Just want to clarify, this is not my Substack, I’m just sharing this because I found it insightful.

The author describes himself as a “fractional CTO”(no clue what that means, don’t ask me) and advisor. His clients asked him how they could leverage AI. He decided to experience it for himself. From the author(emphasis mine):

I forced myself to use Claude Code exclusively to build a product. Three months. Not a single line of code written by me. I wanted to experience what my clients were considering—100% AI adoption. I needed to know firsthand why that 95% failure rate exists.

I got the product launched. It worked. I was proud of what I’d created. Then came the moment that validated every concern in that MIT study: I needed to make a small change and realized I wasn’t confident I could do it. My own product, built under my direction, and I’d lost confidence in my ability to modify it.

Now when clients ask me about AI adoption, I can tell them exactly what 100% looks like: it looks like failure. Not immediate failure—that’s the trap. Initial metrics look great. You ship faster. You feel productive. Then three months later, you realize nobody actually understands what you’ve built.

  • drosophila@lemmy.blahaj.zone
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    13 hours ago

    The thing about this perspective is that I think its actually overly positive about LLMs, as it frames them as just the latest in a long line of automations.

    Not all automations are created equal. For example, compare using a typewriter to using a text editor. Besides a few details about the ink ribbon and movement mechanisms you really haven’t lost much in the transition. This is despite the fact that the text editor can be highly automated with scripts and hot keys, allowing you to manipulate even thousands of pages of text at once in certain ways. Using a text editor certainly won’t make you forget how to write like using ChatGPT will.

    I think the difference lies in the relationship between the person and the machine. To paraphrase Cathode Ray Dude, people who are good at using computers deduce the internal state of the machine, mirror (a subset of) that state as a mental model, and use that to plan out their actions to get the desired result. People that aren’t good at using computers generally don’t do this, and might not even know how you would start trying to.

    For years ‘user friendly’ software design has catered to that second group, as they are both the largest contingent of users and the ones that needed the most help. To do this software vendors have generally done two things: try to move the necessary mental processes from the user’s brain into the computer and hide the computer’s internal state (so that its not implied that the user has to understand it, so that a user that doesn’t know what they’re doing won’t do something they’ll regret, etc). Unfortunately this drives that first group of people up the wall. Not only does hiding the internal state of the computer make it harder to deduce, every “smart” feature they add to try to move this mental process into the computer itself only makes the internal state more complex and harder to model.

    Many people assume that if this is the way you think about software you are just an elistist gatekeeper, and you only want your group to be able to use computers. Or you might even be accused of ableism. But the real reason is what I described above, even if its not usually articulated in that way.

    Now, I am of the opinion that the ‘mirroring the internal state’ method of thinking is the superior way to interact with machines, and the approach to user friendliness I described has actually done a lot of harm to our relationship with computers at a societal level. (This is an opinion I suspect many people here would agree with.) And yet that does not mean that I think computers should be difficult to use. Quite the opposite, I think that modern computers are too complicated, and that in an ideal world their internal states and abstractions would be much simpler and more elegant, but no less powerful. (Elaborating on that would make this comment even longer though.) Nor do I think that computers shouldn’t be accessible to people with different levels of ability. But just as a random person in a store shouldn’t grab a wheelchair user’s chair handles and start pushing them around, neither should Windows (for example) start changing your settings on updates without asking.

    Anyway, all of this is to say that I think LLMs are basically the ultimate in that approach to ‘user friendliness’. They try to move more of your thought process into the machine than ever before, their internal state is more complex than ever before, and it is also more opaque than ever before. They also reflect certain values endemic to the corporate system that produced them: that the appearance of activity is more important than the correctness or efficacy of that activity. (That is, again, a whole other comment though.) The result is that they are extremely mind numbing, in the literal sense of the phrase.