I quit everything, and that's data, not failure

My official record reads like a warning label. Jobs: several, hobbies: a graveyard.

Instruments, languages, a martial art, one very optimistic attempt at keeping bees. The list goes on.

Each exit came with the same commentary, from me and sometimes from others: there it is again. You quit. It's what you do.

For a long time I believed them. Quitting felt like my one consistent talent.

The bee era lasted one summer and zero harvests, in case anyone asks.

At some point I laid the whole list out and looked at it from altitude instead of from inside the shame. A different pattern was hiding there.

It was the first time I reviewed my own history like an analyst instead of a defendant.

• Everything I quit shared a trait: long boring middles, delayed rewards, someone else's pace.
• Everything I stuck with shared the opposite: fast feedback, visible progress, a problem to solve.
• The quits were not random. They were consistent — and consistency is data.

A brain that runs on interest has to sample widely to find its fuel. Every quit was a data point with a price: time, money, a little dignity. But data points are only waste if you never read them.

People call it a lack of follow-through. From the inside it felt more like triage: limited fuel, infinite candidates, hard choices.

Read properly, my history of quitting is a surprisingly precise map of my brain: what it engages with, what it abandons, and roughly how long the honeymoon lasts.

The list of things I never quit is short, and that is exactly why it matters. Those are not lucky accidents — they are the survivors of the largest, most expensive trial-and-error study I will ever run.

The shortlist gets revisited, not worshipped. Survivors can be outgrown too, and quitting one of those is allowed.

Now I quit faster and cheaper: small samples, borrowed gear, short commitments, honest exits. The goal was never to stop quitting. The goal was to get better data per quit.