

What this site is for

If something saves me time, I keep the notes. If it falls apart, I keep those notes too.

Right now I am testing what I would actually use again: a workshop prompt, a cleanup step, or a tiny tool that saves a few minutes.

My filter comes from Wyoming classrooms, coaching, and the move into tech. If a workflow only works in a demo, I am not interested for long. I want the version that saves time, helps a student get unstuck, or keeps a team from checking the same thing all day.

The useful path usually starts small. Read one note, try one tool, or bring me into a workshop where people leave with something they can try Monday.

Workshop proof

The latest workshop feedback was plain: people wanted practical examples, repeatable prompts, and time to check the work.

In the LUM Studio feedback, 10 of 10 respondents said they left more confident using AI at work. Eight marked the session extremely useful and said they had clear next steps.

The most useful critique was also practical: people wanted more time for examples, Q&A, and discussion.

Start here

The blog is where I keep the longer thinking. The tools page is where I keep small utilities, Codex skills, and prompts I made after the normal way got annoying. The shop is for OpenClaw kits and agent reliability resources. The about page explains the teacher-to-tech route behind the work.

Short answers

Who is Aaron Makelky?

Aaron Makelky is a former Wyoming teacher and football coach who now works in tech at Descript and writes about practical AI use.

What does Aaron help people do with AI?

He tests AI tools on real work and turns the useful parts into notes, workshops, and small tools.