comments (10)

  • >On my visits to the Bay Area, I would ask AI researchers or interns why they are doing their current research or projects, when in a year or three agentic LLMs could probably do them;

    This is such a weird point to make that doesn't become correct just because everyone makes it, all the time. Why clean the ocean if some magic future tech will clean them? Why save the world now if some benevolent AI is 'just around the corner' and will do it for us? And people have been making this point for years now, and it's not like my job got any easier. I just got more AI.

    https://www.poetryfoundation.org/poems/51294/waiting-for-the...

    And I say that as someone who uses Claude Code in complex environments almost hourly; I, as the human, still have to do the thinking as Claude still 'can't jump' [1] and I have seen no evidence that they (or similar AI, any time soon) will 'jump' like a human brain does.

    [1] https://www.tomzahavy.com/files/llms-cant-jump.pdf

    a_bonobo

  • > We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent.

    Anyone else finding they're spending more time writing code (or at least driving agents to write code) now?

    14% used to feel about right for me - I'd spend the rest of the time researching approaches and libraries, planning things out in issues, or sometimes just thinking really hard about problems I ran into.

    Now... I still do those things, but I'm doing many of them faster - and I'm often doing them while my coding agents are churning away on code.

    There's also this weird effect where the harder a problem is the more I can get done in parallel with it, because an agent might need to spend 20 minutes on it without my involvement.

    simonw

  • I've found that using LLMs for significant amounts of code generation completely drain the result from any dopamine I would get doing it myself.

    Have others noticed this as well? This is going so far as to me losing interest in side projects because I have "lost touch" with the code base.

    mfru

  • I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."

    mkozlows

  • Like many others in the comments, I feel there are a lot of assumptions in this piece. Before, coding is only 14% therefore, small slice. I think that's a very superficial assumption. That was because coding was expensive and we needed to be sure we didn't code the wrong thing. If code is as cheap as it is now, we will optimize differently, we will structure around it. Instead of so many meetings we will code 5 different versions of the same thing and choose, etc.

    lz400

  • > Myth 2: Writing Code Is the Bottleneck

    Writing code is indeed the bottleneck for same resource constrained companies.

    Rapid code development creates more opportunities for trial and error, providing companies with more information for decision making, that previously might have been addressed by meetings.

    Of course, this might bring other problems, but it might not right to generally speaking that writing code is not a bottleneck.

    langs

  • This reads like a critique of 2023 tooling published in 2026. Their Amdahl-style arithmetic (speed up a 14% slice, cap your gains at 14%) holds only if "AI" means autocomplete. Current frontier models do far more than that: research, code comprehension, review, test authoring, debugging, exploratory prototyping, ideation. That's most of the rest of the working day or "86%".

    The only point that still holds is that organizational policies and procedures that automate AI use and lower the barrier to entry are more efficient than leaving it up to each individual. Every other point they make is either stale or was never true to begin with.

    armitron

  • I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code).

    They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day.

    The problem with this argument is that once you have code, some (not all) of the precursors to code go away.

    kylecazar

  • |--------|-------|------|------|-------|------|

    |Contract|Product|Design|Coding|Testing|Deploy|

    Writing Code Isn't the Bottleneck, until writing code is the bottleneck, until it's not again.

    Supermancho

  • I can't remember of any product in my lifetime that was more over hyped than AI.

    It's a huge piece of shit and if I wasn't forced to use it at work I would never use it.

    It writes dumb, throw-away code and adds thousands of dollars/developer in costs. All this crazy code that we're adding to our projects will come back to bite us in the future, there's no way it won't.

    altern8