AI: Accelerated Incompetence

> Input Risk. An LLM does not challenge a prompt which is leading...

(Emphasis mine)

This has been the biggest pain point for me, and the frustrating part is that you might not even realize you're leading it a particular way at all. I mean it makes sense with how LLMs work, but a single word used in a vague enough way is enough to skew the results in a bad direction, sometimes contrary to what you actually wanted to do, which can lead you down rabbit holes of wrongness. By the time you realize, you're deep in the sludge of haphazardly thrown-together code that sorta kinda barely works. Almost like human language is very vague and non-specific, which is why we invented formal languages with rules that allow for preciseness in the first place...

Anecdotally, I've felt my skills quickly regressing because of AI tooling. I had a moment where I'd reach out to it for every small task from laziness, but when I took a real step back I started realizing I'm not really even saving myself all that much time, and even worse is that I'm tiring myself out way quicker because I was reading through dozens or hundreds of lines of code, thinking about how the AI got it wrong, correcting it etc. I haven't measured, but I feel like in grand totality, I've wasted much more time than I potentially saved with AI tooling.

I think the true problem is that AI is genuinely useful for many tasks, but there are 2 camps of people using it. There are the people using it for complex tasks where small mistakes quickly add up, and then the other camp (in my experience mostly the managerial types) see it shit out 200 lines of code they don't understand, and in their mind this translates to a finished product because the TODO app that barely works is good enough for an "MVP" that they can point to and say "See, it can generate this, that means it can also do your job just as easily!".

To intercept the usual comments that are no doubt going to come flooding in about me using it wrong or trying the wrong model or whatever, please read through my old comment [1] for more context on my experience with these tools.

[1] https://news.ycombinator.com/item?id=44055448

Let's be real, 70% of staff are phoning in their jobs so badly that an AI often is just as good if not better.

The real struggle will be, the people phoning it in are still going to be useless, but with AI. The rest will learn and grow with AI.

> LLMs as they currently exist cannot master a theory, design, or mental construct because they don't remember beyond their context window. Only humans can can gain and retain program theory.

False.

> An LLM is a token predictor. It works only at the level of text. It is not capable of working at a conceptual level: it doesn't reason about ideas, diagrams, or requirements specifications.

False.

Anyone who have spent time in machine learning or reinforcement learning understands that models are projections of higher dimension concepts on to lower dimensions as weights.

It's occurred to me more and more that I need to repurpose 90s.dev into a non-AI community, focused on the ancient art of writing software well, and welcoming to all who honed that craft. What would it need to start with? Forum? Mailing list? Aggregate blog from multiple authors like hackernoon?

[edit] Makeshift mailing list for those interested: https://github.com/sdegutis/90s.dev/issues/2 (subscribe or comment to "sign up for emails" on the topic)

Use an OG forum software that's good and powered some of the classic forums of the time. Make it stylishly retro.