The LLM frenzy is only unmasking something that happened long ago. The dilution started 20+ years ago when people with no real interest in CS were attracted to the software profession by the high pay and low bar to entry. Posts on Hacker News by people who liked their profession and CS topics were often met by "I'm just in in for the paycheck" and IMO that's gradually increased over the years. I've often remarked on the irony of how few hackers, in the sense of having the old-school hacker ethos, there seemed to be on Hacker News.

I’ve had to move away from thinking to meta-thinking. Most of my engineering effort is now focused on figuring out what information and process to feed a model, and then observing how it runs and tweaking the results until it’s not crap. You also stop worrying about the time it takes to code things and start worrying about tampering down on tech debt aggressively. Things that you would have never had time for before (refactoring to make the system slightly better) become incredibly possible and easy now.

If so, it sounds like a fix is relatively easy

List the things you want people to know and they can use AI to learn them

From "Why are AI agents lying, cheating and coordinating?"

"One note on wording. Below, I write that these systems “seek” or “try” things. This is shorthand for a mechanism rather than a claim about consciousness or human-like intent. We use similar shorthand when describing many other situations, like a plant seeking sunlight. A system trained by trial and error behaves as if it were pursuing whatever its training rewarded, and that as-if description is what makes its behavior predictable."

https://yoshuabengio.org/en/publication/why-are-ai-agents-ly...

So there is some attempt to remain grounded. Using shorthand wording makes it easier to reach more people with your message, the whole goal of writing a post like that, but also likely means more people are mislead into treating the short hand as the truth rather than for what it is.

I'm not saying they are alive, they have consciousness, etc.

But do we really know how LLM's(and the layers above, harness, RL, etc) work, or is there some emergent, surprising phenomena in those systems?

The typical person has not had to meaningfully learn math since the invention of calculators. Think about the consequences of that. Now imagine the effect of them ceding general thinking and creating.

Crypto was mostly grift targeting non-technical people

LLMs are a real, genuinely-useful technological innovation that happens to have arrived first in software engineering. Lots of SWEs spend their whole day talking with LLMs and feel a personal connection/expertise with the thing that's also at the top of the hype cycle for non-technical news

I think it's got to do with ownership. The less you own it the less you can tinker with it. https://news.ycombinator.com/item?id=49529072

Use it or lose it.

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