[flawn]

I wonder, how well does Yak-Shaving work for you with AI, how does it look for you specifically and how do you make sure it's not undermining the friction for learning things properly? I want to try some more yak-shaving soon too.

[thimabi]

Yak shaving with AI allows me to function more as a systems designer, code reviewer and tester than a coder per se.

AI is great if you simultaneously guide it and let it guide you. I take my time building a very detailed spec for what I want, then run it through the AI looking for contradictions, misconceptions, edge cases, performance bottlenecks, potential optimizations… anything that might cause problems in the future. Usually these discussions lead to multiple spec-improvement journeys, and that’s where the bulk of learning in a project comes from. Sometimes the AI will flag actual issues, while other times I might need to rein in its proposals — mostly in terms of feature creep and finding non-existing problems. I believe this back-and-forth is the most significant aspect of making the best out of yak shaving.

By the time the spec is “final”, it can be quickly implemented by an AI as I watch, review and test, with practically zero code banging on my part. This way, I get to understand precisely how the project works, make it tailored to my needs, and still not waste time, muscles or even mental bandwidth with menial coding.

[benj111]

You say this just as Google's AI is confidently telling me 'c.addi4spn' is 7 characters long.

So from my perspective you still need to know how to do the thing to catch the errors. Also, are you not missing out on the unknowns?

If an ai does a thing, fair enough. But you haven't tried to work it out yourself, done the wrong thing, to realise why it's done that way.