this post was submitted on 22 Oct 2025
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As an amateur game dev, I believe AI will crash out for the public before it becomes truly useful for programming. I’ve heard colleagues try to use AI , but it often just creates more work. When the AI doesn’t know the answer, which is often. it makes something up, leading to errors, crashes, or hidden issues like memory leaks. I’d rather write the code correctly from the start and understand how it works, than spend hours hunting down problems in AI-generated code, only to never find the issue. Full disclosure I use Chatgpt to edit my dialogue as my English is not great.
I don't think AI code generation is going to be a revolution anytime soon, but AI voice and AI image generation is likely going to stay.
Your anecdote checks out with a study I heard about. Office teams that were using LLMs for a few months reported that results are faster, but editing took longer than doing it conventionally in the first place. Generating boiler plate code and documentation could be another very useful use case in software dev, and I don't really care if that's used. Like in your use case, spell/grammar checking, using LLMs is a natural development of the tools that we already had. Your text processors marks errors, who cares if it's powered by an LLM or by a huge heuristic rule set?
I am using them as a side tool for development. I think LLMs are already very performent for web knowledge search (e.g. replacing a search on stackoverflow), suggestions, explanations and error detection. Although is it worth the resources consumption? Not sure, but I can't afford not staying on top of the tooling available for my job. However, I agree, in my experience, the edit/agent modes are not efficient for coding, for now.
Generating secondary dialogues for a video game is quite a lower quality requirement than software engineering. So I think it could work there. It requires sounding natural, not being exact, LLMs are good at this.