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Joined 2 years ago
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Cake day: July 18th, 2024

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  • You are completely correct, and to be honest I’ve tested commercial product features in prod as well on teams that have the capacity to handle it and make a living on it, unlike this maintainer.

    I’m also experimenting heavily with vibe coding and I think it has many uses for a seasoned programmer while getting a lot of flak.

    Of course there are issues and problems with it, but for me it had been helping out a lot.




  • To be fair they would have needed to spend time testing the manual implementation as well.

    The problem I see mainly is that even if this rolls out perfectly, the erratic and changing nature if llms still make it pointless as a proof of concept. Next time Claude might fuck up in a fringe way that’s not covered by unit tests and is missed by manual tests.

    On the other hand I guess I’ve been guilty myself on numerous occasions to implement fringe bugs into production code, but at least I learn from it.














    • Angel dust by faith no more. It has been cited as a massive influence by many huge 90s metal bands.
    • Pet sounds by beach boys. Without it there would be no sgt Pepper (as we know it) and without that it’s hard to say where pop would be today.
    • The rise and fall of Ziggy stardust and the spiders from Mars by Bowie. While not being the source of the glam wave (hi t-rex) it really took it to a new level, along with the concept of stage personas.



  • As someone who’s been using it in my work for the last 2 years, it’s my personal observation that while the models aren’t improving that much anymore, the tooling is getting much much better.

    Before I used gpt for certain easy in concept, tedious to write functions. Today I hardly write any code at all. I review it all and have to make sure it’s consistent and stable but holy has my output speed improved.

    The larger a project is the worse it gets and I often have to wrap up things myself as it shines when there’s less business logic and more scaffolding and predictable things.

    I guess I’ll have to attribute a bunch of the efficiency increase to the fact that I’m more experienced in using these tools. What to use it for and when to give up on it.

    For the record I’ve been a software engineer for 15 years