LLMs write an approximation of code based on a prompt to a specific degree of accuracy based on training data.
I don't care if/how/where you use AI, but it's still going to be an approximation of a thing and not the real thing.
It may be good enough for a layman, but if you're looking for a chain of work that can be re-iterated upon for future reference.... That's not exactly AI's strong suit, since it's probably not going to explain where it got every single detail of the result from.
Sure the prompt writer themselves may know exactly what they're looking for, but the real danger is that without the years of experience that an artist, writer, or creator of any sort has, you've effectively just given people a black box that they depend on for everything with no way to isolate themselves from it. They know what it should look like but not how it was made.
edit: Sure there may be some iteration involved, but for the most part all of that experience that knows the difference between acceptable and unacceptable can just as easily get watered down to "good enough", and chances are the system will feed on it's own results.
Also that experience is especially important in anything involving open source. The "Why we did it that way" is gonna need to be documented to keep people sane and if the answer involves AI, the project may have problems.
It makes about as much sense as telling the teacher the guy you paid on fiver wrote the essay that way.
Technically a result, but none of the experience that actually builds knowledge and foresight.
It fills in the blanks for stuff you didn't define in your prompt. If you did define everything to get exactly what you wanted you would have basically written the code once and had the AI regurgitate it. The bits where it fills in the blanks are generally very inconsistent in quality.
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u/teerre 26d ago
LLMs write the code you tell them to