This will be used as an excuse to try to drive down wages while demanding more responsibilities from developers, even though this is absolute bullshit. However, if they actually follow through with their delusions and push to build platforms on AI-generated trash code, then soon after they’ll have to hire people to fix such messes.
Translation: “We’re going to make the suite for building, testing, and deploying so obnoxiously difficult to integrate with your work environment that in two years nobody in your DevOps team will be able to get anything to a release state.”
Me, fiddling with a config file for a legacy Perl script that’s been holding up the ass-end of the business since 1996: “Uh, yeah that’s great.”
Says the person who is primarily paid with Amazon stock, wants to see that stock price rise for their own benefit, and won’t be in that job two years from now to be held accountable. Also, who has never written a kind of code. Yeah…. Ok. 🤮
That’d be an exciting world, since it’d massively increase access to software.
I am also very dubious about that claim.
In the long run, I do think that AI can legitimately handle a great deal of what humans do today. It’s something to think about, plan for, sure.
I do not think that anything we have today is remotely near being on the brink of the kind of technical threshold required to do that, and I think that even in a world where that was true, that it’d probably take more than 2 years to transition most of the industry.
I am enthusiastic about AI’s potential. I think that there is also – partly because we have a fair number of unknowns unknowns, and partly because people have a strong incentive to oversell the particular AI thing that they personally are involved with to investors and the like – a tendency to be overly-optimistic about the near-term potential.
I have another comment a while back talking about why I’m skeptical that the process of translating human-language requirements to machine-language instructions is going to be as amenable as translating human-language to human-consumable output. The gist, though, is that:
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Humans rely on stuff that “looks to us like” what’s going on in the real world to cue our brain to construct something. That’s something where the kind of synthesis that people are doing with latent diffusion software works well. An image that’s about 80% “accurate” works well enough for us; the lighting being a little odd or maybe an extra toe or something is something that we can miss. Ditto for natural-language stuff. But machine language doesn’t work like that. A CPU requires a very specific set of instructions. If 1% is “off”, a software package isn’t going to work at all.
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The process of programming involves incorporating knowledge about the real world with a set of requirements, because those requirements are in-and-of-themselves usually incomplete. I don’t think that there’s a great way to fill in those holes without having that deep knowledge of the world. This “deep knowledge and understanding of the world” is the hard stuff to do for AI. If we could do that, that’s the kind of stuff that would let us create a general artificial intelligence that could do what a human does in general. Stable Diffusion’s “understanding” of the world is limited to statistical properties of a set of 2D images; for that application, I think that we can create a very limited AI that can still produce useful output in a number of areas, which is why, in 2024, without producing an AI capable of performing generalized human tasks, we can still get some useful output from the thing. I don’t think that there’s likely a similar shortcut for much by way of programming. And hell, even for graphic arts, there’s a lot of things that this approach just doesn’t work for. I gave an example earlier in a discussion where I said “try and produce a page out of a comic book using stuff like Stable Diffusion”. It’s not really practical today; Stable Diffusion isn’t building up a 3D mental model of the world, designing an entity that stably persists from image to image, and then rendering that. It doesn’t know how it’s reasonable for objects and the like to interact. I think that to reach that point, you’re going to have to have a much-more-sophisticated understanding of the world, something that looks a lot more like what a human’s looks like.
The kind of stuff that we have today may be a component of such an AI system. But I don’t think that the answer here is going to be “take existing latent diffusion software and throw a lot of hardware at it”. I think that there’s going to have to be some significant technical breakthroughs that have not happened yet, and that we’re probably going to spend some time heading down dead-end approaches before we get to that. There’s probably going to be a lot of hard R&D before we get there, and that’s going to take time.
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A company I used to work for outsourced most of their coding to a company in India. I say most because when the code came back the internal teams anways had to put a bunch of work in to fix it and integrate it with existing systems. I imagine that, if anything, LLMs will just take the place of that overseas coding farm. The code they spit out will still need to be fixed and modified so it works with your existing systems and that work is going to require programmers.
So instead of spending 1 day writing good code, we’ll be spending a week debugging shitty code. Great.
It’ll replace brain dead CEOs before it replaces programmers.
I’m pretty sure I could write a bot right now that just regurgitates pop science bullshit and how it relates to Line Go Up business philosophy.
ChatJippity
I’ll start using that!
if lineGoUp { CollectUnearnedBonus() } else { FireSomePeople() CollectUnearnedBonus() }I think we need to start a company and commence enshittification, pronto.
This company - employee owned, right?
I’m just going to need you to sign this Contributor License Agreement assigning me all your contributions and we’ll see about shares, maybe.
Yay! I finally made it, I’m calling my mom.
I love how even here there’s line metric coding going on
I know just enough about this to confirm that this statement is absolute horseshit
It isn’t that AI will have replaced us in 24 months, it’s that we will be enslaved in 24 months. Or in the matrix. Etc.
Will the matrix it puts us in be in 1999? Because I’d take that deal.
Matrix lookin pretty good rn - 1999, stable climate, free apartment, 90s gf (she loves u) etc
Sounds like the no-ops of a decade ago and cloud will remove the need for infrastructure engineers. 😂🤣😂🤣😂🤣😂😂😂🤣
SHUT UP AND GO BACK TO OUR SHITTY YAML BASED INFRASTRUCTURE!
Fuck yml, all my homies hate yml
JSON or bust!
Ok, since YAML is a superset, I can just put the JSON into the YAML.
That sounds cursed.
Please don’t 🙏🏻
🤣😂😪😥😢😭
I feel sorry for all those people in AWS that now have him as a leader…
If, 24 months from now, most people aren’t coding, it’ll be because people like him cut jobs to make a quicker buck. Or nickel.
Well if it works, means that job wasn’t that important, and the people doing that job should improve themselves to stay relevant.
job wasn’t that important
I keep telling you that changing out the battery in the smoke alarm isn’t worth the effort and you keep telling me that the house is currently on fire, we need to get out of here immediately, and I just roll my eyes because you’re only proving my point.
Sure, believe what you want to believe. You can either adapt to what’s happening, or just get phased out. AI is happening whether you like it or not. You may as well learn to use it.
I get why you’re enthusiastic about AI. This whole comment reads like it was AI generated.
Removed by mod
You can adapt, but how you adapt matters.
AI in tech companies is like a hammer or drill. You can either get rid of your entire construction staff and replace them with a few hammers, or you can keep your staff and give each worker a hammer. In the first scenario, nothing gets done, yet jobs are replaced. In the second scenario, people keep their jobs, their jobs are easier, and the house gets built.
Yup. Most of us aren’t CEOs, so we don’t have a lot of say about how most companies are run. All we can do is improve ourselves.
For some reason, a lot of people seem to be against that. They prefer to whine.
AI can’t do anything that hasn’t been done before. That’s never going to change.
Like in Twitter?
Nah that was just a bad CEO
😜 👢
Define “works.”
Because the goals of a money-hungry CEO don’t always align with those of the workers in the company itself (or often, even the consumer). I imagine this guy will think it worked just fine as he’s enjoying his golden parachute.
Define “works”?
If you’re a CEO, cutting all your talent, enshittifying your product, and pocketing the difference in new, lower costs vs standard profits might be considered as “working”.
Hmmm maybe you’re misunderstanding me.
What I mean is “coding” is basically the grunt work of development. The real skill is understanding the requirements and building something efficiently. Tbh, I hate coding.
What tools like Gemini or ChatGPT brings to the table is the ability to create small, efficient snippets of code that works. We can then just modify it to meet our more specific requirements.
This makes things much faster, for me at least. If the time comes when the AI can generate more efficient code, making my job easier, I’d count that as “works” for me.
Oh perhaps the CEOs are the ones that need to be replaced?
Yup, notice nowhere did I say they shouldnt. People read and infer what they want
Nonsense. But then CEOs rarely know what the hell they’re talking about.
If that’s true, how come there isn’t a single serious project written exclusively or mostly be an LLM? There isn’t a single library or remotely original application made with Claude or Gemini. Not one.
Lets wait for any LLM do a single sucessful MR on Github first before starting a project on its own. Not aware of any.
My last employer had many internal tools that were fine.
They had only a moderate amount of oversight.
I had to find a new job, I’m actually thinking of walking away from software development now that there are so few jobs :(
It sucks but there’s no sense pretending this won’t have a large impact on the job landscape.
What did these tools do? I don’t see any LLm being used to creating anything working from scratch, without the human propmter doing most of the heavy lifting.
Mostly internal data cleaning stuff, close etc, which I accept is less in scope than you’re original comment.
The things you are describing sound like if-statement levels of automation, GitHub Actions with preprogrammed responses rather than LLM whatever.
If you’re worrying about being replaced by that… Go find the code, read it, and feel better.
The code was non trivial and relatively sophisticated. It performed statistical analysis on ingested data and the approach taken was statistically sound.
I was replaced by that. So was my colleague.
The job market is exceptionally tough right now and a large part of that is certainly llms.
I think taking people with statistical training out of the equation is quite dangerous, but it’s happening. In my area, everybody doing applied mathematics, statistics or analysis has been laid off.
In saying that, the produced program was quite good.
Certainly sounds more interesting than my original read of it! Sorry about that, I was grumpy.
there isn’t a single serious project written exclusively or mostly by an LLM? There isn’t a single library or remotely original application
IMHO “original” here is the key. Finding yet another clone of a Web framework ported from one language to another in order to push online a basic CMS slightly faster, I can imagine this. In fact I even bet that LLM, because they manipulate words in languages and that code can be safely (even thought not cheaply) tested within containers, could be an interesting solution for that.
… but that is NOT really creating value for anyone, unless that person is technically very savvy and thus able to leverage why a framework in a language over another creates new opportunities (say safety, performances, etc). So… for somebody who is not that savvy, “just” relying on the numerous existing already existing open-source providing exactly the value they expect, there is no incentive to re-invent.
For anything that is genuinely original, i.e something that is not a port to another architecture, a translation to another language, a slight optimization, but rather something that need just a bit of reasoning and evaluating against the value created, I’m very skeptical, even less so while pouring less resources EVEN with a radical drop in costs.
Everybody talks about AI killing programming jobs, but any developer who has had to use it knows it can do anything complex in programming. What it’s really going to replace is program managers, customer reps, makes most of HR obsolete, finance analysts, legal teams, and middle management. This people have very structured, rule based day to days. Getting an AI to write a very customized queuing system in Rust to suit your very specific business needs is nearly impossible. Getting AI to summarize Jira boards, analyze candidates experience, highlight key points of meetings (and obsolete most of them altogether), and gather data on outstanding patents is more in its wheelhouse.
I am starting to see a major uptick in recruiters reaching out to me because companies are starting to realize it was a mistake to stop hiring Software Engineers in the hopes that AI would replace them, but now my skills are going to come at a premium just like everyone else in Software Engineering with skills beyond “put a react app together”
Copilot can’t even suggest a single Ansible or Terraform task without suggesting invalid/unsupported options. I can’t imagine how bad it is at doing anything actually complex with an actual programming language.
It also doesn’t know what’s going on a couple line before it, so say I am in a language that has options for functional styling using maps and I want to keep that flow going, it will start throwing for loops at you, so you end up having to rewrite it all anyway. I have find I end up spending more time writing the prompts then validating it did what I want correctly (normally not) than just looking at the docs and doing it myself, the bonus being I don’t have to reprompt it again later because now I know how to do it
Trouble is, you’re basing all that on now, not a year from now, or 6 months from now. It’s too easy to look at it’s weaknesses today and extrapolate. I think people need to get real about coding and AI. Coding is language and rules. Machines can learn that enormously faster and more accurately than humans. The ones who survive will be those who can wield it as a tool for creativity. But if you think it won’t be capable of all the things it’s currently weak at you’re just kidding yourself unfortunately. It’ll be like anything else - a tool for an operator. Middlemen will be wiped out of the process, of course, but those with money remain those without time or expertise, and there will always be a place for people willing to step in at that point. But they won’t be coding. They’ll be designing and solving problems.
It’s based on the last few years of messaging. They’ve consistently said AI will do X, Y, and Z, and it ends up doing each of those so poorly that you need pretty much the same staff to babysit the AI. I think it’s actually a net-negative in terms of productivity for technical work because you end up having to go over the output extremely carefully to make sure its correct, whereas you’d have some level of trust with a human employee.
AI certainly has a place in a technical workflow, but it’s nowhere close to replacing human workers, at least not right now. It’ll keep eating at the fringes for the next 5 years minimum, if not indefinitely, and I think the net result will be making human workers more productive, not replacing human workers. And the more productive we are per person, the more valuable that person is, and the more work gets generated.
We are 18 months into AI replacing me in 6 months. I mean… the CEO of OpenAI as well as many researchers have already said LLMs have mostly reached their limit. They are “generalizers” and if you ask them to do anything new they hallucinate quite frequently. Trying to get AI to replace developers when it hasn’t even replaced other menial office jobs is like saying “we taught AI to drive, it will replace all F1 drivers in 6 months”.
McDonald’s tried to get AI to take over order taking. And gave up.
Yeah, it’s not going to be coming for programmer jobs anytime soon. Well, except maybe a certain class of folks that are mostly warming seats that at most get asked to prep a file for compatibility with a new Java version, mostly there to feed management ego about ‘number of developers’ and serve as a bragging point to clients.
It’s tons easier to repkace CEOs, HR, managers and so on than coders. Coders needs to be creative, an HR or manager not so much. Are they leaving three months from now you think?
I’ll start worrying when they are all gone.
An inherent flaw in transformer architecture (what all LLMs use under the hood) is the quadratic memory cost to context. The model needs 4 times as much memory to remember its last 1000 output tokens as it needed to remember the last 500. When coding anything complex, the amount of code one has to consider quickly grows beyond these limits. At least, if you want it to work.
This is a fundamental flaw with transformer - based LLMs, an inherent limit on the complexity of task they can ‘understand’. It isn’t feasible to just keep throwing memory at the problem, a fundamental change in the underlying model structure is required. This is a subject of intense research, but nothing has emerged yet.
Transformers themselves were old hat and well studied long before these models broke into the mainstream with DallE and ChatGPT.
The real work of software engineering isn’t the coding. That is like saying that being a doctor is all about reading health charts. Planning, designing, testing and maintaining software is the hard part, and it is often much more political than it is a technical challenge. I’m not worried about getting replaced by AI. In fact, LLMs ability to generate high volumes of code only makes the skills to understand it to be more in demand.
!remindme in 24 months
I will put down a solid grand that this exact same article will be printed by the exact same website 24 months from now and it will receive the exact same reception.
Nah, if it doesn’t pan out then all these folks will pretend they never said this, but in 24 months programming will be obsoleted by <insert fresh buzz here>
CEOs without a clue how things work think they know how things work.
I swear if we had no CEOs from today on the only impact would be that we wouldve less gibberish being spoken
If AI could replace anyone… it’s those dingbats. I mean, what would you say, in this given example, the CEO does… exactly? Make up random bullshit? AI does that. Write a speech? AI does that. I love how these overpaid people think they can replace the talent but they… they are absolutely required and couldn’t possibly be replaced! Talent and AI can’t buy and enjoy the extra big yacht, or private jets, or over priced cars, or a giant over sized mansion… no you need people for that.
How many times does the public have to learn if the CEO says it, he probably doesn’t know what he’s talking about. If the devs say it, listen
