this post was submitted on 19 Sep 2026
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The dotcom bubble was the whole investor industry trying to capitalize on the internet, and they just failed because they were investing everything in a new thing people didn't need yet.

Today we live in an interconnected world, close to what was promised to the investors back then.

In ten, twenty years, once the bubble, OpenAI, Anthropic and all that are long buried, in what form do you think AI will exist? Do you think it will be an improved version of our current-day LLMs, or a different form of AI? Or do you imagine something else altogether?

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[–] currycourier@lemmy.world 13 points 2 days ago (1 children)

I mean I still prefer writing code by hand and I still write higher quality code faster by hand than others on my team who use LLMs to write code for them. Writing good, production intent, software is not about wpm, nor is more code necessarily better. Concision (as long as it doesn't sacrifice readability) is a virtue.

[–] Fandangalo@lemmy.world 3 points 2 days ago* (last edited 2 days ago) (1 children)

I watch a streamer who game devs without AI because I appreciate watching him discuss his thought process & learning more about how I could write it manually. For context, I’m a game designer who knows some code, not an engineer. There’s real concern around skill atrophy without people doing some of these more manual ways of doing things.

My point about WPM is moreso about how the scale impacts velocity. I do think the speed impacts the old adage about software & pregnancy.

  • How long does it take a pregnant person to deliver a baby? Roughly 9 months.
  • How long does it take 2 people? …Roughly 9 months.

There was a quality of software development where work takes the time needed, and sometimes throwing more bodies at something wouldn’t alter the time. A good engineer could maybe shave some time off, or the patterns they used were more resilient or production ready on the first pass. Now, that engineer could genuinely deliver that feature much faster.

Here’s another trap I forgot to mention: our human read speed is always faster than our write. We may write up to 330 wpm, but your read speed is 400-1000 wpm. AI read speed is like 11m / wpm. The gap between our write v. read suggests it’s faster to describe a plan, read what the AI wrote & triage it, rather than the alternative.

  • Case 1: Engineer is capped at 300 wpm write
  • Case 2: Engineer writes a plan at 300 wpm, AI writes a bulk at 6k wpm, then humam reviews at ~800 wpm

I mention John Henry because in the story Henry wins but dies in the process. Going fast is not the only goal, but the scale of the velocity change happening is really difficult to overcome mechanically on paper.

Finally, to be clear, I say this stuff as a bitter pill I don’t want to swallow either. :/ I have my own emotional qualms with the whole situation. There’s big business risks around becoming captured markets & beholden to token costs. I think part of the AI acceleration is about creating that dynamic, and it greatly concerns me.

[–] currycourier@lemmy.world 3 points 1 day ago

Reading speed is not equivalent to code review speed in the slightest! A good case study: https://static0.smartbear.co/support/media/resources/cc/book/code-review-cisco-case-study.pdf Tl;dr the ideal rate of code review is something like 300 lines per hour.

As someone who writes software for a living, these tools are simply nowhere near as good as a seasoned developer in terms of code quality. Getting them to write code at that level takes so much babysitting and tweaking that it is faster to just write it by hand. If you are not a full-time developer and are just writing some code on the side here and there, then yes, an LLM will probably do a better job. And thats ok! I've used them plenty and thought about this a lot as well. So I don't say this out of denial. But, at least for now, they are nowhere near a good as someone who knows what they are doing if you account for quality, and not just how fast the machine can spit out lines.