[caspper69]

I am in the middle of my third AI assisted project. I disagree ~90%.

If you prompt an LLM like an architect and feed it code rather than expecting it to write your code, both ChatGPT 4o and Claude 3.7 Sonnet do a great job. Do they mess up? Regularly. But the key is to guide the LLM and not let the LLM guide you, otherwise you'll end up in purgatory.

It takes some time to get used to what types of prompts work. Remember, LLMs are just tools; used in a naive way, they can be a drain, but used effectively they can be great. The typing speed alone is something I could never match.

But just like anything, you have to know what you're doing. Don't go slapping together a bunch of source files that they spit out. Be specific, be firm, tell it what to review first, what's important and what is not. Mention specific algorithms. Detail exactly how you want something to fit together, or describe shortcomings or pitfalls. I'll be damned if they don't get it most of the time.

[alganet]

> Be specific, be firm, tell it what to review first, what's important and what is not [...] Detail exactly how you want something to fit together [...]

You mean like in a fast food chain?

I know how to use it. All of that was already implied in my original comment. Sometimes though, I want to cook without a rigid mindset.

[skydhash]

I wonder how many lines of code you write in a day. Most PR I’ve seen has a diff in the lowe 2 digits, unless it’s refactoring or formatting.

[caspper69]

If I had to guess, probably a couple hundred lines a day, maybe more if I get in a groove or have a deadline.

But with an LLM, that number goes to about 500 or so, 200 of which are real code and not definitions of some kind. Truthfully, that’s where the LLMs shine. I have this enum with 50 variants, and need to build a dictionary (with further constraints and more complex objects). That shit takes forever even with cut & paste, unless you code with code, and those one-offs aren’t my cup of tea anymore.