Comment by xgb84j

It's not hard to use a drill or a hammer but learning how to use them as tools to make things was always the real challenge. Using LLMs in a useful way I would argue is a much more important skill than programming as was learning how to make programming useful was always the more important skill, but it depends on if you view programming as a means to an end or the end in and of itself.

If you have watched a normie use AI and thought See?! It's not rocket science! We are all the same. then buddy, you are a normie. They are very very bad at it. (If you have not watched an average someone use AI, then I highly recommend it, if for no other reason than to understand your placement on the curve.)

> Your job will be gone and so will mine.

I mean, that's probably true, but the person you are replying to is talking about the present.

>I have to disagree here. People who are really into agentic coding like to say/believe this, but come on, it's not rocket science! You literally ask the agent to do something and it does it, that's it. As long as you use a recent model it will do it really well regardless of how fancy your prompt is. There's no moat here, anyone can do it. Your job will be gone and so will mine.

As someone who's used more and more software made this way—either for hobby stuff or because I've had to for work—I just don't get it. You don't always get exactly what you ask for, and you often ask for something that is really sub-optimal in many ways.

The problem with waterfall wasn't ever solely "it takes a long time to write the code."

>You literally ask the agent to do something and it does it

It's not that simple, you have to remember at the end of the day these things are just doing next token prediction. If you don't give it the proper tokens to attend to, then your outputs won't be satisfactory.

You can get stellar outputs from LLMs, but it really is a function of how well you manage your input tokens.