Comment by Aurornis | Hacker News Reader

Comment by Aurornis | Hacker News Reader

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I've started disregarding any AI take that is all-or-nothing. These tools are useful for certain work once you've learned their limitations. Anyone making sweeping claims about vibecoding-style use being viable at scale or making claims that they're completely useless is just picking a side and running with it.

Different outlets tilt different directions. On HN and some other tech websites it's common to find declarations that LLMs are useless from people who tried the free models on ChatGPT (which isn't the coding model) and jumped to conclusions after the first few issues. On LinkedIn it's common to find influencers who used ChatGPT for a couple things at work and are ready to proclaim it's going to handle everything in the future (including writing the text of their LinkedIn post)

The most useful, accurate, and honest LLM information I've gathered comes from spaces where neither extreme prevails. You have to find people who have put in the time and are realistic about what can and cannot be accomplished. That's when you start learning the techniques for using these tools for maximum effect and where to apply them.

>> The most useful, accurate, and honest LLM information I've gathered >> comes from spaces where neither extreme prevails

Do you have any pointers to good (public) spaces like this? Your take sounds reasonable, and so I'm curious to see that middle-ground expression and discussion.

  > That's when you start *learning* the techniques for using these tools for maximum effect and where to apply them.

https://paulgraham.com/popular.html?viewfullsite=1

"They're perfectly justified: the majority of hot new whatevers do turn out to be a waste of time, and eventually go away. By delaying learning VRML, I avoided having to learn it at all."

If you’re counting on LLMs and coding tools to go the way of VRML, I guarantee you’re going to be disappointed.

This one was on HN recently: https://spectrum.ieee.org/ai-coding-degrades

The quality of code generated with LLM decreases over time.

Let us talk again after, say, five years.

You can gamble, but you can't guarantee

> The most useful, accurate, and honest LLM information I've gathered comes from spaces where neither extreme prevails. You have to find people who have put in the time and are realistic about what can and cannot be accomplished. That's when you start learning the techniques for using these tools for maximum effect and where to apply them.

This requires the level of professionalism that 97.56% of SWEs do not have

Agree 100%

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