zlacker

>>tablet+(OP)
I’d love to see the authors of effusive praise of generative AI like this provide the proof of the unlimited powers of their tools in code. If GAI (or agents, or whatever comes next …) is so effective it should be quite simple to prove that by creating an AI only company and in short order producing huge amounts of serviceable code to do useful things. So far I’ve seen no sign of this, and the best use case seems to be generating text or artwork which fools humans into thinking it has coherent meaning as our minds love to fill gaps and spot patterns even where there are none. It’s also pretty good at reproducing things it has seen with variations - that can be useful.

So far in my experience watching small to medium sized companies try to use it for real work, it has been occasionally useful for exploring apis, odd bits of knowledge etc, but overall wasted more time than it has saved. I see very few signs of progress.

The time has come for llm users to put up or shut up - if it’s so great, stop telling us and show and use the code it generated on its own.

>>grey-a+ba
I think we're talking past each other. There's always been a threshold: above it, code changes are worth the effort; below it, they sit in backlog purgatory. AI tools so far seem to lower implementation costs, moving the threshold down so more backlog items become viable. The "5x productivity" crowd is excited about this expanded scope, while skeptics correctly note the highest value work hasn't fundamentally changed.

I think what's happening is two groups using "productivity" to mean completely different things: "I can implement 5x more code changes" vs "I generate 5x more business value." Both experiences are real, but they're not the same thing.

https://peoplesgrocers.com/en/writing/ai-productivity-parado...

>>marxis+ne
This is exactly what I’ve experienced. For the top-end high-complexity work I’m responsible for, it often takes a lot more effort and research to write a granular, comprehensive product spec for the LLM than it does to just jump in and do it myself.

On the flip side, it has allowed me to accomplish many lower-complexity backlog projects that I just wouldn’t have even attempted before. It expands productivity on the low end.

I’ve also used it many times to take on quality-of-life tasks that just would have been skipped before (like wrapping utility scripts in a helpful, documented command-line tool).

>>bicx+zg
> On the flip side, it has allowed me to accomplish many lower-complexity backlog projects that I just wouldn’t have even attempted before

This has been my experience at well - AI coding tools are like a very persistent junior-- that loves reading specs and documentation. The problem for AI companies is "automated burndown of your low-complexity backlog items" isn't a moneymaker, even though that's what we have. So they have to sell a dream that may be realized, or may not.

The benchmark project in the article is the perfect candidate for AI: well defined requirements with precise technical terms (RFCs), little room for undefined behavior and tons of reference implementations. This is an atypical project. I am confident AI agent write an HTTP2 server, but it will also repeatedly fail to write sensible tests for human/business processes that a junior would excel at.