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The Eternal Sloptember

geohot.github.io

11–20 of 389 posts

Re: The Eternal Sloptember

#11
Coders underestimate the utility of AI in so many boring day to day tasks. If you freelance, that’s where the money is at, not in creating a startup that fills holes in AI offerings or in creating generic slop while hoping for ad money.

Re: The Eternal Sloptember

#12

My guess is the models just continue to get better and better When I got into agentic coding a year or two ago I was sure it was only good at autocomplete. Something happened earlier this year where the models hit a new level of capability. Everyone I know now just does agentic coding, and it’s really amazing. I think we should just try pushing this as far as we can possibly go, it really feels like the acceleration…

We're already hitting some logistical limits. Even if transformers don't have an inherent capability plateau, we only have so many GPUs and so much power to improve them, and we're finding it very difficult to expand that infrastructure. Something like 6 GW of new DCs have been announced over the past 2 years of which less than 1 GW has actually been turned on and started serving, and the deliverable dates for the rest just keep slipping. (Not to mention that the DCs are all talking as if the chips in them will last 6 years, which is turning out to be a stretch.)

Re: The Eternal Sloptember

#14
I'm in the "haven't written any code in a while" boat ATM. I'd love to see examples of issues that are so big that they warrant reverting to manual coding.

My main issue has been the inconsistent quality across between model releases and the tendency to insert older APIs or documentation, especially with command line tools.

I can understand if the model struggles with a million line monolithic codebase with a decade of cruft but can't think of why it'd be too much of a pain with new codebases.

Re: The Eternal Sloptember

#15
post #7

If nothing else, Eternal Sloptember is a term that seems obvious once you have it. I can’t believe this is the first time I’m seeing it.

If you were on Usenet before '93 the words still haunt you

I was very much unborn in '93, could you share the folk history for the record?

Re: The Eternal Sloptember

#17
With the level of ability that AI is at right now, I've found it useful personally to think of it something like a very good search over existing knowledge. Another step up in searchability in the lineage of reference books, stack overflow, GitHub etc.

Programmers are rewriting and reinventing the same techniques more often than any other vocation I can think of, and so we were primed for a really good search over prior art. The fact that AI can also adapt that prior art to your particular use case makes it even more powerful.

Much like how great success never came from cobbling together various bits of copy-pasted code from Stack Overflow though, current AI can't really build your whole project.

Re: The Eternal Sloptember

#18

My guess is the models just continue to get better and better When I got into agentic coding a year or two ago I was sure it was only good at autocomplete. Something happened earlier this year where the models hit a new level of capability. Everyone I know now just does agentic coding, and it’s really amazing. I think we should just try pushing this as far as we can possibly go, it really feels like the acceleration…

what if we're accelerating to a brick wall?

Re: The Eternal Sloptember

#19
Nah this person is dead wrong. Lets come back in 2 years and check on it. I'm willing to make a reasonable bet on these terms: companies will go even more AI native, will use even more tokens and spend even more money.

EDIT: To people downvoting me, please come up with a reasonable bet and lets try to work it out.

EDIT 2: $500 bet paid to your account on whether LLM's are going to still be used productively or not. No one?

EDIT 3: Any bet that would express the author's argument in a way that can be disproven in the future

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