I think there is more to it than that.

I am a high quality/craftsmanship person. I like coding and puzzling. I am highly skilled in functional leaning object oriented deconstruction and systems design. I'm also pretty risk averse.

I also have always believed that you should always be "sharpening your axe". For things like Java delelopment or things where I couldn't use a concise syntax would make extensive use of dynamic templating in my IDE. Want a builder pattern, bam, auto-generated.

Now when LLMs came out they really took this to another level. I'm still working on the problems.. even when I'm not writing the lines of code. I'm decomposing the problems.. I'm looking at (or now debating with the AI) what is the best algorithm for something.

It is incredibly powerful.. and I still care about the structure.. I still care about the "flow" of the code.. how the seams line up. I still care about how extensible and flexible it is for extension (based on where I think the business or problem is going).

At the same time.. I definately can tell you, I don't like migrating projects from Tensorflow v.X to Tenserflow v.Y.

I really should spend some time analyzing what I do to get the good output I get..

One thing that is fairly low effort that you could try is find code you really like and ask the model to list the adjectives and attributes that that code exhibits. Then try them in a prompt.

With LLMs generally you want to adjust the behavior at the macro level by setting things like beliefs and values, vs at the micro level by making "rules".

By understanding how the model maps the aspects that you like about the code to language, that should give you some shorthand phrases that give you a lot of behavioral leverage.

Edit: Better yet.. give a fresh context window the "before" and "after" and have it provide you with contrasting values, adjectives, etc.

I was totally aligned until I saw the refusal for a comment in the code. When the refusals are pedantic like that, it just weakens the overall findings significantly.

Actually I would have agreed with you 2 years ago. But now working with AI so much, maybe RSS "is" just the thing we need for some of the distrobution.

I guess, how often do you pay someone to fix your car? Repair something in your house? Give you financial advice?

Those are all things many people outsource their thinking to other people with.