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Joined 9 months ago
Cake day: January 20th, 2026
  • Similar field, similar experience. I think it’s easy to sleep on how much LLMs can help your work if you’re just using chatbots- because those give incorrect answers so often that most interactions end up being a waste of time.
    But if you give the model tools to test its answers, and prompt it in a way that restricts responses to tool outputs instead of generated answers, suddenly the many mistakes are less of a problem. It wrote a function with 5 bugs that did the wrong thing to begin with? and then it caught all of those mistakes in testing and fixed them, and it took 6 seconds, so it doesn’t really matter. Maybe that’s how I write a function in my head too, I just think through the most obvious issues before typing the code and testing it.
    The high level planning still needs frequent and detailed instructions, otherwise it tends to go down the wrong rabbit holes.

    Setting up the environment took some time, bit since I started using claude code I actually started to go through my tech debt backlog, because fixes that used to mean I have to take a day off, I now take 5 minutes to write down the issue and the scope of the fix, and 10 minutes to watch it being fixed. I am pretty sure I will stop writing code in a year or two maximum. I am slightly worried what happens to the codebase if prices of tokens get out of control, but I guess local models could help as long as you have the hardware.