John Carmack is a personal hero of mine, so it pains me to say this:
Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
It could be he is doing incredible work in private... but it could also be that he's lost in the weeds, because AI is so counterproductive while feeling the opposite?
Again I don't get what people on HN are doing? Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed. I mean, we should not measure everything in money, but for lack of a better measure for productivity, I cannot see how anyone finds it counterproductive. This was strictly impossible for our small team before recent AI and hiring more people didn't work for the pricing. Our profits jumped, revenue jumped, client count jumped. What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
We do spend all our time either code reviewing or talking with clients but the latter was already the case and the former was just better spaced out over time as this would before take many months.
If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves? Certainly they understand their problems better than you and they can adapt to rising issues faster if their in-house team does it themselves. And certainly what kind of AI you can access, they can too and perhaps even more. So what will remain your value propositions?
I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly. Or work on the backend when constraints are not strictly enforced (for various historical reasons). Schematic understanding is still an issue.
Sometimes additional chunkings and detailed planning/instructions suffice. But other time, humans are still the best vehicles to code.
> nagging question that if it’s so easy, why would the clients not do it by themselves?
It's easy if you're already an expert at software engineering and know how to leverage AI. For people like that, it's a phenomenal upgrade (this is true for me and several co-workers I chat with, all of whom are chasing cool ideas on side projects). But if you're non-technical, or not use to thinking about requirements, or think that using AI is "give me the prompt", it's a pretty big moat to cross.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Plenty of reasons, including:
1. They don't (yet) know how to use AI to accomplish what they need.
2. The ROI is still meaningfully positive and they don't want to have to do it themselves.
3. Having a third-party do the work provides protection for decision-makers. If the project fails, the third-party takes the blame and "nobody gets fired for buying IBM".
4. The vendor does bring valuable insight to the table and pairs it with the use of AI to deliver a result that wouldn't have been possible in-house.
This doesn't mean that everyone will be able to get work and maintain their rates in AI world but some people will.
I recently tried to encourage my smart, technical, but not-programmer friend to build an app using LLMs and he was just like, "I still have no idea where to even start."
People talk a lot about how "real programmers" used to have to clean up or actually deploy everyone's half-baked MS Access app, and that sort of thing will probably still be the case for a while.
The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s. Bad code generated by someone who doesn't know how to program well -- whether that person is supposed to be a professional programmer but is incompetent, or has a different job -- is nothing new, and neither is having competent programmers clean it up. LLMs probably generate more of it, but can also fix a lot of it, or at least patch it up.
A year ago, LLMs were not useful for me as a programmer. Now they are: the models are better, they can use long contexts more effectively, and the harnesses are better at helping the models. Nowadays my job is mostly not programming, but LLMs let me organize and prepare tools in spare time rather than needing days or weeks of attention. I would not trust them on a 200k+ line project -- and Claude Opus 5 has issues even on 50k LOC projects -- but they absolutely can help given good direction and a narrow enough scope.
Then I don't understand at all what point you were trying to make about being miserable in our jobs. Cleaning up after bad code has always been part of the job for decades; so has balancing the creation of new technical debt against resource availability.
> The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s.
I do actually understand that.
I have done this very put the Access database on the web job myself. (FWIW I was well-paid for it and the firm I worked for earned a fortune, but this was in 1997)
I mean they've boasted[1] about their generated code being so good that they add basically zero value and that they're riding out the rentseeking for as long as possible.
Meanwhile they've apparently played with LLM porting of Postgres (or Postgres features?) and "would not put it in production"[2], so we can also guess the kind and scope of features being discussed here.
They're not "adding no value", the SLA is the value. I have a business problem, and I pay you to solve it and support your solution for me, is a completely different proposition than standing up your own solution as a non-technical org and maintaining it.
> They're not "adding no value", the SLA is the value
The code their Astra+Fable setup, automatically generated from requests customers leave in voicemails, is apparently so good they never correct it. If the stories being woven are true, the SLA is literally just a middleman's 100k cut.
At the very least there might be some particulars here that aren't universally applicable.
The second was just for fun; it is fun. This is very far from the code we roll out at customers though. We build LoB apps which are basically crud apps (they are not but most here would call it that).
We can have fun and make money right? Possibly at the same time but not in that case.
> The second was just for fun; it is fun. This is very far from the code we roll out at customers though.
Which is fine, great even (I do the same thing!), but in trying different things outside your day job, it seems like you do understand why people working on different things than you might be "reporting all these negative AI experiences"?
It's a pretty bad sign when you need to resort to this kind of comment stalking to try to find ammunition for a general argument. This user could be a complete con man, and it still wouldn't invalidate the core thesis of LLMs providing business value.
> you need to resort to this kind of comment stalking to try to find ammunition for a general argument
It's not a general argument, they made specific claims, but vague posted (and implying everyone else must be crazy) to the point that the conversation is derailed by a bunch of people trying to figure out what they meant.
> it still wouldn't invalidate the core thesis of LLMs providing business value.
lol, no, "providing business value" is not what was claimed:
>> What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
> I mean it's weird that we all imagine reasons why we're still relevant when we have set fire to the thing that made us indispensable.
Very few things in this world are all-or-nothing, and not every purchasing decision is based on price alone.
Do you always buy the cheapest meal? Car? When you renovate your house, do you always choose the cheapest contractor?
Tons of developers will lose their jobs, and many more will find it hard to maintain the salaries/rates the industry has been accustomed to. This is already happening. The days where an average graduate from a run-of-the-mill CompSci program or even a coding bootcamp could sleepwalk into a $150,000+/year entry-level job are largely gone. The days where you have job security simply because you're a competent developer with 10 years of experience are in the process of going away.
This does not mean that there is no subset of developers who cannot be successful in this market. There are people who are doing just fine because they know how to articulate their value and sell themselves to employers or clients.
> If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Because it's not (yet) that easy, especially if we're talking a complex and genuinely useful app. Agentic coding is fast, but it's not magic.
> I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly.
Exactly. Which is why Joe Average still will have little to no luck vibe coding anything serious or novel. You still (IME) need a lot of active guidance, still need to push away from dead ends and propose alternative algorithms, and it takes hundreds of prompts to go from concept to what I would consider beta. (But, this is just my own experience, and it's possible I'm doing it wrong?)
I don't think that really matters. I have already seen companies generating their own code and just QA testing it, with no software engineers in sight. Or they ask us to "review" their 10k loc PR in 2 hours.
The spirit of the parent comment is true. People feel like it's productive and even if they make something worse, they are going to use it.
Clients are starting to, that’s exactly why I am not sure why AI doom deniers here think this will think it will go well for them. But it will still take awhile and we are enjoying that time. If we see new markets, we will move into them.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
I mean, that's exactly what's starting to happen, we have more and more clients to whom we propose a quote and their answer is "guess i'll just vibe code it" or come to use with an app that they vibe-coded and does the job, and they're content with it. So far it seems to work out just fine for them.
Ya, AI is very good at generating number, be that code for software, images for ads, or banal prose for company blogs. AI not so good at growing corn, cooking eggs, biulding houses, running fiber, treating disease, changing brake pads, loading a truck... or any of the other millions of physical-world jobs on which the economy is biult.
If you company is all about creating things that go on the internet, sure, AI is your thing. But for most companies the internet is a communications tool rather than a product. Those companies are not seeing the claimed productivity gains.
They sure are though; they have many processes to automate as well: big corn farmers/factories also have admin, erp, crm, departments with processes etc. There are companies doing billions in revenue with departments of people just copy/pasting PDFs who do real life things like you state who have immediate gains. But they won't do it alone yet and luckily need us. They still benefit though vs the large consultant businesses or even their own IT deps though.
Literally everyone I know in a large enough company who talks about AI talks about increasingly panicky mandates to use more Copilot coming from above, like you'll lose your job if you don't use it more. I heard exactly this story from my neighbour just three days ago. Literally a call from head office demanding they use Copilot more — to do a task Copilot can't do.
Everyone in smaller companies describes various efforts to get AI to do more that ultimately end up involving lots of corrections or nurse-maiding ChatGPT to get it to do exactly what they need, when what they need is often so formulaic they should already have a process.
Nobody I talk to describes it in terms of massive productivity gains. Everyone describes it as a puzzle they feel variously compelled to solve.
I can add a data point for you: At my job they have made "amount of AI usage" a criteria for performance reviews, advancement and promotions. Mandate from the top: Use as much AI as you can. They even have a leaderboard (accessible to managers) showing who is using the most and least AI. It feels as though nobody even cares how good or bad a job I do, as long as I do it using AI.
They do and there are certainly some mid-level management jobs at risk, but ask any farmer/electrician/millright about the claimed impact of AI and they will laugh. They have yet to see an AI capable of reliably replacing a fuse let alone doing a solid day's work.
Yes, agree with that, but that's usually not the sort of work we talk about here. But sure, robots are close there. All those admin jobs on the other hands...
> Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed.
OK so, it sounds empty and miserable to me, but we can stipulate that this is how it is working out for you.
Given that stipulation: how long do you think this can possibly last, when you are in a race to the bottom with everybody else who is doing this?
Have you made plans about how you will get out of your office lease, downsize, subcontract this button-pushing to even cheaper people overseas, etc.? Are you ready to lay off everyone who works for you, downsize your house to a smaller mortgage? Because you're on a burning platform. If you can do this, so can everyone else.
I mean, I think we all are, possibly, on the same burning platform; I don't think I can fully avoid AI so I am trying to make sense of it.
But I intend to fully avoid being in a race with other phone whisperers if I can.
You're not just in a race to the bottom with everybody else who is doing this. I don't think his anecdote is particularly surprising at all. You can do the same with basically any typical CRUD app, which is already going to be some very large percentage of all business software. But this kind of also leads to the conclusion that so can the people paying you.
I think the years of software development/employment for problem solving, in and of itself, are numbered at this point. When people start to understand how relatively easy this stuff is, they're going to be in-housing everything. Not only for price but also because of increased flexibility/confidentiality/control, and even lower concept-to-live timelines.
What third party stuff continues to exist will see its comp plummet. I imagine now you can already get some really nice quality software contracted out on places like fiverr for nothing simply because the skill involved to produce quality solutions has plummeted.
I think it's a mistake to assume that quality doesn't plummet when cost does, even if the AI is capable of quality work. The quality issue will always resurface.
But yeah — I mean, I am a freelancer who burned out for reasons that are rather more influenced by the SaaS wave. That was hard to compete with. People choose between the solution that meets their needs and changing their processes to meet the ten-times-cheaper solution that doesn't, and that decision is often not at all irrational; by and large you want as many of your problems to be shared problems as possible.
I am trying to return to work so I am looking at what AI can really do for me, but the conclusion I draw is that since I cannot simply burn token money to solve people's problems, and because bugs cost me money, I need a strategy where I remain in full control of actual code, but LLMs help me do things faster. If I can't solve that, I am out.
Perhaps AI will upend the SaaS market before it fucks the freelancer market and the balance may temporarily shift. But it probably won't.
And at that point, as a fiftysomething, even with a bit of financial security, I start thinking about living a rather shorter, happier life, instead of a longer one. Because as much as I might have ideas, I don't think there is much I can switch to where I have appropriately deep skills to survive AI there, and all those alternative jobs will be oversubscribed and less likely to hire me.
I wonder if people in this industry have understood what we are doing to ourselves, to our friends.
A bit of a tangent here, but I'd look into lower cost of living areas if you have the ability to move/remote, even moreso if you'll be drawing social security or have a pension. Money just goes so much further, and with an overall much better quality of life. And there's always stuff like teaching, moreso because it's enjoyable than for the paycheck.
But in these parts of the world, making a few bucks doing whatever in the software world goes so much further. Because of that I think LLMs are bringing in something like a temporary golden age. And these parts of the world will be the last to have the lights go out on software simply because the low cost of living means there's a whole lot more slack to give before things get bad.
I am moving to somewhere cheaper, yes. Though since my passport is no longer strong (British), my choice/range of cheaper is a lot more limited.
Quality of life will not improve, because I will be lonelier (plus I have a great quality of life here in other ways, that many places cannot match) but I am mostly reconciled to that loss. I will have a fair bit more flexibility in use of space, which means I can be a bit more of a portfolio-earner; I do have some fringe skills that could make some money still, and I can have a little workshop or studio.
> But in these parts of the world, making a few bucks doing whatever in the software world goes so much further.
I am (undiagnosed but very obviously) ADHD and I don't tend to find it easy to make a sustainable income off "a few bucks" here and there; the effort expenditure in managing it always ends up subsidising the work. It's part of why I am burned out. I need thicker strands of work and those are fewer and further between.
I have little certainty when things will get bad, but I do think it likely it happens in the next five or six years, and I do know that when things do get bad they favour the young. Which I am not. It is clear to me that I am never getting an ordinary dayjob in the tech industry again.
I don't mean to sound particularly gloomy but I think mine is the generation whose lifespans will dramatically shorten. I think a lot of single middle aged people (men mostly) in the tech industry will choose the time and manner of their departure. Because we are deliberately creating both misery and job insecurity.
I don't think you're being gloomy so much as realistic. It's clear a lot of people either don't realize what's already happened, or are in some sort of denial about it. What you're saying is entirely true and was almost certainly also true during past eras of revolutionary leaps in technology. Fortunately in current times we have far more options than we did in the past, but realizing those options takes a bit of adventurism.
Since you already have that in you, I think you'll be surprised what you'll find - entire communities of interesting English speaking tech-oriented folks, many with more than a few grey hairs, would be just the start. And don't forget the teaching aspect. If you have a degree, smarts, some basic charisma, and can roll with a bit of chaos - you'll find plentiful opportunities to teach any topic imaginable. It's not just English, like many think. It's really quite fun!
I have taught/lectured the odd thing in my past and I can do it; I come from a family of teachers and it is in the blood.
I do not have the psychological constitution to teach kids so I am not going to do that.
But teaching/training adults is an industry that AI will destroy because the baseline income — the stuff nobody else wanted to do but you could earn from — will be eliminated, increasingly by policy directives from above. I have some ideas in that regard but it is difficult to see how I won't end up competing with LLMs when even open weights models are pretty good at coming up with tech tutorials etc.
Broadly I think there is undue optimism about what will be left to move to when the programming jobs dry up.
(Thank you for the discussion, though! I may sound quite negative but actually I am doing better than I have been for years, and it is always useful to provoke one's own thoughts)
Well there's a world of difference between teaching a 7 year old and teaching a 17 year old. I would say in both regards a more engaging style may be necessary than what you're possibly alluding to, so there is that. Depending on your background, teaching in a university is also completely viable. There's also the private lessons possibility. There's many options and I definitely wouldn't just write it off.
I don't think AI will touch education. A good case study there is Khanmigo which was to be Khan Academy's revolutionary AI tutor. There's been a million articles written about the topic. It completely failed, in spite of receiving massive sponsorship and imposition in various educational settings. And I'm kind of surprised that Khan himself didn't understand or predict this. As you probably know, great intrinsically motivated students don't really need teachers. You could give them a book or a sort of LLM tutor, and they'd excel completely independently. But then there are the other 95% of students you have to consider.
And those other 95% tend to fall into camps of either being a bit less gifted in the cognitive domain, or lacking motivation. Depending on exactly where they stand on the balance of two, a good teacher can have a huge impact, whereas 'go learn with the LLM for a few hours' would have them tune out instantly. It's because teaching isn't just about literally teaching, but about forming a rapport and trying to gradually push those 95% into more of the habits and patterns of the 5%, but without them realizing they're being pushed in that direction. An LLM there is almost entirely nonsensical.
Software is easy until it isn’t - the moment you need serious infra you’re in deep trouble and looking for an experienced partner or a saas solution anyway.
The days of b2b saas subscriptions doing one simple thing well for 3 or so users are however numbered.
Try getting something good out of fiverr or upwork. Even now it’s terrible (we get to clean up some the experiments). I agree maybe with the in house after enough years but that will also have a big effect on employees of those companies; a future (5+ years for sure as enterprises don’t move so fast) AI would need few resources to create and optimize and improve. I am not resisting my company won’t exist soon-ish; I am resisting that people see a bright future for devs here on HN. I don’t know where that comes from outside handwaiving ‘loom’ and ‘train’.
I know fiverr will start delivering nice software in 5 years and that’s what I worry about. By that time fiverr is probably just a chatbox though without humans, as what is the point?
The point is that button pushers currently simply don’t seem to be able to do this work, so it’s a little more than pushing some buttons. But no, I don’t think it will last very long, but few years more I guess looking at the competition and lack thereof.
What you describe does not sound all that much more than button pushing, TBH.
And your competition is not non-skilled people using AI to take your jobs. It is _cheaper people_ using AI to take your jobs. All the things that outsourcing teams used to struggle to match are much less of a struggle to match when you are actively depersonalising your own effort by handing it to Claude.
Don't underestimate the power of motivated reasoning. Certain people don't like AI coding for various ideological reasons, and so they will, not coincidentally, consistently fail to find it productive or helpful.
As long as we don't underestimate the power of motivated reasoning for other certain people as well, who like AI coding for various ideological or financial reasons.
I mean sure if long term maintenance and code quality don’t matter then I wholeheartedly agree with you.
It’s spectacular for small projects, limited-scope apps (eg marketing campaigns etc) and for market-testable prototypes.
But if you don’t review and edit the code, things become unmaintainable soup very fast, with subtle logic bugs all over the place. And if you do review and edit the code, when working in large nontrivial codebases, then in my experience AI doesn’t actually go faster even if it feels like that at the start of each task.
Obviously this only holds if you have any sort of code quality standard to begin with (and I agree that with small / short-lived products you don’t need one)
I'm currently working on porting a mid-sized project to a new architecture, new programming language and of course adding new features.
Getting a new feature implemented is quite easy. You spend a few hours brainstorming specs with the agent, then ask it to implement it. This gives you extremely frequent code drops that add a new brick, add a new feature, etc. All of this with 100% code coverage (we also have mutation testing, strongly-typed code, standard and custom linters, etc.)
Then you look at the code. Code that has passed review, generally. You realize that the database schema has been broken silently, and that the agent has rewritten the tests or the golden fixtures to match. You realize that it has made assumptions that contradict the specifications and the product is going to break once it's in the hand of users. You realize that the 100% code coverage is essentially a convenient lie, because the code and tests have been written to make passing easy. You realize that none of the security golden rules have been followed, and that has managed to happen because the agent has somehow deactivated linting.
Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?
On the upside, bugfixing becomes so fast! Just add a new test, wait a few dozen minutes, and a new Merge Request appears. With equally convincing/misleading explanations, and something else broken.
After ~4 months, we had a bare bones deliverable, which we're now steadily expanding. If we had had to write the product manually, I suspect that it would have taken us at least one year, possibly two. So, that's the productivity increase. The productivity decrease is that what we have is not a product but a glorified demo, something that will work very nicely on the happy path, but on any other path, all bets are off.
Thankyou for putting the last three months of my life into words <3
> and the explanations of the agent are convincing enough that surely, it knows better than you.
I feel this in my bones. I also get to watch the misalignment feedback loop close itself when the next agent sees that security rules aren't followed because of a hallucinated 20 line justification in a code comment, and then it decides that the project _is_ a demo and then confidently writes even more security holes into the codebase.
Then when you catch the issue, the agent pushes back against the fix because it would need a schema change and production DB migration.
> Then you look at the code. Code that has passed review, generally. You realize that the database schema has been broken silently, and that the agent has rewritten the tests or the golden fixtures to match.
I find that the code review leg of this is critical to invest a lot of energy into hardening.
First is don't trust the code review from your local harness, even if it uses sub-agents; externalize it into another system.
Second is to get your most critical human code reviewers to encode their heuristics in markdown files and feed those to the code review agents.
Third, if possible, is to bring the code review "into the loop" so that it's not only running in the PR, but also running in the coding loop so the coding agent has immediate, external feedback. Final PR code review is a backstop.
This pattern [0] works well because it solves for some team level problems where folks are using different harnesses or different models (consistency issues) and it means that code reviews don't just sit at the end of the loop; it actively alters the code production cycle.
In my experience, they are fairly good at catching stuff in human-written code, but they tend to gloss over agent-written code, just as human beings being lulled to complacency by superficially-looking competent code.
> "Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?"
I have come to realize that AI is so "successful" because the system in which it is being deployed was designed to push product as fast and cheaply as possible from the start.
Humans are usually overworked and stretched to their breaking point, which I originally saw as the source of our broken software woes, which, like our streets in the US, just get a new layer of asphalt to cover up the crumbling bits each year instead of rebuilding the infrastructure with reliability and longevity in mind.
My former employer was using both Claude and Codex for firmware that was driving an over-burdened power circuit that itself was partially designed with ChatGPT. All of the individuals involved approach LLMs with god-fearing reverance because they do not understand _how_ the LLM works, just that it _does_ in a "good enough" way and they can offload their thinking, which is something we all wish we could do because thinking is hard, time-consuming and costly. I get it.
But like you mentioned, tests were being passed, not because the code was sound, but because the tests were altered to match the results. This is not necessarily the fault of the agent, either; it's just interpretting the prompt(s) - written by a flawed human, btw - with stochastic mechinations that seem to make a great deal of sense on the surface, but remain unable to be followed or repeated by the brains of (most of) its users.
As a rresult, I had to deal with product that work great in the field...at least at first, before it start literally catching fire, ruining its own powertrain because everything the agents touched became too complex with too many subtle cracks in the veneer to review properly. The system (read; capitalism) demanded viable product quickly to please investors, and the burnt-out humans who decided to try this AI thing ended up trusting it nearly completely, so any ideas of repeatable and complete testing, diagnostics and root cause failure analysis morphed into a sloppy "it works on the bench" checklist before being sold to a customer who had come to trust that their deceptively simple product would just work as advertised.
I'm going to die on the hill that AI as a replacement for our brains is precisely how we will make ourselves go extict, but I am old enough to already be regarded as a crufty dinosaur who is stuck in his ways, and I'm made peace with all of that. What I can't get my head around is watching people use this awesome tool (and it is, admittedly, awesome) to literally just speed up all the mistakes they were already making. Perhaps it is because I am aging, but slowing down and having a think seems more valuable to me now than it ever has, especially when creating something new. AI is powerful and, like any good tool, could be useful in the right hands, but more often than not I see it being used as an accelerant for all the worst parts of product development to appease a market that has suddenly been told they can now pick all three points on the Iron Triangle instead of just two. This makes about as much sense to me as taking a laxitive when you already are suffering diarrhea.
AI amplifies existing process. For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seems’ to be productive (producing slop).
Yeah, that gives me the scary feeling that especially here people are overvalueing themselves by a lot. They find AI counterproductive because they simply never were good at what they do before AI. This is always always my read of people who value talking, meetings and office time as important: I have never met people who have that and who are not sales or just plain suck at their job; AI amplifies that. Also with salespeople who now send me presentations that just have a bucket loads of hallucinations in them: turns out they never read them but had interns write most of them: now they still cannot read and AI generated stuff looks plausible. I only have anecdotal experiences but this sure seems to resonate for the AI negativity around here. I could be wrong but it's so far removed from our experiences.
You don’t value “talk”? I understand. I have a lot of those around me and they are super productive, all day, alone, in their little cubicles. Oblivious to everything around them.
I don’t know what to say to those types anymore. Live and let live I guess.. or in this case, not live I suppose.
It usually is more like; I send an email or so which contains enough details to understand whatever we are doing. A person in that list sends it to 20 people. The next email is a zoom invite with 30 people of 1.5 hours to ‘go over the email together’. If these people have no influence, good or bad over the outcome, why would I waste this time while it usually just says they were too lazy or incompetent to read the email?
Useful talk and meetings all day is fine, but these are just to write busy/billable hours for all these useless folk with no value for the project. And socially I like listening and talking, just not for this.
> For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seem’ to be productive
Convenient way of saying "you're holding it wrong".
I get flamed here whenever I say it's a skill issue, but it absolutely is. Not everyone has what it takes to be a successful CTO but that's the role you play if have 20 agents working on something you designed. I see you got downvoted too.
It would be a skill issue if someone would show they’re able to use it to produce good software while showcasing that it’s due to their mastery. Till this day, I don’t think there’s any such demonstration. Any defects of the technology is always blamed on skill issue.
There's a ton of people out there in various unknown companies grinding away and managing a reasonable number of well-prompted, parallel agents with decent CI and deployment strategy making judicious use of human review.
But that's boring and you can't build a YouTube audience around it.
What had he produced in the years prior to AI getting good enough for coding? All I know is he was on Zuckerberg's sinking metaverse boat for years, and then nothing else.
Maybe it's him, maybe it's his employer. I don't know. I am skeptical of AI's impact on work myself but I just don't think AI is the only thing to blame here.
Oculus was pretty fun and a really nice piece of hardware. What was painful was all the meta things on top of it, which I doubt was something he personally added.
> Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
He's been spinning his wheels for a while. Carmack is a great example of how important working on the right stuff is. He's undoubtedly a brilliant programmer. Through him we get to see that a brilliant programmer working on non-programming tasks, can produce nothing.
Carmack hasn't produced anything genuinely noteworthy after leaving id software, if we are being frank.
His work at Armadillo aerospace was more akin to hobby, not really leading anywhere, a VR stint at facebook, again, is difficult to gauge at how large his personal contribution was, and this new AI thing is likely end with him leaving the company, again.
Carmack is an amazing engineer, a genius even, but either the age of the individual contributor creating the entire thing from the ground up is over, and he's bored of it, trying to find a niche where this still works, or he is exploring the areas in which to apply his curiosity.
What I'm saying is that his current productivity or lack of thereof isn't a marker of how AI is productive (or not) in general
Actually, I'd expect someone like Carmack to be the least productive with AI. Carmack focused his career on high-performance 3d graphics tricks. Those are free now. What isn't free is knowing how to use them. In other words, the game engine is free, the game maps/zones/levels are costly. The "John Romero" part of the equation. Let's see what the idea people are making, not the code gurus.
That AI still hasn't made my effort and thinking and directing and checking and ideas completely redundant and thus out of job?
It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
> It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
I’d go even further. Shades of grey implies two extremes on a linear scale, but the world has colour, meaning wildly different interpretations that go in novel directions.
However, ironically, your comment reads to me as extremely black and white—full of certainty, rigidity, possibly some bad faith interpretation and straw manning—while the one you’re criticising has (some) nuance and doubt and seems open to the idea of being wrong.
What complain? OP asked a question. Carmack created Doom, Quake in 2, 3 years. What has he created in 4 years of AI? Should be exceptional if one of the most productive programmers ever says it makes him more productive.
That reminds me of something on my last job. Before AI, we had not so good communication, but if we had a question, the person on the other end will try to give you a passable answer. After AI, everyone seems to be a proxy for the LLM tools they're using and any misleading statement you point out is answered by "Why don't you use $llm_tool to check it out?".
You're comparing the challenge of building game engines in the 90's with the more open-ended AGI research. It's different enough that I don't think it's valid to conclude he's less productive now based on impact over time.
Its very different living in the late 80s to early 90s coming up with cool ideas that push affordable hardware to their limits just like John Carmack did with games like Keen, Wolf3d, Doom and Quake.
It was at an era where someone good at their craft can get the recognition they deserve. However, while some things he managed to figure out himself.. other things were ideas from others. He simply tried it and reviewed the results!
Looking in the games industry today - an 'individual' is not going to get the same recognition like John Carmack back in the day (or Ken Silverman, etc)
This industry is LARGE. Any god-like programmer trying things within a large corporation is not likely to get noticed today as they hide away in the background pushing an in-house games engine forward. I am sure there are a fair number of John Carmacks out there. Invisible... nameless legends pushing things, etc.
As for indie companies - why risk trying to be a 2026 version of John Carmack when Godot, Unreal, etc, exists. Its a different world today!
Same thing for AI. I bet there have been some legendary programmers working on AI in the last 10 years. Again, nameless individuals behind the brand.
If any names are mentioned... its likely CEO's or other higher ups... not the talent underneath. I guess thats good business strategy and works [for the business].
Focusing on John Carmack - I am not taking anything away from him. He is a legend. I am sure he contributed towards VR before and after Meta purchase. With AI.. I guess we will see.
At the end of the day the guy could walk away and focus on hobbies. Still has a lot of batteries left. More power to him.
I'm a practical optimist. I see us as being in the age of engineering for AI -- like the early days of the steam engine. We're going to get a ton of things wrong and impractically implemented. But we don't anticipate the train conductor to build the steam engine on their train -- we just expect it to work as targeted.
(Note I'm not being pollyannish here -- a lot of codegen downright sucks).
Sure, among all these other people doing 'incredible work' for 30+ years publicly, well into their 50s, John Carmack sure is a disappointment by comparison.
I sense sarcasm. But I think you misinterpreted the parent’s point. I read it as: yes, Carmack has made huge contributions but, has not publicly released anything noteworthy since the advent of AI coding. Of course that doesn’t mean he won’t, just that so far nothing he released has backed up his statement.
Can you imagine a football fan going up to Ronaldo and saying hey, I saw an interview you did last week - I think you may be lost in the weeds there with your training regimen and outlook. I want to let you know - I remain a skeptic.
I mean, when you start scoring goals like you did 5 years ago Ronaldo, but until then, I remain a skeptic about that training regimen.
As for misinterpreting - maybe you're misinterpreting. Or maybe it's unproductive and dare I say presumptuous to reply to people you know nothing about with 'you're probably wrong and I'm probably right'. Do you do that in real life? Working out great, I can only assume given you've adopted a similar approach here, or?
Do you believe a 50 year old software engineer is mentally no longer able to work?
Should they be forced to sit back and tell stories of the good old days because their knees are blown out?
Do you believe that one of the greatest living programmers is so washed up at 50 that _even with the greatest LLM tools_ cannot ship something publicly in four years to back up his claims?
I would rather listen to someone with current merits than someone who has not produced anything notable in years. Especially if the topic is current trends in software development.
I mean his post boils down to "Get on the bandwagon because you might otherwise miss out. All the cool kids do AI now."
There are valid concerns there (and you should probably be playing around with LLMs), but he voiced none of them. He just led with a metaphor about obsolescence and then continued spreading FOMO with an authoritative voice.
Perhaps he is actually lamenting being the out of touch kung fu master, but his pride won't allow him to articulate the ways in which he identifies with that?
Edit: Had to re-read a bunch of stuff about Musashi, and to Carmack's credit, seems to have been a relatively pragmatic guy when it comes to the choice of weapons in a battle, talking both about the benefits and drawbacks of firearms (although they were slightly different ones than we have today)
A vanishingly small percentage of the software in the world has failure modes that kill people. To say the analogy you're making is "only partly applicable" would be very generous..
No, but a shocking amount of unappreciated software can cost a TON of money if it fails, even briefly, which is another disaster scenario.
More software than you'd think can get people killed, though.
And more software than you'd think is running inside a barely-understood SCADA package that runs user scripts, which can now be authored by AI the user doesn't understand, and that can result in either or both of the above outcomes. This is true in just about every city in the world, several times over.
Software engineers have to understand that they aren't the only flavor of engineer, and even if "everyone is a [software] engineer" was the intended statement, it demonstrates excessive hubris. Many real engineers do work on systems with failure modes that kill people.
However, Ikea furniture does not tend to collapse a critical moment 90 days after it's been put together because it was unforeseen that the cup you sat on the table would be green, which it wasn't designed to account for.
This is fascinating, but also makes me wonder about smaller scale printing from back in that era.
Does anyone know where I might find out more about small-scale printing, what we would call desktop publishing now, but prior to the advent of personal computers and photocopy machines?
It's easy to find some information, but hard to find detailed information like this article presents.
They make 200 billion dollars a year, 60 billion of which is profit, so they could afford to hire a million more moderators at first world wages (50k/yr) and still be making 10 billion dollars a year in profit, and that's assuming nothing else changed, if they stopped spending money on VR, AI, and other horseshit, they'd have even more money for moderators.
They can also choose to show fewer ads, i.e., only show manually human reviewed ads, and if there are too many to review, charge more per ad until there aren't too many.
Pre AI and Post AI code review hours are both 0.75 in this made up example. I find that implausible.
Even with the same amount of code, AI code is less trustworthy* and requires more attention... but we know it won't be the same amount, it will be more. This means it will take longer to review, or there will be unforeseen consequences of not spending that extra time.
*meaning no human eyes have looked at it and said "this doesn't make sense", or "this is cheating", or "this doesn't meet requirements", and won't be caught until code review if at all.
To me the biggest gotcha with AI code is that the bugs are not “normal”.
When reviewing human code I focus on specific parts because I know that there are parts where a person will just not make a bug (unless very junior).
AI on the other hand, will not do an off-by-one mistake, but it will happily just delete perfectly working code for no obvious reason. Or monkey patch a dependency because it missed a config flag. Or generally fail in a very novel and creative way.
The effort it takes to review AI code is much greater. And this is in a code base I am deeply familiar with.
Imo the future lies in a solid core programs with powerful plugin frameworks that expect all plugins to be code that was never read.
I think this is a good practice anyway. Putting as much code as possible into silos with guarded permissions.
Historically plugins have been kind of crappy because they were constantly breaking with updates. However if they only live as a spec, and are regenerated when needed they can easily survive API changes.
Bonus feature is that if all “installed” plugins are generated together, the llm can also find ways to avoid them being buggy due to weird interactions.
All this while keeping the main program from crashing.
Security wise the spec can also be inspected using a trusted LLM. It is trivial to hide exfiltration or malicious code in plugin/extension code (e.g.: honey). But it is much harder to hide it in a spec.
Yup. I can expect an llm to write proper code to update an hashmap or update a db, but ffs the amount of race conditions, use after free and general concurrency issues I found on colleagues PRs developed fully with these things is disgusting.
The hard part is that LLM code looks like there is some sort of flow. It is like a nice statistical smooth flow. It looks very convincing at a glance. No one would write code like that and not know what they are doing comments self assured and all.
My experience as well, it is too fond of abstractions and will constantly spin up functions like: isUserAdmin(){return user.isAdmin}
which look nice on a surface level but obfuscates real understanding of the code and the actual data structures being used. Your end result
is pretty and reads nice, but is bloated and difficult to reason with code.
LLMs are incredibly good at replicating common, coarse statistical features - which is what backs "looks very convincing at a glance".
If it's a general signal that's easy for you to recognize at a glance, it's a signal that's natural and easy for an LLM to replicate.
They're much worse at making the underlying structure work. Not incapable at all, especially not the modern LLMs. Frontier models kick ass. But it's true that an LLM denies you a lot of the classic "tell at a glance" by its very nature.
> Even with the same amount of code, AI code is less trustworthy* and requires more attention... but we know it won't be the same amount, it will be more.
If you think that, you aren't reviewing human code closely enough IMO. Human code and AI code should be scrutinized equally closely. Or rather, if you're relying on where you think the code came from rather than actually, y'know, reviewing the code itself, then you aren't doing a good job.
But now it seems the only likely outcomes of such technology are:
> rich people hoarding wealth
> high (and unpleasant) unemployment
> ICE agents being remotely operated unaccountable robots whose operators are made anonymous by law.
Where the future goes I don't know, but I'm no longer optimistic about it for the average person.
With a byte you can keep track of 256 things, with two, 64k things, or with a byte you can issue one of 256 commands, etc.
Of course, now we'll use a dictionary of objects with various properties to keep track of a bunch of 'true'/'false' strings...
We collectively act like RAM is free and so are cycles
Tangent: I abandoned C and then later Windows as a consequence of Charles Petzold's* book on win32 programming, the fact that so much bullshit boilerplate was required to get a GUI up on a OS literally named after its GUI windows...
*Fwiw I like his books, I just didn't like the way Windows wants me to do things then
Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
It could be he is doing incredible work in private... but it could also be that he's lost in the weeds, because AI is so counterproductive while feeling the opposite?
I remain a skeptic.
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