Except there’s no average person, the average itself is a combination of people with the most diverse needs and constraints. It’s like the joke that the average human being has 1 breast and 1 testicle.
It is a thing to some extent, but there’s also a correlation of companies that do cross-platform for simple apps being cheap on development, and making it work very well on some specific platform isn’t their priority.
Basically, I’d say the LLM doesn’t have a “theory” of anything that wasn’t in its training. It’ll always treat your project as if it was reading a book for the first time.
As an example, if you chat with an LLM it can sort of explain concepts it learned in its training, because it created some internal representation of them. However it’ll never be able to explain things about your project unless you tell it (then it can simply repeat it, which is the same RAG does, the LLM is just spitting it out without any deep understanding of it).
You can try to cram as much context to it as possible and overload it with extra information, or you can understand this difference and separate a task that you know the LLM can handle because you’ll be able to leverage its knowledge and judge the final work yourself.
But this distinction needs to be more clear, I think. The LLM doesn’t have any deep understanding of anything you’re creaming into the context window the same way it does with concepts it learned during training from millions of examples and building some internal model of the concepts and their relationships.
Often times to write a good enough specification in a way the LLM won’t misunderstand it, you need to really understand the code and the possible pitfalls in it though. A few times when I tried this route, even adding details just in case the LLM still went and assumed something wrong that I didn’t consider would be a problem until the agent had to make that choice. Then it becomes a game of doing it again and again with more and more detailed instructions until you could have yourself done it in less time and having a deeper understanding of the problem (or I could argue having any understanding of the problem at all, since having the LLM do it for you is like being a manager who has no clue about the lower level decisions made and only being communicated the final result).
You’re not wrong, but there’s a nuance here. More often than not our thoughts fool us into thinking we have something clear when we have only a vague idea of what you want to do.
I kinda [wrote about this before](https://dielsonsales.github.io/2023/05/11/starting-a-new-blo...) but the takeaway is that writing forces you to structure your thoughts, giving them a final shape and enables you to notice flaws or gaps in your own thinking process. It’s impossible to do this without writing.
It would be good to have specific situations here I guess, otherwise it's quite abstract, and I'm not sure what to make of it.
As to your post, I think rather than writing it's the act of pressuring yourself to figure the thing out that is making you more knowledgeable about the thing.
You are putting it out publicly out there so you really want to be certain that you are correct, and therefore you do a lot of research.
If you wanted to be accurate and prove a point, the motivation mechanism could vary, but also the eventual communication mechanism could vary. It doesn't necessarily have to be in writing, it could be a live debate or simply something else you built. The writing or the product are end product, but the process of wanting to produce something is what made you research and to understand.
You could be writing to yourself into a Google Docs, and not care and you would not go deep to research since there's no incentive to be accurate.
E.g. I could be doing a home project whether hardware, software or DIY, that in order to produce this output I have to learn and think. Similar to as good set of words to communicate some idea. But also I could build some slop without thinking and I could produce slop writing without thinking, and about nothing special.
I’d like to recommend people to read the “Programming as a theory building” article and why the code itself isn’t enough to understand the whole context of a complex project.
Every time you work in a complex software project, you have all the context in your head about what you must take into consideration. LLMs don’t, you have to explain every little detail to them, but there’s no telling where it stops: do you have to explain X to it or is it in the training already?
When you try to shape how a LLM should behave and what it should know, you end up writing a Bible of relevant context that’s increasingly difficult to maintain as well, often with outdated or contradictory information, and it is still free to ignore things you have written and proceed however it wants.
That’s why so many people only feel comfortable giving the LLM some limited task to do, because you can judge if that specific task needs just enough context that it can handle by itself.
It’s what’s called in software engineering as “casual software” as a differentiator of “business software” and “critical software”. Not all types needs a high bar of quality, and most of the software engineering thought practices are tailored for business applications that will be made available to multiple users.
As you said, building a script that only you use personally or a very simple thing that just accomplishes one task and it’s easy to test require almost no engineering, and an LLM can often build those with very little downsides.
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