Why AI hasn't replaced software engineers, and won't

christkv

I have found that the attention moves to thinking about the things I want done and planning, reading and iterating over the specs and other artefacts that will be part of running the agents. I still need to understand the code and iterate over it to get to a usable and maintainable point. I find the problem is we are reaching the top of the slop curve. I will subside because it's impossible to actually do anything useful with all the output. There will just be a ton of half-finished and abandoned projects. Whatever gets into production will require more eyes on it. I just think a lot of people are still stuck in the "holy f** I'm so productive" and working themselves into the ground being productive pumping out code. I think it's a phase that will pass.

baalimago

It most certainly will replace software engineers. What's missing is, as the article suggests, the "Delivery" bit. But that's not the realm of software engineers, that's the realm of DevOps/SRE/Cloud engineers. I work as a cloud engineer and have been contacted by multiple non-engineering friends who have now been able to create their pet projects from scratch in different languages and have it running locally, as webapps and native apps. So what they are missing is a platform to easily deploy and maintain their projects, much like a "normal" developer would. Right now it's quite tedious to set up this scaffolding, but it's absolutely possible with AGENTS.md, skills and rigid hollistic tests. Once done, non-technical people can continue developing independently without hiring any software engineers by simply telling claude/codex what they want. Claude/codex will then be able to make judgement calls based on the preset architecture, which will guide the non-technical user. So in my anecdotal case, AI has already replaced several software engineers. Once scaffolding like this is productized, I suspect that greenfield projects can be managed entirely from a product standpoint using agentic coders + platform engineering. And that is today. Imagine in 5 years.

kypro

Not buying it. The idea that deciding and delivering are things only humans can do with their intelligence seems faulty. As it stands AIs today are not always great at making decisions (but they're getting much better), and orgs of today still trust people and hold people to account, rather than their AI systems. Neither of these are strong moats. It's a moat only while AI systems have some limitations vs an expert human, and corporate processes are still extremely human-centric.

xnx

Misleading > Among the 270 jobs in the 1950 U.S. census, only one job was automated away — elevator operator. But many others were rendered obsolete by new technology, like the job of telegraph operator. In that same time farm jobs went from 15% of the workforce to 2%.

pmdr

Might never replace completely, but those remaining will be expected to pump out a lot more code so companies won't need to hire as many.

lnenad

It literally has and will even more in the future. It won't replace *all* software engineers but once the genie is out low effort low risk stuff will be done by an AI. Loveable and such have so many live projects, the alternative was a human building those.

bamboozled

The question is, are executives willing to give up all their power and status to an LLM or will “industry” just use AI to invent more bullshit jobs to keep everyone, including the exec relevant. The reason humans haven’t been replaced in many areas entirely is because humans like being someone’s.

softwaredoug

It’s not really about replacing software engineers. But about commodifying it. More software engineers (or roles responsible for code) that work for lower pay might be the trend. Or to maintain a high level of pay you wear many hats, including software.

logicchains

AI won't be put in important positions of responsibility within an organization because AI providers will never accept liability for bad decisions. You can't fire Claude if it fucks up, and it's got very limited ability to learn from its mistakes. It's also incapable of making good decisions where doing so requires synthesizing more than a few hundred thousand tokens worth of domain knowledge/experience in something that doesn't have an infinite amount of synthetic verifiable training data like code and math. In theory continuous learning (live weight updates) could help to some degree. But there's essentially no progress towards that because it requires solving a few hard, currently completely unsolved problems. 1. Weights drift over time and there's no way to re-merge them after a few tens of thousands of updates, so when a new model version was released there'd be no way to update existing continuously-learned models to that. 2. It'd allow permanent jailbreaking. And 3. A model can't learn new things without forgetting existing things, unlike humans brains which have hardware plasticity (like London taxi drivers having larger hippocampi due to having to memorize so many streets).

rdksu

The only bit AI can't replace is probably the need for a 'fall guy' or someone to take responsibility for something. This, however, will obviously not be sufficient to prevent job losses.

simianwords

Just look and see what Cloud did for software engineers? It pushed us one level higher and lowered the demand for "db experts" and "low level systems people". The only ones who remained were the strong ones who were hired into the cloud companies. The rest moved up and changed careers. Why would anyone think the same thing won't apply here? If you are still a Typescript bunny who fiddles with some newly learned React tidbit -- this won't cut it anymore. The market won't need you. Move up and adapt or move down and become an expert (harder).

dekdrop

I think it's people who were sloppy about programming are more interested in vive-coding. Because now they can make something without the mental rigour needed. Engineering as it should be is play of rigour. Those who value understanding system will continue the human aspect of it

neuroelectron

The whole field of engineering set to disappear and be replaced by contractors. Of course this is what they've always wanted. That's why they do outsourcing and the whole point of AI so, basically instead of getting paid a small salary to maintain someone's money-making machine, people will bid for jobs. They'll be more and more layers of abstraction that business owners will have to pay rent to. Until it's just basically socialism.

litver

"In this essay, we argue that there is enough evidence to reject the narrative that once AI capabilities reach a certain threshold, it will cause mass layoffs." - too late, it already did

jehnnysmith

This guy might be living under a rock.

another-dave

"Can the sandwich be further compressed? We don’t think so. At one end of the pipeline, development teams need to decide what to build." I mean, but this is talking about the process as a whole, not individual jobs. "Farmers won't be replaced by combine harvesters - we still need someone to decide what to plant and to harvest it". Sure, but if you used to have 10 labourers in a field manually ploughing with a pair of oxen and now you have one guy driving the machinery it absolutely has replaced jobs. Companies are already talking about "1 person teams" to deliver projects. We'll still have _some_ jobs but the ratio will change dramatically and engineering will move a lot closer to "team lead" role (and maybe even Product Manger role to boot)

IanCal

> software development, as a “decide-execute-deliver sandwich”. AI compresses the “execute” layer — the middle of the sandwich — but the other two layers resist automation in a way that will not be overcome by capability improvements alone. I really struggle to see why improved capabilities cannot deal with those other layers. I do not believe you have substantiated this claim about not being possible as capabilities improve. > At one end of the pipeline, development teams need to decide what to build. Developers are not the ones that do this largely. This role is far more on the side of "Product Owner". Sometimes your job covers both, but this is not the majority of the work and does not mostly require SE knowledge - some input usually. > This layer is hard to automate because it requires thinking about user needs, market signals, organizational priorities, and in some cases regulatory constraints. Hmm, these are language models that can talk through much of this already - but more importantly none of what is mentioned there requires software engineering. For parts that do (I'm sure someone would come to correct me if I said that there was none or seemed to suggest it is never ever ever relevant) this is a much smaller slice. > As AI capabilities improve, the kinds of decisions that can be delegated to AI increase over time. But this does not make the “decide” layer thinner — once a decision can be delegated to AI, it is no longer a source of competitive advantage, and the value of human decision-making migrates upward. Software increases in complexity over time, so there is no ceiling to this process. Now this is rather hidden but a huge leap in logic. The decide layer does get thinner for all the same projects, and then you simply assert that software will get more complex and so this cancels it all out. A team of 5 may end up being able to ship what a team of 50 used to, and maybe now there are 10 teams outputting more - but is there not a clear limit to this? At some point do we not just need 45 fewer people ? That there needs to be some engineers is not the same as needing anywhere near as many as we have. For a time I think we will see increased output meaning more software, but that tails off as they get better. > At the other end of the sandwich, human teams need to be accountable for what they deliver. Why? And if we assume so, why does that need a software engineer ? > It is possible that some day in the future teams will ship mission-critical code without fully testing and understanding it, You don't need to read code to test it, and people choose to ship products without fully understanding the code all the time. Literally any decision maker who is not a software engineer who knows the entire codebase does this. Companies fully ship systems that are far too complex for any single developer to even understand. And much of software isn't mission critical. Or at least, if you want to say it is then the mission is low stakes. > today’s AI is so unreliable that such haphazard practices would represent an existential threat to software teams and their customers. I'd argue for a bunch of stuff this isn't true, and the whole point of the article is "never even if they get better" which is different. > A central insight of AI as Normal Technology is that we can collectively choose to keep humans accountable through shared norms, law, and policy. Sure, we can ban AI writing code, but will we? Is there a huge collective concern for all us high paid engineers being replaced by AI?

RA_Fisher

Sadly I think this post will mislead people, bc the difficult truth (for many) is that software engineering isn't that hard and that's why AI can easily substitute that layer (lower barriers to entry than widely believed).

JimDabell

We have been aggressively and enthusiastically automating away software engineering for the entire history of the computer industry. Every time we do so, we are able to build bigger, better things more quickly. When this happens, our work becomes more valuable and expectations rise to match. The world’s appetite for software has been insatiable so far. AI hasn’t replaced software engineers because every time we become more productive, the goalposts move. There’s two things that could put an end to this. Firstly, we might finally become productive enough to exhaust the world’s appetite for software. I don’t see any evidence of this happening, but if somebody wants to make this argument, they should be clear about why this time is different to the entire history of the computer industry so far. Secondly, if AI becomes superhuman at software engineering when acting autonomously. Specifically, AI+human developer no longer outperforms AI alone. So far, all the available evidence seems to show AI as a force multiplier for developers and that for good results, at best you can have AI doing 90% of the work as long as an expert developer is driving things. There isn’t strong evidence that either of these situations is going to happen in the near future, so I think software engineers are safe for now. But if you have a narrow skill set and you are focused in particular areas (e.g. front-end web development), then I would worry more, because even if AI cannot replace software engineers in general , it’s quite likely to be able to completely consume specific domains with generalists holding the reins.

Havoc

I don’t think pointing at all the corporate coms about ai layoffs as fake invalidates the risk. The corporate stuff can be lies while the tech‘s impact could end up being real. It’s just noise in this context. Similarly this assumption (the burger diagram in the article) showing execution phase shrinks but somehow everything else expands to keep the burger size the same seems less than plausible. That said some portions of swe seem like they‘re still very far off from being threatened. Especially the portions where correctness is crucial. With say web dev you’ve got a lot more room to yolo it than say navigation code for rockets. The LLM can likely do both but I don’t think anyone is vibe coding the later any time soon