[cglace]

The thing I can't wrap my head around is that I work on extremely complex AI agents every day and I know how far they are from actually replacing anyone. But then I step away from my work and I'm constantly bombarded with “agents will replace us”.

I wasted a few days trying to incorporate aider and other tools into my workflow. I had a simple screen I was working on for configuring an AI Agent. I gave screenshots of the expected output. Gave a detailed description of how it should work. Hours later I was trying to tweak the code it came up with. I scrapped everything and did it all myself in an hour.

I just don't know what to believe.

[aaronbaugher]

It kind of reminds me of the Y2K scare. Leading up to that, there were a lot of people in groups like comp.software.year-2000 who claimed to be doing Y2K fixes at places like the IRS and big corporations. They said they were just doing triage on the most critical systems, and that most things wouldn't get fixed, so there would be all sorts of failures. The "experts" who were closest to the situation, working on it in person, turned out to be completely wrong.

I try to keep that in mind when I hear people who work with LLMs, who usually have an emotional investment in AI and often a financial one, speak about them in glowing terms that just don't match up with my own small experiments.

[TeMPOraL]

I used to believe that until, over a decade later, I read stories from those ""experts" who were closest to the situation", and it turns out Y2K was serious and it was a close call.

[jmholla]

I just want to pile on here. Y2K was avoided due to a Herculean effort across the world to update systems. It was not an imaginary problem. You'll see it again in the lead up to 2038 [0].

[0]: https://en.wikipedia.org/wiki/Year_2038_problem

[spaceman_2020]

You’re biased because if you’re here, you’re likely an A-tier player used to working with other A-tier players.

But the vast majority of the world is not A players. They’re B and C players

I don’t think the people evaluating AI tools have ever worked in wholly mediocre organizations - or even know how many mediocre organizations exist

[code_for_monkey]

wish this didnt resonate with me so much. Im far from a 10x developer, and im in an organization that feels like a giant, half dead whale. Sometimes people here seem like they work on a different planet.

[naasking]

> But then I step away from my work and I'm constantly bombarded with “agents will replace us”.

An assembly language programmer might have said the same about C programming at one point. I think the point is, that once you depend on a more abstract interface that permits you to ignore certain details, that permits decades of improvements to that backend without you having to do anything. People are still experimenting with what this abstract interface is and how it will work with AI, but they've already come leaps and bounds from where they were only a couple of years ago, and it's only going to get better.

[hattmall]

There are some fields though where they can replace humans in significant capacity. Software development is probably one of the least likely for anything more than entry level, but A LOT of engineering has a very very real existential threat. Think about designing buildings. You basically just need to know a lot of rules / tables and how things interact to know what's possible and the best practices. A purpose built AI could develop many systems and back test them to complete the design. A lot of this is already handled or aided by software, but a main role of the engineer is to interface with the non-technical persons or other engineers. This is something where an agent could truly interface with the non-engineer to figure out what they want, then develop it and interact with the design software quite autonomously.

I think though there is a lot of focus on AI agents in software development though because that's just an early adopter market, just like how it's always been possible to find a lot of information on web development on the web!

[ForHackernews]

Good freaking luck! The inconsistencies of the software world pale in comparison to trying to construct any real world building: http://johnsalvatier.org/blog/2017/reality-has-a-surprising-...

[seanhunter]

   > "you basically just need to know a lot of rules..."

This comment commits one of the most common fallacies that I see really often in technical people, which is to assume that any subject you don't know anything about must be really simple.

I have no idea where this comment comes from, but my father was a chemical engineer and his father was mechanical engineer. A family friend is a structural engineer. I don't have a perspective about AI replacing people's jobs in general that is any more valuable than anyone elses, but I can say with a great deal of confidence that in those three engineering disciplines specifically literally none of any of their jobs are about knowing a bunch of rules and best practices.

Don't make the mistake of thinking that just because you don't know what someone does, that their job is easy and/or unnecessary or you could pick it up quickly. It may or may not be true but assuming it to be the case is unlikely to take you anywhere good.

[arkh]

> just

In my experience this word means you don't know whatever you're speaking about. "Just" almost always hide a ton of unknown unknowns. After being burned enough times nowadays when I'm going to use it I try to stop and start asking more questions.

[drysine]

>a main role of the engineer is to interface with the non-technical persons or other engineers

The main role of the engineer is being responsible for the building not collapsing.

[gerikson]

Most engineering fields are de jure professional, which means they can and probably will enforce limitations on the use of GenAI or its successor tech before giving up that kind of job security. Same goes for the legal profession.

Software development does not have that kind of protection.

[cheevly]

I promise the amount of time, experiments and novel approaches you’ve tested are .0001% of what others have running in stealth projects. Ive spent an average of 10 hours per day constantly since 2022 working on LLMs, and I know that even what I’ve built pales in comparison to other labs. (And im well beyond agents at this point). Agentic AI is what’s popular in the mainstream, but it’s going to be trounced by at least 2 new paradigms this year.

[handfuloflight]

Say more.

[cglace]

So what is your prediction?