How I use it #
Code: I work with coding agents daily - usually a whole herd of them1. They write code, draft tests, hunt bugs, and read documentation faster than I ever could. They are great colleagues: tireless, well read, and occasionally overconfident.
Words: AI helps me proofread and translate - most of the Danish/English translations on this site were machine-assisted. The opinions, the stories, and the bad puns are all my own.
Learning: A good model is a rubber duck2 that talks back. I use it to explore ideas, challenge my assumptions, and dig into topics I don’t know well yet.
How I don’t #
I don’t vibecode - describe what I want, accept whatever comes out, and ship it as a black box. That’s fast, but it means handing over control and understanding, and production software demands both.
Instead:
- Every line gets reviewed. I read and understand the code before it ships - I don’t merge what I can’t explain.
- Everything gets tested. Agents write tests too, but the tests have to pass and make sense before anything goes anywhere.
- I own the decisions. AI suggests, I decide. The architecture, the trade-offs, and the mistakes are mine.
- No hidden AI magic. When AI played a significant part in something I publish, I say so.
The tools will keep changing3, but the principle won’t: I’m the pilot, the AI is the very smart GPS.
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See rubber duck debugging. ↩︎
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They change roughly every other week at the moment 😅 ↩︎