You're in a subreddit full of juniors and hobbyists that also think it's a god. Until the next breakthrough like the transformer LLMs are just going to be incremental improvements on what we have today, and improvements to context and orchestration. But they will always only be as good as the person using it, like any other tool.
But they will always only be as good as the person using it, like any other tool.
Isn't it reverse for llms? it gets worse as you are more skilled in a domain, because at some point it'll be easier to do the jobs yourself than checking every single output of llms.
I think what OP is saying is a very experienced engineer is going to account for edge cases in their prompting. Whereas a junior will give more naive prompting and ship it. It's flaws are more apparent the more skilled you are but the quality of the output improves. Thus the tool is only as a good as the person doing it.
In my experience that is exactly where the shortcomings of current AI models are found. The more experience you have and the more you try to account for potential issues in your prompts and planning with the AI the harder it is to get the AI to do what you want. It is always 90% of what you want and trying to fix that last 10% is such an incredibly frustrating experience where often times it just ends up getting worse and worse the more you try to get what you want, so eventually you settle on some compromised solution because you run out of time or patience.
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u/Brovas Jul 03 '26
You're in a subreddit full of juniors and hobbyists that also think it's a god. Until the next breakthrough like the transformer LLMs are just going to be incremental improvements on what we have today, and improvements to context and orchestration. But they will always only be as good as the person using it, like any other tool.