The article gives the example of Bun's successful Zig to Rust of why this is the end of programming. I think that rewrite is a perfect example of why it's NOT the end of software engineering. A non-programmer could not have prompted AI to do that rewrite, and in fact a non-programmer would not have even conceived of the idea of doing that rewrite in the first place. Somebody is still needed to 1. come up with the idea that a Zig-to-Rust rewrite is necessary to achieve certain technical goals 2. prompt the AI to do the rewrite, clearly describing the before-and-after architecture, the goal of the rewrite, and technically verifying the result.
Neither 1 nor 2 can be done by someone who doesn't even know what Bun, Zig, or Rust is, let alone deeply understand how those work. In fact, even I as a programmer with decades of experience in PHP/Python/JS but without specific experience in Zig and Rust probably couldn't do a proper rewrite for a project the size of Bun.
Yeah when ever I have been worried about AI completely removing the need for any kind of programming skill I think about how much I had to guide it and stop it doing dumb things (even when using Sol or Fable).
I also tried to vibe code a machine learning thing and it got to a level where I was lost and I tried to move ahead without understanding the problem and let the agent figure it out. And despite using Fable it was a mess and I realized that I had to teach my self more before I can continue. Even worse it felt like it was working for a bit until It become clear it was trash. I would Imagine that kind of experience would annoy a lot of non-developers and they would not want to try again.
It feels like this narrative of programming and computer sciences skills being irrelevant is pushed by many groups (not just AI companies) who want to reduce the value of human skill and talent both financially and socially. It's quite insidious when you think about it, A gleeful sort of tone is detectable where the person is happy that nothing require mental effort or skill. Not that this is that article and that it seems to be saying that AI has changed everything (which I agree some what though I think people will still write some code by hand, Their are still things I code entirely by hand usually certain scripts or things I really need to understand and my intuition of them is important)
Yes but those are all semantic tasks which can be done and understood in time by the next iteration of models training at that meta-level of architectural analysis.
AI deeply understands what Bun, Zig and Rust are, how they work, can conceive of the before and after architecture (probably the hard step here), can conceive of the goal of the rewrite, and can verify (using Lean and machine-checked proofs of the before and after expected states) the final result.
They just needed us to ask. Build a sufficiently general research program that can find and iterate on ideas, and it will do the asking itself.
Sure, maybe step 2 can eventually be replaced by AI. But step 1? Why would the AI even conceive of the idea of doing a rewrite in the first place?
And rewriting is just an example. There are tons of architectural decisions that need to be made every day in the building of advanced software. This is no "correct" way to do it that the AI can know in advance, it's a technical decision to be made by an engineer.
Maybe it sees a bunch of segfaults in the Zig codebase and decides a memory safe language is better, just as the human did in Bun's rewrite. I'm not sure why you think it wouldn't have been able to conceive a rewrite.
I don't know if this is the end of programming, but i can clearly observe the gradual end of expertise in my company - people slowly forgetting architecture, principles, and how stuff works in general, in favor of code delivery speed.
And without expertise you end up asking stupid things to a token producer machine, however godlike it can be.
I really do think that people who rely on AI to make architectural dissensions will simply have a bad time later down the road when it turns out that the AI made a stupid decision.
I have noticed myself a 3 months or so ago sometimes asking AI questions for things that I knew the answer to (but had to think about) and my solution would have been better. Once I realized it I realized how despite always telling my self to think about the result I was still allowing myself to hand over some of my thinking to the AI.
What I have started doing is still doing lots of things without AI and trying to not lose those skills because I think they are still needed but AI can lull you into handing over your prefrontal cortex, which is scary.
If you care about architecture and principles, the AI is excellent in architecting around that goal too and/or helping you articulate your own intuitions. You just need to be willing to sacrifice code delivery speed. It's far from an either/or.
I have found different, often even when doing something like coming up with a database schema, the solution it chooses is not the best and and can be even terrible sometimes. It could be I suck at prompting.
I guess in most industries speed was always the primary concern. Things like architecture and principles were there only to prevent things slowing down to a crawl. A way to protect that speed
Which speed in which industry? Speed of having the idea, speed of creating a early mockup, speed of creating the prototype, speed of proof, speed of creating the process to replicate at scale, speed of mass production, speed of maintenance and evolution tasks, speed of support, speed of dismantlement, speed of keeping track of all the damn conflicting priorities between all speeds?
In building/construction industry, certainly one might expect delivery speed to matter, and humanity have literally millennia of experience in the domain, and yet it’s notoriously known to go through the roof all the time.
No, it was to build things that were good enough. I am watching initiative after initiative fail after a rapid PoC phase, the more in depth the LLM dependence the quicker the codebase becomes unmanageable.
And who will fix the slop? Not Silicon Valley programs being paid $200K or whatever. We stand on the verge of a golden age of outsourcing in software which will make all previous phases of outsourcing look like trial runs.
I live in what's probably the outsourcing capital of the world (though I thankfully don't work in those body shops).
I don't think there's going to be a rush to outsource. In fact, I suspect that it's quite the opposite scenario going to play out.
Primarily because now that the cost to produce the boring/mundane stuff that is the stuff of outsourcing (internal tooling, dashboards, ERP, integrations, QA etc.), it will likely be much more cost effective to hire 3 devs in the US and give them hefty token budgets and have much easier coordination and communication loops than outsourcing to a Bangalore body shop that will try and bill you 15 engineers for the same work.
In fact, word on the street here is that there's a significant correction in the Bangalore realty market for the first time in history thanks to the IT salaries drying up. [1]
I suspect LLMs are going to have a global worldwide deflationary effect what with white collar salaries at risk. The only counter acting force might be the distortions caused by recent wars and tariff shenanigans of the US government.
But even having said all of that I am hopeful for the eventual benefits human beings can reap from the advent of LLMS. The only thing that keeps me up at night is my lack of faith in the aging gerontocracy (worldwode phenomenon) that all our futures are in the hands of that seems to be ill equipped to handle this period of what is most likely massive upheaval and uncertainty.
Won't this mean that a lot of developers in Silicon Valley will find themselves out of a job? If the competition (AI operators) can sit 8000 miles away and be paid peanuts.
The whole point is that we’re TikToking the software industry and no one will know what to tell the ai to get the software written in a way that works. It’s in principle the same as idiocracy where no one knows how to make burrito covers anymore because shit won’t grow
I do see this as good... for my personal future career. Currently AI has caused a massive hiring stop in Consulting which is the area I want to go into. However the more terrible AI decisions there are in the future the more need for a human that can scrutinize those decision there is again. Aka Consulting will boom in a few years. (Is my hope)
This is a strong article with a distracting headline. Challenge for commenters: can you discuss the content without getting caught up in the headline?
My favorite paragraph:
> The fact that AI wrote 1M LOC and then refined it over the course of the next couple of months to produce a reliable piece of software that is currently running on millions of developer machines is absolutely mind blowing. And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short. If you can build a verification system and give proper direction, AI can produce a highly complex, highly sophisticated piece of software and it can continue to refine it until it just works.
For me, this captures what's special about the Claude Fable 5 and GPT-5.6 Sol class of models. If you can reduce a problem to a clearly verifiable end state, provide the necessary context, and equip a model with the necessary tools it can usually get to a good solution.
Reducing problems to that state and designing that environment remains a skill, and one that I expect we will be paid handsomely for.
> Reducing problems to that state and designing that environment remains a skill, and one that I expect we will be paid handsomely for.
This seems to be what AI these days seems almost super humanly good at. See coding or math I guess.
But it does beg the question, why would a programmer using AI as a tool be worse than a programmer building the harness and environment and asking AI to go hogwild? The latter is definitely faster but if it's the former, atleast I will have an understanding how the system works. Weather that is valuable is an open question as far as I am concerned
To me it’s a purpose fit solution that does actually show what LLMs are capable of. Just in the best case, with the most well defined constraints one will be able to work with.
It proves that with a sufficient spec, it can do a lot of work. The spec is always the problem though - to make the spec correct enough, one has to go thru the same process as coding it. Will LLMs surface the right tradeoffs, let alone make them? Working w frontier models all day, I can say resoundingly no, and not for a long while I think. Always looking for examples of things going well though if folks have some to share.
I think he is saying this in reference to this:
"If you can reduce a problem to a clearly verifiable end state, provide the necessary context [...]"
Which for reference i am not an engineer but a Physicist is literally one of the things we make jokes about for engineers. Not that we are much better in that regard as a verfiable end state in Physics is like realy realy dificult to get so is the necessary context.
I don't mean to imply that was easy! I think it's hard, and a skill that needs active investment. It's one of the reasons I'm not afraid for my career.
I see a lot of enthusiasm from people who work alone or who have total control over a project and nothing but abject misery from people who work in a professional setting with a group of people using coding models.
This is a terrible, shallow article, that is about what you'd come to expect.
> If you can build a verification system and give proper direction,
That's called programming. The Bun tests and oracle are the result of years of programming. If you have to spend years programming an oracle before, programming is not ended. This is not just the headline claim. They are also making the claim in the article. `What I mean by this is that I think the act of writing code manually and having other humans review it to create useful, working software is headed for extinction.`
I'd also note the $165,000 figure is cited for the 11 day sprint, but this has only been released months later with both employees and agents hammering away at it. The true cost of this rewrite is likely in the millions.
There's also the quality angle. It's taken as a given that because Claude Code is using it in production, it must be quality software. This couldn't be further from the truth. Claude Code is absolute dogshit software that nobody in their right mind would even consider using if Claude didn't gatekeep their subscription subsidy token rates behind it. It is the absolute worst of any possible harness that anybody uses seriously.
Don't get me wrong, this is impressive in some degree. It is a genuine feat of software engineering to have written a class of programs that can generate other programs of this scale. I use LLMs daily for various classes of tasks because they are helpful tools. But the claims of its relevance and impact are wildly, wildly overstated. Note also the exponential growth in Github commits, and yet there is not a single piece of non-LLM related, LLM-generated software that I use, or existing software that I have felt has improved as a result of adopting full LLM-based workflows. There is no massively popular new software that regular end consumers are using, just a bunch of .md file wrappers for certain types of developers to obsess over while failing to provide value to non-developers. To the contrary, software in general appears to be degrading even more rapidly than it already was, with major Windows issues, Github issues, outrageous security breaches [as a result of woefully incompetent security practices rather than amazingly competent offensive practices], etc. becoming more and more common.
I agree with the thesis. Development is moving towards intent and alignment and clear understanding of needs. These have always been important but in a future where code is almost free, customers will be more demanding about having their needs met, fast.
Our SaaS company is making plans to move towards bespoke development, which until now has been far too costly for most customers to accept. It also violates the multi-tenant cost/business model, so we're scrambling to figure out what hosting and ops and support agreements look like in a bespoke future.
The implications here go well beyond development. I'm seeing pretty massive changes happening in finance, consulting, HR, accounting, law, design, architecture, health, and everything else. When the value of intelligence is effectively zero, how are humans supposed to market and sell themselves in the job market? Some white collar people might try to move into physical jobs for job security, but it will only take a fraction of white collar workers to migrate to crater wages there too.
We're not ready for this. Socially, economically, and politically. Look at how we treated middle Americans who lost their manufacturing jobs when they were offshored to China. Hillary Clinton famously laughed at them and told them to "learn to code." We'll watch jobs and industries disappear while clinging to our own and praying that it's not us today.
UBI is going to be inevitable soon, but it's also woefully insufficient. Giving a developer who used to earn $100k $20k per year UBI isn't going to placate their white hot rage at the social contract being broken. We're going to need universal high income, and paying for that is going to be such a radical social change that I worry voters won't accept it until things are dire.
The time has long passed since the “inevitable” things should have come into existence, for example universal basic housing. What happened instead of the advent of it is something to behold: somehow instead of supply being provisioned in response to demand, we simply changed the excess demand into an externality. Now there’s been a lot of “rage” about this, but it hasn’t been effectual. We still have plenty of homelessness right now and no particular mechanism to control it. We may not be ready for this change, but that doesn’t mean we will accept the change instead of simply pretending the problem never existed and should never exist, if everyone just behaved right.
From TFA: "What I mean by this is that I think the act of writing code manually and having other humans review it to create useful, working software is headed for extinction."
“Since FORTRAN should virtually eliminate coding and debugging…” -- FORTRAN report, 1954 [1]
And the FORTRAN report was both right and wrong. What was meant by "coding" back then, carefully crafting machine instructions from higher level specifications, was almost entirely eliminated. It was replaced by something else, which we now call coding.
Big difference is that now C level management really tries to push this narrative down to our throats.
People who are writing and claiming thing like this should be held accountable for it. It is easy to try to scare developers that their job is going away. Especially for gaining attention. Currently I don't see difference between these claims and conspiracy theories...
Such a big disconnect in the coverage of coding models and the output they produce.
If you discard coding purity questions like style, architecture, cleanliness - the stuff they come out with is buggy & error prone.
The problems seems architectural - in that context windows are limited and you need more compute to increase them, married with the fact the models are really over confident. But if you do increase them it causes mode collapse. Yann LeCun has a really good graphic in his slides of a circle (all possible answers) and a red line coming from the centre depicting the one correct path. How do you actually stop the model going into the subsequence of wrong paths? I don't think it's possible.
I've had so many times in my day job someone has told me (Claude told them) there is a bug in my code, I look at it and nope - it just didn't look up the right file. Then you push back on it and it completely crumbles and says sorry.
I wouldn't keep an employee hired who did that over and over again and never learned
People acting like meat proxies add no value. Claude is also very eager to make conclusions without digging deeper. It has no inherent curiosity or prior knowledge about the codebase asside from what it can see.
Hm. I'm someone who stills prefers to code by hand, and one of my hobbies is to go do some work in my blacksmith shop down in my barn. While my wife enjoys making our own clothes by hand and quilting.
OK, I think I'm going to bow out of these discussions. Clearly I'm not as into tech as I though I was.
It's a highly paid, in demand career path where formal education is optional.
They came for the sysadmins first because they had more power, but they were always coming for you.
Even if "Agentic Coding" doesn't solve programming, there is an aligned incentive not to care, I've heard directly from the executives at large companies that they despise the amount of leverage software programmers have... and now they have an excuse to end it on a unified front.
That is sufficed to say that many people in our profession don't actually care about software development or programming, they just saw a lucrative career path.
My personal and somewhat bitter opinion is that the profession will be more enjoyable for me once all the people who are only in it for money leave. I can live a blue collar salary life working in tech and still enjoy it. Maybe I'll have less scrum masters and shit. Thank god.
If I thought this would happen I would've done something else with my life. There's still some fun to be had, and I'll probably stay in the industry because it pays well and I have history here, but the magic has largely died.
I essentially have the opposite opinion, you're going to lose people who had a lot of passion and be left with people who are content writing prompts for money.
My personal take is that the AI era will be a rough brush that will help shed all the accumulated cruft in this profession.
I think highly technical, knowledgable people will remain, and thrive in a few years, and all the rest will move on to the next fad, or whatever pays the most.
The reason a segment of the current market will remain is because LLMs still need steering, we are not at a point where an abstract idea can go from Tweet to product, and we are many many leagues away from that. Of course, this has been noted to oblivion before, so I'm not really providing shocker value at all here.
I think the best glimpse into the future is the bugginess and engineering laziness of Claude Code itself.
New versions ship daily and I seem to hit brand new issues every day. They disappear after a few more updates, but it's damn annoying to keep up instead of doing work, and the direction of changes is lacking at best. The underlying technology otherwise seems nothing short of a miracle, but the contrast is eye-opening.
In industries where this is acceptable, that's the future. In ones that can't tolerate it, it isn't. I hadn't expected software engineering itself to be one of the former but it's kinda obvious in retrospective.
I’m still looking out for the end of programming for the human eye: these models are still pretty bad at any kind of UI that isn’t some React dashboard or single page report. For example, iOS / SwiftUI design. Sure, they can write the code just fine, but I’ve had a hard time just letting them vibe out a basic View with Sections that doesn’t look slopped out.
LLMs will accelerate the proliferation and searchability of ideas. Many times I've been using an LLM and it'll suggest ideas I would have never come across naturally that have been beneficial to whatever I happened to be implementing. For learning in general, it's been the most delightful tool I've ever used.
On the other hand, if you're working in an industry where you and your coworkers are developing novel solutions that aren't widely known, chances are you'll still be doing that by hand with some light LLM automation. There are industries with a lot of gatekept secrets where LLMs will be less useful. What I will say on that matter is this: if you weren't surprised frontier labs stole copyrighted work for training data, you'd do well to mind what you push through their systems.
In our shop, we are understanding that the art of "designing and implementing algorithms, step-by-step specifications of procedures, by writing code in one or more programming languages" (Source: wikipedia) shifted to LLMs does not mean that programming has ended, but that expectations around what and how humans do programming has changed and will continue to change. We still need humans who understand how databases should work and should be designed/evolved because these humans are the consumers of the programs. The prompters (programmers) are the consumers. LLMs are not consumers. Without programmers, LLMs don't do any work.
Considering the direction that InfluxDB has taken over the years, making insanely terrible product and tech decisions, chasing shiny new things, breaking the Open Source edition further and further while not being able to offer a competent sales process for the commercial one, I think it's fair to take the opinions of the author with a mountain of salt.
LLMs are scarily good at translation, whether between natural or between programming languages. Also very good at re-implementing the stuff that has been provably done before. And, arguably, 90-95% of writing code is exactly that.
I'm no expert, but it feels like this exact thing is how it ends up eating itself. For two reasons.
- Eventually the universe of "provably done before" is now all LLM genned code. So the training data quality starts a slow decline.
- That it's "good enough" now for 90+% of the work kills the pipeline for any new human software experts. So they never gain the experience and insight to be able to steer the AI to produce ok-ish code. Existing experts age out. This cycles with the bullet above over time. And at some point we're stalled, all code is now mediocre at best and while output is high, innovation/evolution is low. Or whatever innovation we have is coming from a very small circle without much natural competition.
In my experience they still struggle a lot though. They're great at 1 to 1 translations but they will fight the target language to get there tho. A lot of the rust rewrites I've seen done by AI contain a lot of patterns that any rust dev worth it's salt will scoff at.
The end of programming and the birth of metaprogramming. The art of writing programs that write programs, which itself is significantly harder than writing programs themselves. In fact I'm glad to see this happening because at most shops the use of metaprogramming is minimal to non-existant. (see Linux/Chromium/Firefox/Android)
> And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short.
It's not. If you give it a reference implementation, and unless the LLM/agent cheats, you'd get the migration minus undocumented/untested behavior. I've done that with different domain, migrating existing numerical code from Fortran to Rust. When working on the same codebase, agents routinely shit the bed unless given increasingly specific and concrete specs.
It's simply a spectrum between "make an airbnb for ants, make no mistakes" and providing an actual specification (and I consider an implementation to be such). What you don't provide and account for from the beginning will be paid in tokens later. That puts a price label on technical debt, which is interesting in itself, and a perverse incentive for AI companies.
He is right. The GitHub graphs show that most code is already no longer written by humans, and the shape of the graphs (as well as the recent pace of LLM progress as measured by various benchmarks) tell us that human programming is going to become a niche activity in the near future.
Nope. Not yet. The frontier still produces slop and never refactors. Your code base will grow with the square of your features and grind to a halt. God speed to folks that work at this shop.
if you tell it to do a thing it'll try it's best to make you think that it was done. I rarely get good refactors from AI unless I tell it specifically what to do.
It's just another tool. Programming is/can be fun. People still hand turn wood, and make their own furniture, even though Ikea exists.
Or maybe 'code' just gets pushed down a level like assembly did when C was invented, for example. As a percentage very few people look at assembly in comparison to the 1960s-80s.
The main reason that I'm in the process of switching jobs is to get more money, in case we are fucked as a profession later on. So yeah, even if I don't necessarily believe this is the future, I am certainly making sure that if it is the future I will be more comfortable.
I'm going to separate this from the title, versus the contents on the post
on the bun rewrite, this matches my experience
it's always been worth completely ignoring people that had a negative experience with AI-assisted coding, because others of us have been entirely functional. the slow trickle of examples has always been because it was counterproductive to tell anyone that your project or service was AI-assisted in coding or entirely vibe coded.
but now, with bun being an Anthropic project and their whole thing is showing examples that would speed up everyone else, the truth is out there. good move by them.
bun is a fast runtime and will save millions of projects time and compute costs in CI/CD and redeployments
on the title, I disagree, but with a twist. manually coding is just not necessary, but the ability to get results, and use available compute resources efficiently and at low cost are still disciplines. I don't just mean "architecture", I mean a more specific part of architecture like knowing that your postgres instance can already be an event based architecture and you don't need the cloud provider's pub/sub arrangement at all.
right now, AI isn't going to do that for you. but regarding the discipline, I don't have pride over that, I think that's a major point for people, a level of gatekeeping and pride. this isn't what we need, this isn't what companies need, everyone always needed results.
people in this career are concerned about the billable rate when people with less familiarity with the discipline can deliver results, and thats where I also see a different outcome: delivering results in software still has some unique attributes compared to almost every role in an organization.
A, it just has to be done. B, it's still one of the only roles where your workers can compete directly against you whenever they feel content enough to do so, or discontent with how you are paying them.
Software engineers have little to no overhead costs of running their own thing, they have no licenses and hence no geographic limitation compared to your accountants and lawyers, and they also have enough money to cover the little overhead costs they do incur, something even your sales team doesn't have before getting caught in a lead trading ponzi scheme. The major markets for software engineers (California) nullifies any non-compete you were relying on. It doesn't matter who is doing the software, whether it was someone that was previously doing HR, or someone that built an identity around coding, it just has to be done.
But this should translate into hiring, right now, the importance and cost reinforces teams to want to interview for something that they think "should" be gatekept. multi week, multi month, hiring processes to prove someone has a cognitive ability. but this isn't necessary, people should be able to come into the effort, the same way someone can pick up a broom. the same way a sailor on an old expedition picked up an oar and splits the bounty during the trip.
The article gives the example of Bun's successful Zig to Rust of why this is the end of programming. I think that rewrite is a perfect example of why it's NOT the end of software engineering. A non-programmer could not have prompted AI to do that rewrite, and in fact a non-programmer would not have even conceived of the idea of doing that rewrite in the first place. Somebody is still needed to 1. come up with the idea that a Zig-to-Rust rewrite is necessary to achieve certain technical goals 2. prompt the AI to do the rewrite, clearly describing the before-and-after architecture, the goal of the rewrite, and technically verifying the result.
Neither 1 nor 2 can be done by someone who doesn't even know what Bun, Zig, or Rust is, let alone deeply understand how those work. In fact, even I as a programmer with decades of experience in PHP/Python/JS but without specific experience in Zig and Rust probably couldn't do a proper rewrite for a project the size of Bun.
Yeah when ever I have been worried about AI completely removing the need for any kind of programming skill I think about how much I had to guide it and stop it doing dumb things (even when using Sol or Fable).
I also tried to vibe code a machine learning thing and it got to a level where I was lost and I tried to move ahead without understanding the problem and let the agent figure it out. And despite using Fable it was a mess and I realized that I had to teach my self more before I can continue. Even worse it felt like it was working for a bit until It become clear it was trash. I would Imagine that kind of experience would annoy a lot of non-developers and they would not want to try again.
It feels like this narrative of programming and computer sciences skills being irrelevant is pushed by many groups (not just AI companies) who want to reduce the value of human skill and talent both financially and socially. It's quite insidious when you think about it, A gleeful sort of tone is detectable where the person is happy that nothing require mental effort or skill. Not that this is that article and that it seems to be saying that AI has changed everything (which I agree some what though I think people will still write some code by hand, Their are still things I code entirely by hand usually certain scripts or things I really need to understand and my intuition of them is important)
Yes but those are all semantic tasks which can be done and understood in time by the next iteration of models training at that meta-level of architectural analysis.
AI deeply understands what Bun, Zig and Rust are, how they work, can conceive of the before and after architecture (probably the hard step here), can conceive of the goal of the rewrite, and can verify (using Lean and machine-checked proofs of the before and after expected states) the final result.
They just needed us to ask. Build a sufficiently general research program that can find and iterate on ideas, and it will do the asking itself.
Sure, maybe step 2 can eventually be replaced by AI. But step 1? Why would the AI even conceive of the idea of doing a rewrite in the first place?
And rewriting is just an example. There are tons of architectural decisions that need to be made every day in the building of advanced software. This is no "correct" way to do it that the AI can know in advance, it's a technical decision to be made by an engineer.
Maybe it sees a bunch of segfaults in the Zig codebase and decides a memory safe language is better, just as the human did in Bun's rewrite. I'm not sure why you think it wouldn't have been able to conceive a rewrite.
Source code transpilers were a thing since forever.
We'd guess that LLMs probably make them cheaper, but there's no real world data on this.
I don't know if this is the end of programming, but i can clearly observe the gradual end of expertise in my company - people slowly forgetting architecture, principles, and how stuff works in general, in favor of code delivery speed.
And without expertise you end up asking stupid things to a token producer machine, however godlike it can be.
It's hard not to extrapolate...
I really do think that people who rely on AI to make architectural dissensions will simply have a bad time later down the road when it turns out that the AI made a stupid decision.
I have noticed myself a 3 months or so ago sometimes asking AI questions for things that I knew the answer to (but had to think about) and my solution would have been better. Once I realized it I realized how despite always telling my self to think about the result I was still allowing myself to hand over some of my thinking to the AI.
What I have started doing is still doing lots of things without AI and trying to not lose those skills because I think they are still needed but AI can lull you into handing over your prefrontal cortex, which is scary.
If you care about architecture and principles, the AI is excellent in architecting around that goal too and/or helping you articulate your own intuitions. You just need to be willing to sacrifice code delivery speed. It's far from an either/or.
I have found different, often even when doing something like coming up with a database schema, the solution it chooses is not the best and and can be even terrible sometimes. It could be I suck at prompting.
I guess in most industries speed was always the primary concern. Things like architecture and principles were there only to prevent things slowing down to a crawl. A way to protect that speed
Which speed in which industry? Speed of having the idea, speed of creating a early mockup, speed of creating the prototype, speed of proof, speed of creating the process to replicate at scale, speed of mass production, speed of maintenance and evolution tasks, speed of support, speed of dismantlement, speed of keeping track of all the damn conflicting priorities between all speeds?
In building/construction industry, certainly one might expect delivery speed to matter, and humanity have literally millennia of experience in the domain, and yet it’s notoriously known to go through the roof all the time.
No, it was to build things that were good enough. I am watching initiative after initiative fail after a rapid PoC phase, the more in depth the LLM dependence the quicker the codebase becomes unmanageable.
It is about functionality.
Functionality iterations or adaptations are just faster with good architecture and principles.
There's zero evidence to support the notion that LLMs help deliver software quicker.
And who will fix the slop? Not Silicon Valley programs being paid $200K or whatever. We stand on the verge of a golden age of outsourcing in software which will make all previous phases of outsourcing look like trial runs.
I live in what's probably the outsourcing capital of the world (though I thankfully don't work in those body shops).
I don't think there's going to be a rush to outsource. In fact, I suspect that it's quite the opposite scenario going to play out.
Primarily because now that the cost to produce the boring/mundane stuff that is the stuff of outsourcing (internal tooling, dashboards, ERP, integrations, QA etc.), it will likely be much more cost effective to hire 3 devs in the US and give them hefty token budgets and have much easier coordination and communication loops than outsourcing to a Bangalore body shop that will try and bill you 15 engineers for the same work.
In fact, word on the street here is that there's a significant correction in the Bangalore realty market for the first time in history thanks to the IT salaries drying up. [1]
I suspect LLMs are going to have a global worldwide deflationary effect what with white collar salaries at risk. The only counter acting force might be the distortions caused by recent wars and tariff shenanigans of the US government.
But even having said all of that I am hopeful for the eventual benefits human beings can reap from the advent of LLMS. The only thing that keeps me up at night is my lack of faith in the aging gerontocracy (worldwode phenomenon) that all our futures are in the hands of that seems to be ill equipped to handle this period of what is most likely massive upheaval and uncertainty.
[1] https://timesofindia.indiatimes.com/real-estate/news/housing...
Project "Death by a thousand cuts"
Won't this mean that a lot of developers in Silicon Valley will find themselves out of a job? If the competition (AI operators) can sit 8000 miles away and be paid peanuts.
The whole point is that we’re TikToking the software industry and no one will know what to tell the ai to get the software written in a way that works. It’s in principle the same as idiocracy where no one knows how to make burrito covers anymore because shit won’t grow
Maybe a super smart AI will take over the part of telling the smaller AI's what to do.
Humanity can then relax in floating chairs drinking soft drinks and consuming AI generated entertainment.
This is cope. There is no going back to artisan programming. Any issues will also be fixed by ai agents.
Sufficiently complex software is something agents still struggle a lot with
Patching over the architectural nightmares LLMs pour out is I think the opposite of artisan programming.
I do see this as good... for my personal future career. Currently AI has caused a massive hiring stop in Consulting which is the area I want to go into. However the more terrible AI decisions there are in the future the more need for a human that can scrutinize those decision there is again. Aka Consulting will boom in a few years. (Is my hope)
This is a strong article with a distracting headline. Challenge for commenters: can you discuss the content without getting caught up in the headline?
My favorite paragraph:
> The fact that AI wrote 1M LOC and then refined it over the course of the next couple of months to produce a reliable piece of software that is currently running on millions of developer machines is absolutely mind blowing. And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short. If you can build a verification system and give proper direction, AI can produce a highly complex, highly sophisticated piece of software and it can continue to refine it until it just works.
For me, this captures what's special about the Claude Fable 5 and GPT-5.6 Sol class of models. If you can reduce a problem to a clearly verifiable end state, provide the necessary context, and equip a model with the necessary tools it can usually get to a good solution.
Reducing problems to that state and designing that environment remains a skill, and one that I expect we will be paid handsomely for.
> Reducing problems to that state and designing that environment remains a skill, and one that I expect we will be paid handsomely for.
This seems to be what AI these days seems almost super humanly good at. See coding or math I guess.
But it does beg the question, why would a programmer using AI as a tool be worse than a programmer building the harness and environment and asking AI to go hogwild? The latter is definitely faster but if it's the former, atleast I will have an understanding how the system works. Weather that is valuable is an open question as far as I am concerned
To me it’s a purpose fit solution that does actually show what LLMs are capable of. Just in the best case, with the most well defined constraints one will be able to work with.
It proves that with a sufficient spec, it can do a lot of work. The spec is always the problem though - to make the spec correct enough, one has to go thru the same process as coding it. Will LLMs surface the right tradeoffs, let alone make them? Working w frontier models all day, I can say resoundingly no, and not for a long while I think. Always looking for examples of things going well though if folks have some to share.
Simon - I hope this is not a rude question, but do you work with other engineers?
Yes, why do you ask?
I think he is saying this in reference to this: "If you can reduce a problem to a clearly verifiable end state, provide the necessary context [...]"
Which for reference i am not an engineer but a Physicist is literally one of the things we make jokes about for engineers. Not that we are much better in that regard as a verfiable end state in Physics is like realy realy dificult to get so is the necessary context.
I don't mean to imply that was easy! I think it's hard, and a skill that needs active investment. It's one of the reasons I'm not afraid for my career.
I see a lot of enthusiasm from people who work alone or who have total control over a project and nothing but abject misery from people who work in a professional setting with a group of people using coding models.
I'm just building some data points.
I don't work with a large team, so I don't personally experience the hell of coworkers dumping thousands of lines of unreviewed slop on me.
(I get a bit of exposure to that from my open source projects but it's much easier to close or ignore those.)
This is a terrible, shallow article, that is about what you'd come to expect.
> If you can build a verification system and give proper direction,
That's called programming. The Bun tests and oracle are the result of years of programming. If you have to spend years programming an oracle before, programming is not ended. This is not just the headline claim. They are also making the claim in the article. `What I mean by this is that I think the act of writing code manually and having other humans review it to create useful, working software is headed for extinction.`
I'd also note the $165,000 figure is cited for the 11 day sprint, but this has only been released months later with both employees and agents hammering away at it. The true cost of this rewrite is likely in the millions.
There's also the quality angle. It's taken as a given that because Claude Code is using it in production, it must be quality software. This couldn't be further from the truth. Claude Code is absolute dogshit software that nobody in their right mind would even consider using if Claude didn't gatekeep their subscription subsidy token rates behind it. It is the absolute worst of any possible harness that anybody uses seriously.
Don't get me wrong, this is impressive in some degree. It is a genuine feat of software engineering to have written a class of programs that can generate other programs of this scale. I use LLMs daily for various classes of tasks because they are helpful tools. But the claims of its relevance and impact are wildly, wildly overstated. Note also the exponential growth in Github commits, and yet there is not a single piece of non-LLM related, LLM-generated software that I use, or existing software that I have felt has improved as a result of adopting full LLM-based workflows. There is no massively popular new software that regular end consumers are using, just a bunch of .md file wrappers for certain types of developers to obsess over while failing to provide value to non-developers. To the contrary, software in general appears to be degrading even more rapidly than it already was, with major Windows issues, Github issues, outrageous security breaches [as a result of woefully incompetent security practices rather than amazingly competent offensive practices], etc. becoming more and more common.
> That's called programming. The Bun tests and oracle are the result of years of programming.
I completely agree. That's why I warned about getting distracted by the headline.
I agree with the thesis. Development is moving towards intent and alignment and clear understanding of needs. These have always been important but in a future where code is almost free, customers will be more demanding about having their needs met, fast.
Our SaaS company is making plans to move towards bespoke development, which until now has been far too costly for most customers to accept. It also violates the multi-tenant cost/business model, so we're scrambling to figure out what hosting and ops and support agreements look like in a bespoke future.
The implications here go well beyond development. I'm seeing pretty massive changes happening in finance, consulting, HR, accounting, law, design, architecture, health, and everything else. When the value of intelligence is effectively zero, how are humans supposed to market and sell themselves in the job market? Some white collar people might try to move into physical jobs for job security, but it will only take a fraction of white collar workers to migrate to crater wages there too.
We're not ready for this. Socially, economically, and politically. Look at how we treated middle Americans who lost their manufacturing jobs when they were offshored to China. Hillary Clinton famously laughed at them and told them to "learn to code." We'll watch jobs and industries disappear while clinging to our own and praying that it's not us today.
UBI is going to be inevitable soon, but it's also woefully insufficient. Giving a developer who used to earn $100k $20k per year UBI isn't going to placate their white hot rage at the social contract being broken. We're going to need universal high income, and paying for that is going to be such a radical social change that I worry voters won't accept it until things are dire.
The time has long passed since the “inevitable” things should have come into existence, for example universal basic housing. What happened instead of the advent of it is something to behold: somehow instead of supply being provisioned in response to demand, we simply changed the excess demand into an externality. Now there’s been a lot of “rage” about this, but it hasn’t been effectual. We still have plenty of homelessness right now and no particular mechanism to control it. We may not be ready for this change, but that doesn’t mean we will accept the change instead of simply pretending the problem never existed and should never exist, if everyone just behaved right.
From TFA: "What I mean by this is that I think the act of writing code manually and having other humans review it to create useful, working software is headed for extinction."
“Since FORTRAN should virtually eliminate coding and debugging…” -- FORTRAN report, 1954 [1]
And the FORTRAN report was both right and wrong. What was meant by "coding" back then, carefully crafting machine instructions from higher level specifications, was almost entirely eliminated. It was replaced by something else, which we now call coding.
[1] http://www.softwarepreservation.org/projects/FORTRAN/BackusE...
Big difference is that now C level management really tries to push this narrative down to our throats. People who are writing and claiming thing like this should be held accountable for it. It is easy to try to scare developers that their job is going away. Especially for gaining attention. Currently I don't see difference between these claims and conspiracy theories...
So you are suggesting we will soon drop the "vibe" from "vibe coding"?
Such a big disconnect in the coverage of coding models and the output they produce.
If you discard coding purity questions like style, architecture, cleanliness - the stuff they come out with is buggy & error prone.
The problems seems architectural - in that context windows are limited and you need more compute to increase them, married with the fact the models are really over confident. But if you do increase them it causes mode collapse. Yann LeCun has a really good graphic in his slides of a circle (all possible answers) and a red line coming from the centre depicting the one correct path. How do you actually stop the model going into the subsequence of wrong paths? I don't think it's possible.
I've had so many times in my day job someone has told me (Claude told them) there is a bug in my code, I look at it and nope - it just didn't look up the right file. Then you push back on it and it completely crumbles and says sorry.
I wouldn't keep an employee hired who did that over and over again and never learned
> Claude told them
People acting like meat proxies add no value. Claude is also very eager to make conclusions without digging deeper. It has no inherent curiosity or prior knowledge about the codebase asside from what it can see.
Really didn't see programming going the way of blacksmithing in my lifetime, let alone early in my lifetime.
Hm. I'm someone who stills prefers to code by hand, and one of my hobbies is to go do some work in my blacksmith shop down in my barn. While my wife enjoys making our own clothes by hand and quilting.
OK, I think I'm going to bow out of these discussions. Clearly I'm not as into tech as I though I was.
Why not?
It's a highly paid, in demand career path where formal education is optional.
They came for the sysadmins first because they had more power, but they were always coming for you.
Even if "Agentic Coding" doesn't solve programming, there is an aligned incentive not to care, I've heard directly from the executives at large companies that they despise the amount of leverage software programmers have... and now they have an excuse to end it on a unified front.
That is sufficed to say that many people in our profession don't actually care about software development or programming, they just saw a lucrative career path.
My personal and somewhat bitter opinion is that the profession will be more enjoyable for me once all the people who are only in it for money leave. I can live a blue collar salary life working in tech and still enjoy it. Maybe I'll have less scrum masters and shit. Thank god.
If I thought this would happen I would've done something else with my life. There's still some fun to be had, and I'll probably stay in the industry because it pays well and I have history here, but the magic has largely died.
I essentially have the opposite opinion, you're going to lose people who had a lot of passion and be left with people who are content writing prompts for money.
I agree with you.
My personal take is that the AI era will be a rough brush that will help shed all the accumulated cruft in this profession.
I think highly technical, knowledgable people will remain, and thrive in a few years, and all the rest will move on to the next fad, or whatever pays the most.
The reason a segment of the current market will remain is because LLMs still need steering, we are not at a point where an abstract idea can go from Tweet to product, and we are many many leagues away from that. Of course, this has been noted to oblivion before, so I'm not really providing shocker value at all here.
I think the best glimpse into the future is the bugginess and engineering laziness of Claude Code itself.
New versions ship daily and I seem to hit brand new issues every day. They disappear after a few more updates, but it's damn annoying to keep up instead of doing work, and the direction of changes is lacking at best. The underlying technology otherwise seems nothing short of a miracle, but the contrast is eye-opening.
In industries where this is acceptable, that's the future. In ones that can't tolerate it, it isn't. I hadn't expected software engineering itself to be one of the former but it's kinda obvious in retrospective.
I’m still looking out for the end of programming for the human eye: these models are still pretty bad at any kind of UI that isn’t some React dashboard or single page report. For example, iOS / SwiftUI design. Sure, they can write the code just fine, but I’ve had a hard time just letting them vibe out a basic View with Sections that doesn’t look slopped out.
LLMs will accelerate the proliferation and searchability of ideas. Many times I've been using an LLM and it'll suggest ideas I would have never come across naturally that have been beneficial to whatever I happened to be implementing. For learning in general, it's been the most delightful tool I've ever used.
On the other hand, if you're working in an industry where you and your coworkers are developing novel solutions that aren't widely known, chances are you'll still be doing that by hand with some light LLM automation. There are industries with a lot of gatekept secrets where LLMs will be less useful. What I will say on that matter is this: if you weren't surprised frontier labs stole copyrighted work for training data, you'd do well to mind what you push through their systems.
In our shop, we are understanding that the art of "designing and implementing algorithms, step-by-step specifications of procedures, by writing code in one or more programming languages" (Source: wikipedia) shifted to LLMs does not mean that programming has ended, but that expectations around what and how humans do programming has changed and will continue to change. We still need humans who understand how databases should work and should be designed/evolved because these humans are the consumers of the programs. The prompters (programmers) are the consumers. LLMs are not consumers. Without programmers, LLMs don't do any work.
Considering the direction that InfluxDB has taken over the years, making insanely terrible product and tech decisions, chasing shiny new things, breaking the Open Source edition further and further while not being able to offer a competent sales process for the commercial one, I think it's fair to take the opinions of the author with a mountain of salt.
LLMs are scarily good at translation, whether between natural or between programming languages. Also very good at re-implementing the stuff that has been provably done before. And, arguably, 90-95% of writing code is exactly that.
I'm no expert, but it feels like this exact thing is how it ends up eating itself. For two reasons.
- Eventually the universe of "provably done before" is now all LLM genned code. So the training data quality starts a slow decline.
- That it's "good enough" now for 90+% of the work kills the pipeline for any new human software experts. So they never gain the experience and insight to be able to steer the AI to produce ok-ish code. Existing experts age out. This cycles with the bullet above over time. And at some point we're stalled, all code is now mediocre at best and while output is high, innovation/evolution is low. Or whatever innovation we have is coming from a very small circle without much natural competition.
In my experience they still struggle a lot though. They're great at 1 to 1 translations but they will fight the target language to get there tho. A lot of the rust rewrites I've seen done by AI contain a lot of patterns that any rust dev worth it's salt will scoff at.
The end of programming and the birth of metaprogramming. The art of writing programs that write programs, which itself is significantly harder than writing programs themselves. In fact I'm glad to see this happening because at most shops the use of metaprogramming is minimal to non-existant. (see Linux/Chromium/Firefox/Android)
> And you can say, “well it’s not that impressive because they had an oracle to compare against, so it was simple to go from one language to another”, but I think that’s selling this entire thing short.
It's not. If you give it a reference implementation, and unless the LLM/agent cheats, you'd get the migration minus undocumented/untested behavior. I've done that with different domain, migrating existing numerical code from Fortran to Rust. When working on the same codebase, agents routinely shit the bed unless given increasingly specific and concrete specs.
It's simply a spectrum between "make an airbnb for ants, make no mistakes" and providing an actual specification (and I consider an implementation to be such). What you don't provide and account for from the beginning will be paid in tokens later. That puts a price label on technical debt, which is interesting in itself, and a perverse incentive for AI companies.
I think I’m on the right track by building a feature flag service for AI coding agents. It will serve coding agents rather than human users.
Controversial title just to stir the engagement. Congrats, you're on top of HN!
The title accurately reflects what is in the post. Therefore your assessment of the title is unfair.
He is right. The GitHub graphs show that most code is already no longer written by humans, and the shape of the graphs (as well as the recent pace of LLM progress as measured by various benchmarks) tell us that human programming is going to become a niche activity in the near future.
Or is it a transition to truly declarative programming?
The Bun from Zig into Rust move is at best doing a "burn out on the main street"
Loud with lots of smoke, but didn't go anywhere!
Nope. Not yet. The frontier still produces slop and never refactors. Your code base will grow with the square of your features and grind to a halt. God speed to folks that work at this shop.
You can often just tell it to refactor though. That's like a scheduled harness thing, not a game changer.
Perhaps, but you need to tell it how to refactor or you’ll get more gibberish and helper functions. Hence, programming.
if you tell it to do a thing it'll try it's best to make you think that it was done. I rarely get good refactors from AI unless I tell it specifically what to do.
It's just another tool. Programming is/can be fun. People still hand turn wood, and make their own furniture, even though Ikea exists.
Or maybe 'code' just gets pushed down a level like assembly did when C was invented, for example. As a percentage very few people look at assembly in comparison to the 1960s-80s.
The main reason that I'm in the process of switching jobs is to get more money, in case we are fucked as a profession later on. So yeah, even if I don't necessarily believe this is the future, I am certainly making sure that if it is the future I will be more comfortable.
I don't think we'll be fucked as a profession. That's just SV hype from people living far away from reality
What are you switching to?
Switching jobs, not profession. I am currently very underpaid.
What to?
Clickbait title for a story about a bot translating a program from one language to another. Some people get hyped over the most trivial things.
I'm going to separate this from the title, versus the contents on the post
on the bun rewrite, this matches my experience
it's always been worth completely ignoring people that had a negative experience with AI-assisted coding, because others of us have been entirely functional. the slow trickle of examples has always been because it was counterproductive to tell anyone that your project or service was AI-assisted in coding or entirely vibe coded.
but now, with bun being an Anthropic project and their whole thing is showing examples that would speed up everyone else, the truth is out there. good move by them.
bun is a fast runtime and will save millions of projects time and compute costs in CI/CD and redeployments
on the title, I disagree, but with a twist. manually coding is just not necessary, but the ability to get results, and use available compute resources efficiently and at low cost are still disciplines. I don't just mean "architecture", I mean a more specific part of architecture like knowing that your postgres instance can already be an event based architecture and you don't need the cloud provider's pub/sub arrangement at all.
right now, AI isn't going to do that for you. but regarding the discipline, I don't have pride over that, I think that's a major point for people, a level of gatekeeping and pride. this isn't what we need, this isn't what companies need, everyone always needed results.
people in this career are concerned about the billable rate when people with less familiarity with the discipline can deliver results, and thats where I also see a different outcome: delivering results in software still has some unique attributes compared to almost every role in an organization.
A, it just has to be done. B, it's still one of the only roles where your workers can compete directly against you whenever they feel content enough to do so, or discontent with how you are paying them.
Software engineers have little to no overhead costs of running their own thing, they have no licenses and hence no geographic limitation compared to your accountants and lawyers, and they also have enough money to cover the little overhead costs they do incur, something even your sales team doesn't have before getting caught in a lead trading ponzi scheme. The major markets for software engineers (California) nullifies any non-compete you were relying on. It doesn't matter who is doing the software, whether it was someone that was previously doing HR, or someone that built an identity around coding, it just has to be done.
But this should translate into hiring, right now, the importance and cost reinforces teams to want to interview for something that they think "should" be gatekept. multi week, multi month, hiring processes to prove someone has a cognitive ability. but this isn't necessary, people should be able to come into the effort, the same way someone can pick up a broom. the same way a sailor on an old expedition picked up an oar and splits the bounty during the trip.