The problem being that the time spent fixing the bugs in that 25% outweighs the time saved. Now that tools like Copilot are being widely used, studies are showing that they do not in fact boost productivity. All claims to the contrary seem to be either anecdotal or marketing fluff.
The AI tap complition is >100000% better than the coding assistants, it just saves you typing and doesn't introduce new bugs you need to fix instead of writting buggy shitty code from a text description.
I have around 7 YOE, and I have found LLMs useful for very specific questions about syntax whenever I am working in a new language. For example, I needed to write some typescript recently and asked it how can I make a type that does X.
It is not as good with questions about API documentation for popular java libraries though and it will just hallucinate APIs/method names.
If I ask it a generic question like "how can I create a class in Java to invoke this API and store the data in this database" it is pretty useless. I'm sure I could spend more time giving it a better prompt but at that point I can just write the code myself.
Overall they are a better search engine for stackoverflow, but the LLMs are not really helping me code 30% faster or whatever the latest claim is.
It'd be interesting to know how much of Google's code is written by junior engineers. I can't imagine 25% of the code is from juniors, at which point Google's CEO is either exaggerating what he considers LLM-generated code or more than just juniors are using it.
I agree with your take though, it does seem helpful to juniors but not beyond that (yet), and this OP stat seems dubious unless juniors are doing a big portion of the work.
https://www.techspot.com/news/104945-ai-coding-assistants-do...