Compared to the original simple HTML site it’s really surprising to see from the grugbrain.dev author!
it is using astro, we are scaling down the use of tailwind (I wanted to give it a try, but didn't really click with it.)
I don't mind someone doing something kind of fun with the website and trying something new out, I know some people don't like it but some people do. All good.
clear text with minimal markup has many desirable properties IMHO
It gets pretty far to the solution on it's own and quickly, but then you spend time adjacent to the problem, building out it's cage while iterating through the remainder of the solution.
We actually have pretty good models for how long it takes to forget things. It's the same basic math that powers Anki. To oversimplify, if you force yourself to remember something right before you would have otherwise forgetten it, you will remember it roughly 2.5 times as long before forgetting it again. (This changes at both the shortest time intervals and the longer ones, so treat it as a rough rule of thumb, not an exact formula.)
But this provides a handy bound! If you've been doing something professionally for 20 years, you should expect to remember it for another 50. At which point you're likely well into old-age, and memory performance may decrease for other reasons.
Where AI kills you is actually at the other end: initial learning. You are much less likely to need to recall something after 1 day, 2.5 days, 6.25 days, etc. And thanks to the lack of the "testing effect", memory formation will be much weaker.
In other words, I would naively expect AI to make long-used skills a bit rusty, but to drastically impede formation of new skills and knowledge.
It’s not human, of course, and I think this problem actually relates to the fact that LLMs don’t have a world model. They don’t study and think through a design in the way that humans do. They don’t form a mental model of how everything fits together and how that design can be tweaked to most elegantly support a change.
I suspect that this is a fundamental limitation of LLMs, and that design will remain a weak point until some sort of bespoke design AI is bolted onto the side. In the meantime, we’ve got a lot of people producing a lot of code very quickly, and I think the debt in that code is going to be a millstone around our necks for a long time to come.
This article will be part of the next model training set, and probably it will be able to solve it despite not understanding anything about world or not studying or thinking.
Many developer criticism of AI coders could be easily directed at 95%+ of human developers. Much coding is monkey see, monkey do and keep trying until it does the things we want it to do. AI can certainly do that cheaper and faster and really this is why automated testing became such an important software discipline with or without AI.
The second issue is: what was tooling and the prompt approach?
(To be clear, I have no problem with the premise of the write up. But without some details like this, it's sort of like saying "I had a bad board on my deck, and my tape measure wasn't able to help me remove the nails. What a bad tape measure."
recursivedoubts•7h ago
it was a rather mundane bug, but i thought the interaction was interesting and worth analyzing to show where AI is very strong and where it is not as strong
hugeBirb•1h ago