Only on the Internet is this true, not in real life. I cannot and do not trust any of these things to do a proper job because they have not in any situation succeeded in any job I've given them. And no company I deal with claims otherwise
It might make sense to learn now, before everyone expects that you be an expert with this tool in order to do your job. On the other hand perhaps they will be easier to learn if you wait.
There is an incredible amount of nuance to be had in using LLMs and we reached the stage, probably only in the last few weeks where all the pieces have fallen into place such that if you are skilled at using the LLMs just about all of the previous problems with them can now be easily mitigated. If you learn how. There is a lot to learn.
- You need to have a mental model to grow an idea
- When a pattern is known you can use a library!
- When a pattern is not known AI will make stuff up
No matter how "good" coding with an AI will become there is no way you get around learning, having someone understand what's going on and take responsibility.
I'm fine with formal checking and fuzzing or getting hints where a bug might come from - but these are iterations on tools we used before like a debugger, strict types, functional programming and well fuzzing.
I tried to have an AI iterate on a step i don't fully understand yet and i always regretted it. Highly interconnected projects will grind to a halt until you do learn.
You can check with people doing highly specced software in the medical domain that even with very good specs there is ambiguity in natural language thus it can never be the source of reliable and manageable software.
However - i read about some smart guys in the 40s or so encountering the need for a formal language to tell a computer what to do with 0 ambiguity and i think they called it a "programming language"
Still glad I basically never have to debug a build issue or memory error again though
Lack of documentation used to be a running joke.
The goose_spec.txt in 2019 would be "goose is like c and rust only with syntax like array{;}[] btw it uses a small amount of stacks instead of malloc."0 10klocs.
Now, we make sure the AI leaves documentation so it can figure out what it was doing earlier.
A local model a few generations and many weights behind newest Claude can implement my novel algorithms and write the documentation I wouldn't.
Yes, many times it does dumb CS for kindergarten mistakes but it only has to work towards the optimum every once in a while.
With the tutorial, the summary also makes more sense. I have not read the other parts yet, but so far I like what I see.
All is in pretty good taste, and I like what I've seen so far. I do not care if the author himself came up with the idea, or if AI came up with it and the author approved.
I do not understand why you "have to" know this to make use of it. You can judge ideas independently of where they came from (and you should).
Couldn’t make it more than a few sentences in before the bile started to build up in the back of my throat and I had to back out. It’s shocking to me that people knowingly post unedited Claude-slop drivel and are seemingly unashamed about it. In 2026, it seems the main role of technical humans should be to act as a barrier between our agents’ output and other humans.
Apparently, this can actually assist the LLM:
https://silly.business/blog/we-should-revisit-literate-progr...
as discussed here previously:
I'd love to experiment with this myself.
That's without even mentioning that AI writing can often state the what but not the why. That human perspective is usually the most valuable knowledge to get across in writing.
Of course Humans can make errors when translating that to English. But if you’ve read any amount of Claudish it should be obvious that interpolating the code to documentation with an LLM typically produces a significantly worse result in almost every way. Except for superficially “sounding” correct.
Plus, if a human puts the effort into writing something, that signals to me that it's worth something, because human time is much more scarce than LLM time.
You cannot tell either from the AI written docs. I'd rather OP gave a rambling post about some problem he has in gamedev that led him to think a new language was needed, why the constraints are different, and how this will improve X, Y, or Z in his own words. Then I can infer what this project is and where it is going. Right now, I have no clue.
The author has written that post about why the language came about. He doesn't owe you that, but he did it anyway. He doesn't owe you anything more. You can use it or not. Advising him to throw away all the documentation and rewrite it again by hand from scratch so that adastra22 can deign to examine it further is ridiculous.
If you have a question about whether or not this further iterations will fit your specific (and so far undescribed) particular use case, the correct avenue for that is to ask the author politely. Or Fable; Fable could probably tell you without having to bother the author. But holy cow, the entitlement.
We're talking about a programming language. Languages, and their compilers, evolve over time. Where is this one headed?
The way to find out if a language is suitable for your needs is not to demand, in an entitled way, that the author perform an act for you. It is to (a) ask the author politely; or, failing that, (b) to examine it yourself (or ask Fable to evaluate it, using tokens you paid for).
This particular language, further, is Apache 2.0 licensed. If it's not working for you, fix it. Jesus.
For a programming language? It's subpar and you know it.
See this for a language docs site by a small-ish team, but a significant effort was put into making it nice to read: https://tour.gleam.run/everything/
This one is easy: I'd read the docs if it were written by a human, but I won't read them if they're written by Claude.