If you had python code and you didn't want it to have syntax highlighting or be run/imported or any of the other normal things that you do with python files, it might make sense to have python code in a .txt. file.
Same idea here IMO. .md would signal the wrong intent, as you don't want to render it to markdown formatting or read as a markdown file normally is. You want it to be read as plain unrendered text.
What do you have trouble reasoning about regarding FastHTML python compared to Jinja2 or Django templates?
To me, it seems like a direct translation, and that's what makes it easy to reason about. I'm curious about what situations you find more intuitive to use Jinja2 over Python.
For example, in FastHTML:
P() -> <p></p>
Div(P()) -> <div><p></p></div>
The lack of a big transformation layer and things being 1:1 is what makes me think it's just as easy to reason about, but it comes with the advantage of a more powerful Python over a templating language.
I agree that this wouldn't be a great solution if you want people who don't know Python to make HTML edits.
IMO it's not a "structure in one place" vs "more composable so more spread out"
In HTML, you are much more likely to have things in one place because you don't have great options otherwise.
In Python, you can choose to keep things in one place and not compose them, or you can choose to refactor to compose them if that makes them better for your particular use.
It is, however, definitely true that with the extra option, you have the option to refactor it so much it's less readable. How much to refactor and split things apart, decentralize, DRY vs how much to keep things in a structured place can be a hard thing to figure out!
> Once you grow beyond the "website" with simple interaction your front end becomes it's own universe
I think this has been a major failing/pain point of web-dev that this MUST be the case. However, I think fastHTML for me is going to fix that. Naturally there is no approach that is ideal in every case, but for a ton of them fastHTML I think works. I've built several things with fastHTML and am very optimistic.
As far as the visual identification, I think python is just as clear to see visual blocks as HTML, but comes with many additional refactoring options (that you can choose when it makes sense to use for your use-case).
Try playing with https://h2x.answer.ai/ and putting in some HTML code and see how it looks in python. Maybe you'll disagree, but I find it quite refreshing.
I didn't see anything in the article that indicated the authors believed that those who don't see use cases for LLMs are anti-progress or anti-technology. Is that comment related to the authors of this article, or just a general grievance you have unrelated to this article?
They think they are real business use cases, because real businesses use them to solve their use cases. They know that chatgpt can't solve this off the shelf, because they tried that first and were forced to do more in order to solve their problem.
There's a summary for ya! More details in the stuff that they linked if you want to learn. Technical skills do require a significant time investment to learn, and LLM usage is no different.
Luckily it's not one or the other. You can fine tune and use RAG.
Sometimes RAG is enough. Sometimes fine tuning on top of RAG is better. It depends on the use case. I can't think of any examples where you would want to fine tune and not use rag as well.
Sometimes you fine tune a small model so it performs close to a larger varient on that specific narrow task and you improve inference performance by using a smaller model.