The only people who would say this are people that don’t know programming.
LLMs are not going to replace software devs.
Wrong, this is also exactly what people selling LLMs to people who can’t code would say.
It’s this. When boards and non-tech savvy managers start making decisions based on a slick slide deck and a few visuals, enough will bite that people will be laid off. It’s already happening.
There may be a reckoning after, but wall street likes it when you cut too deep and then bounce back to the “right” (lower) headcount. Even if you’ve broken the company and they just don’t see the glide path.
It’s gonna happen. I hope it’s rare. I’d argue it’s already happening, but I doubt enough people see it underpinning recent lay offs (yet).
AI as a general concept probably will at some point. But LLMs have all but reached the end of the line and they’re not nearly smart enough.
LLMs have already reached the end of the line 🤔
I don’t believe that. At least from an implementation perspective we’re extremely early on, and I don’t see why the tech itself can’t be improved either.
Maybe it’s current iteration has hit a wall, but I don’t think anyone can really say what the future holds for it.
LLMs have been around since roughly
20162017 (comment below corrected me that Attention paper was 2017). While scaling the up has improved their performance/capabilities, there are fundamental limitations on the actual approach. Behind the scenes, LLMs (even multimodal ones like gpt4) are trying to predict what is most expected, while that can be powerful it means they can never innovate or be truth systems.For years we used things like tf-idf to vectorize words, then embeddings, now transformers (supped up embeddings). Each approach has it limits, LLMs are no different. The results we see now are surprisingly good, but don’t overcome the baseline limitations in the underlying model.
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You’re right, I thought that paper came out in 2016.
I’m not trained in formal computer science, so I’m unable to evaluate the quality of this paper’s argument, but there’s a preprint out that claims to prove that current computing architectures will never be able to advance to AGI, and that rather than accelerating, improvements are only going to slow down due to the exponential increase in resources necessary for any incremental advancements (because it’s an NP-hard problem). That doesn’t prove LLMs are end of the line, but it does suggest that additional improvements are likely to be marginal.
we’re extremely early on
Oh really! The analysis has been established since the 80’s. Its so far from early on that statement is comical
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“at some point” being like 400 years in the future? Sure.
Ok that’s probably a little bit of an exaggeration. 250 years.
I can see the statement in the same way word processing displaced secretaries.
There used to be two tiers in business. Those who wrote ideas/solutions and those who typed out those ideas into documents to be photocopied and faxed. Now the people who work on problems type their own words and email/slack/teams the information.
In the same way there are programmers who design and solve the problems, and then the coders who take those outlines and make it actually compile.
LLM will disrupt the programmers leaving the problem solvers.
There are still secretaries today. But there aren’t vast secretary pools in every business like 50 years ago.
It’ll have to improve a magnitude for that effect. Right now it’s basically an improved stack overflow.
…and only sometimes improved. And it’ll stop improving if people stop using Stack Overflow, since that’s one of the main places it’s mined for data.
Nah, it’s built into the editors and repos these days.
?
If no one uses Stack Overflow anymore, then no one posts new answers. So AI has no new info to mine.
They are mining the IDE and GitHub.
You seem to be missing what I’m saying, and missing my point. But I’m not going to try to rephrase it again.
There is no reason to believe that LLM will disrupt anyone any time soon. As it stands now the level of workmanship is absolutely terrible and there are more things to be done than anyone has enough labor to do. Making it so skilled professionals can do more literally just makes it so more companies can produce quality of work that is not complete garbage.
Juniors produce progressively more directly usable work with reason and autonomy and are the only way you develop seniors. As it stands LLM do nothing with autonomy and do much of the work they do wrong. Even with improvements they will in near term actually be a coworker. They remain something you a skilled person actually use like a wrench. In the hands of someone who knows nothing they are worth nothing. Thinking this will replace a segment of workers of any stripe is just wrong.
The problem with this take is the assertion that LLMs are going to take the place of secretaries in your analogy. The reality is that replacing junior devs with LLMs is like replacing secretaries with a network of typewriter monkeys who throw sheets of paper at a drunk MBA who decides what gets faxed.
I’m saying that devs will use LLM’s in the same way they currently use word processing to send emails instead of handing hand written notes to a secretary to format, grammar/spell check, and type.
I thought by this point everyone would know how computers work.
That, uh, did not happen.
Good take
No
I don’t know if you noticed but most of the people making decisions in the industry aren’t programmers, they’re MBAs.
Irrelevant, anyone who tries to replace their devs with LLMs will crash and burn. The lessons will be learned. But yes, many executives will make stupid ass decisions around this tech.
It’s really sad how even techheads ignore how rapidly LLM coding has come in the last 3 years and what that means in the long run.
Just look how rapidly voice recognition developed once Google started exploiting all of its users’ voice to text data. There was a point that industry experts stated ‘There will never be a general voice recognition system that is 90%+ across all languages and dialects.’ And google made one within 4 years.
The natural bounty of a no-salary programmer in a box is too great for this to ever stop being developed, and the people with the money only want more money, and not paying devs is something they’ve wanted since the coding industry literally started.
Yes its terrible now, but it is also in its infancy, like voice recognition in the late 90s it is a novelty with many hiccoughs. That won’t be the case for long and anyone who confidently thinks it can’t ever happen will be left without recourse when it does.
But that’s not even the worst part about all of this but I’m not going into black box code because all of you just argue stupid points when I do but just so you know, human programming will be a thing of the past outside of hobbyists and ultra secure systems within 20 years.
Maybe sooner
Maybe in 20 years. Maybe. But this article is quoting CEOs saying 2 years, which is bullshit.
I think it’s just as likely that in 20 years they’ll be crying because they scared enough people away from the career that there aren’t enough developers, when the magic GenAI that can write all code still doesn’t exist.
yeah 2 years is bullshit but with innovation, 10 years is still reasonable and fucking terrifying.
The one thing that LLMs have done for me is to make summarizing and correlating data in documents really easy. Take 20 docs of notes about a project and have it summarize where they are at so I can get up to speed quickly. Works surprisingly well. I haven’t had luck with code requests.
That’s not what was said. He specifically said coding.
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.
Edit: did it, thanks ChatJippity
def main(): # Check if the correct number of arguments are provided if len(sys.argv) != 2: print("Usage: python script.py <PopScienceBS>") sys.exit(1) # Get the input from the command line PopScienceBS = sys.argv[1] # Assign the input variable to the output variable LineGoUp = PopScienceBS # Print the output print(f"Line Go Up if we do: {LineGoUp}") if __name__ == "__main__": main()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
ChatJippity
I’ll start using that!
I know just enough about this to confirm that this statement is absolute horseshit
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 🙏🏻
🤣😂😪😥😢😭
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
I’ll take “things business people dont understand” for 100$.
No one hires software engineers to code. You’re hired to solve problems. All of this AI bullshit has 0 capability to solve your problems, because it can only spit out what it’s already
stolen fromseen somewhere elseIt can also throw things against the wall with no concern for fitness-to=purpose. See “None pizza, left beef”.
I’ve worked with a few PMs over my 12 year career that think devs are really only there to code like trained monkeys.
Guys that are putting billions of dollars into their AI companies making grand claims about AI replacing everyone in two years. Whoda thunk it
He who knows, does not speak. He who speaks, does not know.
–Lao Tzu…
Great answer to interview questions
What does the person “who knows” do when they have to give a presentation?
But coding never was the difficult part. It’s understanding a concept, identify a problem and solve it with the possible methods. An AI just makes the coding part faster and gives me options to quicker identify a possible solution. Thankfully there’s a never ending pile of projects, issues, todos and stackholder wants, that I don’t see how we need less programmers. Maybe we need more to deal with AI, as now people can do a lot more in house instead of outsourcing, but as soon as that threshold is reached, companies will again contact large software companies. If people want to put AI into everything, you need people feeding the AI with company specific data and instruct people to use this AI.
All I see is middle management getting replaced, because instead of a boring meeting, I could just ask an AI.
I dread meetings and I can’t wait for AIs to replace those managers. Or perhaps we’ll have even more meetings because the management wants to know why we’re so late despite the AI happily churning out meaningless codes that look so awesome like all that CSI VB GUI crap.
That’s when you write an AI auto reply cron. Let the snake eat its tail. Hehe
It’s been said before but the whiter your collar the more likely you are to be replaced by AI simply because the grunts tend to do more varied less pleibeon things.
Middle managers tend to write a lot of documents and emails which is something AI excels at. The programmers meanwhile have to come up with creative solutions to problems, and AI is less good at being creative, it basically just copy pastes known solutions from the web.
Realises devs have always joked about their jobs just being about copy-pasting solutions from StackOverflow 80% of the time
Oh God…
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.
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.
Edit: wow what a bunch of hypersensitive babies. I swear, y’all just allergic to learning or something. I just said people need to improve themselves to stay relevant, and people freak out and send me death threats. What a joke.
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.
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AI can’t do anything that hasn’t been done before. That’s never going to change.
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.
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
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.
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
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Lets wait for any LLM do a single sucessful MR on Github first before starting a project on its own. Not aware of any.
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.
Todays news: Rich assholes in suits are idiots and don’t know how their own companies are working. Make sure to share what they’re saying.
Of course they won’t be; somebody has to debug all the crap AI writes.
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Yeah writing the code isn’t really the hard part. It’s knowing what code to write and how to structure it to work with your existing code or potential future code. Knowing where things might break so you can add the correct tests or alerts. Giving time estimates on how long it will take to build the parts of the system and building in phases to meet your teams needs.
I’ve always thought that design and maintenance are the difficult and gruelling parts, and writing code is when you get to relax for a bit. Most of the time you’re in maintenance mode, and it’s harder than writing new code.
This. I’m learning a new skill right now & hardly any of it is actual writing— it’s how to arrange the pieces someone else wrote (& which sometimes AI can decently reproduce.)
When you use a computer you don’t start by mining iron, because the thing is already built
Everybody talks about AI killing programming jobs, but any developer who has had to use it knows it can’t 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.
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 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.
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.
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.
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.
I don’t understand how you could understand how LLMs work, and then write this.
Machines can learn that…
Ah, nevermind.
If you’ll excuse me saying, I feel that you are the one who is looking at something and extrapolating.
