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>While a model like GPT-4 offers unmatched suggestion quality, it's impossible to run on every keystroke (unless you charge users $1,000/month) Still alot less than the average SWE salary and this cost will go down over time. Anyway, jokes aside, I usually don't use copilot tools in my IDEs. I have zero difficulty with coding itself. I would not enable one unless i'm trying to learn a new language or something. I can see how they would be helpful for more junior level engineers, but they'd still need someone senior to check for security vulnerabilities and the like. Where LLMs come in handy is more complicated scenarios like understanding legacy spaghetti code, learning a new API without having to read the documentation, finding out how do to X in a new framework, undocumented behaviours and as a solo founder, non code tasks like marketing copy, mock customer interviews, writing data science type SQL queries to better understand my metrics, naming my subscription plans etc which I otherwise would not be that great at. For these tasks I always use GPT-4 which almost always gets good results. But its nowhere near the level where it could replace an actual engineer, even if you fed it an entire codebase. |
I'd argue the opposite - give something like chatgpt/copilot to a junior engineer and they use it to generate a bunch of overly repetitive code that they don't understand. If they're trying to write anything even slightly non trivial it's not going to work.
In order to get value from AI code generation you need to be competent enough to properly review the output.