A lot of companies have been under AI psychosis for years and will be forever.
I don't think it's super clear what we'll find out.
We've all built the moat of our careers out of our expertise.
It is also very possible that expertise will be rendered significantly less valuable as the models improve.
Nobody ever cared what the code looked like. They only ever cared if it solved their problem and it was bug free. Maybe everything falls apart, or maybe AI agents ship code that's good enough.
Given the state of the industry were clearly going to find out one way or the other, hah!
I think some companies will find out that their senior engineers were providing more value and software stability than they gave them credit for!
Corporate feedback loops are very slow though, partly because management don't like to admit mistakes, and partly because of false success reporting up the chain. I'd not be surprised if it takes 5 years or more before there is any recognition of harm being done by AI, and quiet reversion to practices that worked better.
Calling this "psychosis" is maybe a neologism but it's apt in perspective.
All that's actually new with "AI psychosis" is an acceleration of that phenomenon. The agents will summarize status faster than any middle manager. Claude will happily draw you any "up-and-to-the-right" graph you please, with the most common contemporary examples being "tokens burned" and "lines of code written". And vibe coding doesn't even require paying the cost of a mass layoff to get the "familiarity debt".
There have always been both good and bad engineering leaders. No tool will magically make a bad leader into a good leader overnight. There is nothing new under the sun.
“It feels like entire companies are deluded into thinking they don’t need me, but they still need me. Help!”
The broad sentiment across statements of this “AI psychosis” type is clear, but I think the baseline reality is simpler. How can you be so certain it’s psychosis if you don’t know what will unfold? Might reaching for the premature certainty of making others wrong, satisfying that it might be to the ego, be simply a way to compensate the challenges of a changing work environment, and a substitute for actually considering the practical ways you could adapt to that? Might it not be more helpful and profitable to consider “how can I build windmills, ride this wave, and adapt to the changing market under this revolution” than soothing myself with the delusion that all these companies think they don’t need me now, but they’ll be sorry.
The developer role is changing, but it doesn’t have to be an existential crisis. Even though it may feel that way — but probably it’s gonna feel more that way the more you remain stuck in old patterns and over-certainty about how things are doesn’t help, (tho it may feel good). This is the time to be observant and curious and get ready to update your perspective.
You may hide from this broad take (that AI psychosis statements are cope) by retreating into specific nuance: “I didn’t mean it that way, you’re wrong. This is still valid.” But the vocabulary betrays motive. Resorting to clinical derogatory language like “AI psychosis” invokes a “superior expert judgment” frame immediately, and in zeitgeist context this is a big tell. It signifies a need to be right, anda deeply defensive pose rather than a clear assay of what’s real in a rapidly changing world. The anxiety driving the language speaks far louder than any technical pedantry used to justify it, and is the most important and IMO profitable thing to address.
You should not release a product into the market unless you have a good enough product that can keep you and your client compliant, safe and secure - including not leaking their customer info all over the place.
Prompt injection risk, etc. are massive for agentic AI without deterministic guardrails that actually work in practice.
Stop testing in production if you're shipping in a regulated industry. Ridic!
If you're not technical, you can get someone who is after signs of p-m fit, demos, but BEFORE deployment. This is common sense and best practices but startup bros dgaf because they're just good at sales and marketing & short term greedy.
Comical.
I am very close to using it as a pair programmer, but with me actually coding. I am just so tired of fixing its mistakes.
At the end of the day, we can only read so much and take on so much work before we bottleneck ourselves. Cognitive overload leads to burnout. Rumplestiltskin vibes with this AI stuff…
The groundwork for that was laid long ago with the idea of constant updates. It's been fine for years to ship bugs and rely on a rapid release cycle and constant pressure on users to upgrade everything all the time. To roll that back requires a lot more than toning down AI psychosis; it requires going back to a go-slow mindset where you actually don't release things until they're ready. It still needs to be done, but it's harder than just laying off the AI kool-aid.
What's more, the only people they talk to about it are others at the same company. There is no external touchstone. There are power dynamics from hierarchy. No new ideas other than what is generated within the company. In other circumstances, this is a textbook environment for radicalization.
I would encourage all leadership to take a deep breath. You have time to think slow.
In all seriousness...well, yeah. AI is a monkey's paw, and that's how monkey paws work. So many movies and books warned us!
Changing this focus is not easy but one thing that will usually do the trick is economic issues.
In other words; in order to get any serious consideration, something has to be broken.
AI is perfectly capable of doing this given enough time.
There’s this delusion that if we somehow write enough tests that we’ll expunge every defect from software. It’s like everyone forgets that the halting problem exists.
Let them.
AI coding swept over the software industry faster than most previous trends. OOP and its predecessor "structured programming" took a lot longer. Agile and XP got traction fairly quickly but still took longer than AI -- and met with much of the same kind of resistance and dire predictions of slop and incompetence.
AI tools have led to two parallel delusions: The one Mitchell Hashimoto describes, and the notion that we (programmers) knew how to produce solid, reliable, useful, maintainable code before AI slop came along. As always with tools that give newbs, juniors, managers some leverage (real or imagined) we -- programmers -- get upset and react to the threat with dire warnings. We talk about "technical debt" and "maintainability" and "scalability."
In fact the large majority of non-trivial software projects fail to even meet requirements, much less deliver maintainable code with no tech debt. Most programmers don't know how to write good code for any measure of "good." Our entire industry looks more like a decades-long study of the Dunning-Kruger effect than a rigorous engineering discipline. If we knew how to write reliable code with no tech debt we could teach that to LLMs, but instead we reliably get back the same kind of mediocre code the LLMs trained on (ours), only the LLMs piece it together faster than we can.
With 50 years in the business behind me, and several years of mocking and dismissing AI coding whenever someone brought it up, I got dragged into it by my employer. And then I saw that with guidance and a critical eye, reasonably good specs, guardrails, it performed just as well and sometimes more throroughly than me and almost all of the people I have worked with during my career. It writes better code and notices mistakes, regressions, edge cases better than I can (at least in any reasonable amount of time).
AI coding tools only have to perform better -- for whatever that means to an organization -- than the median programmers. If we set the bar at "perfect" they of course fail, but so do we. We always have. Right now almost all of the buggy, insecure, ugly, confusing software I use came from teams of human programmers who didn't use AI. That will quickly change and I can blame the bugs and crashes and data losses and downtime on AI, we all can, but let's not pretend we're really losing ground with these tools or that we could all, as an industry, do better than the LLMs, because all experience shows that we can't.
the top reply is from someone doing exactly that, arguing "but the agents are so fast!"
Maybe they're assuming that doubling the code-base/features is more beneficial versus the damage from doubling the number of bugs... Well, at least for this quarter's news to investors...
The answer I got is "It's game theory. Someone will do it, and you'll be forced to do it, too. It can't be that bad".
I mean, yes, logic is useful, but ignorance of risks? Assuming that moving blazingly fast and pulverizing things will result in good eventually?
This AI thing is not progressing well. I don't like this.
You'll be forced to do it, or lose. The unstated assumptions are that, first, it will work, and second, that you can't afford to lose. But let's just assume those for the sake of argument.
> It can't be that bad
That does not follow at all. It can in fact be that bad. That was what made the game theory of MAD different from the game theory of most other things.
Oof. Potential "bad" outcomes of "game theory" should be calibrated to include all the bloody wars and genocides throughout recorded history.
Why did the Foi-ites kill every man, woman and child of the conquered Bar-ite city? Because if they didn't, then they'd be at a disadvantage if the Bar-ites didn't reciprocate in the cities they conquered...
i don't think it's 'our side' that has the psychosis.
Thanks. :)
The problem was not him, but the fact that the number of people who thinks like him. They may word it in a more benign form, but the idea is the same.
So obsessed with being the first mover and winning the battle, never thinking whether they should, or what would happen with that scenario.
Missing the whole forest and beyond for a single branch of a single tree.
The whole "you'll be forced to do it" comes from the alternative being that you lose. You no longer get to be a player in the "game". In the same way that coopers and cobblers are no longer a significant thing, but we still have barrels and we still have shoes. Software engineers who refuse to employ any LLMs won't be market competitive. If you adopt it, you at least get to remain playing the game until the game changes/corrects. That's the part that's "not so bad".
Choosing your own survival isn't ethically bankrupt.
Let's say I'm polar opposite of them, and we're on the same page with you.
seems like it's working ideally to me!
And also, he might not be right. But the good news is, we’ll all get to find out together!
The energy feels misdirected and maybe also a communication issue, I think spreading awareness needs to come not from attacking and also not from attempts to change people’s perception. It’s also quite challenging to distill a concept when it’s new, we learn both from our experiences and experiences of others; but, so far, these alleged systems that will eventually collapse, haven’t done so yet and it makes it sound like you’re preaching and predicting, condemning even, rather than raising awareness and education.
Not trying to sound hopelessly optimistic either, just that the other extreme isn’t also helpful, and that a spectrum is not what we want it to be but what the collective shapes it, so saying psychosis is rejecting the harsh reality that they’re far removed from your worldview and not working towards an understanding.
EDIT: Maybe I'm old and I don't get twitter, I also don't know much about the challenges he faced communicating his concerns, I sort of had a meta comment with the intent of "try listening more first, some people are difficult to reason with but respond better if you just let them speak and look for a teachable moment during the conversation". Anyways, I'm in agreement that there's too much unsupervised AI in the wild, I'm not saying he's wrong more like saying that doubling down on "stop doing that" will likely be ignored by those that are already ignorant to it, hence what I wrote above.
He is clear in pointing out the hard earned lessons we have learned before and how the current actions are essentially undermining it. This is dumb (i agree) and he expects better from people whom he respects.
it's clear, personal, logical. I don't understand what your criticism is.
Sorry, I don't buy your argument
*Il outline how briefly: mutate the model 500 times, give 1/500 of your user base a mutated version of the model, and save the top 5 of these model, ranked by how often the users did something, over the course of a week. Repeat for a year, passing the top 1% of these models onto the next round. This is the simplest way to do this and I can think of better ways to do this. I don't even work on this sorta thing; its 100% obvious to the AI labs how to do this better
But equally, like, do people need Terraform if they can just tell codex “put it live”, and does that hurt to see?
It all just feels like horse drawn carriage operators trying to convince automobile drivers to stop driving.
I'm not sure that's true. We've actually seen several open source projects that were vibe coded literally fold up and disappear because they ran into issues that the AI couldn't solve and no one understood them well enough to solve.
There's a reason openai/anthropic and friends are hiring shitloads of software engineers. You still need people that can understand and fix things when the AI goes off hte rails, which happens way more often than any of those companies would like to admit. Sure, "fixing things" often involves having the AI correct itself, but you still have to understand the system enough to know how/when to do that.
Maybe the problem is you, but you won't figure that out if you think the other person has psychosis.
For example, maybe you need to do a better job explaining, changing your language, simplifying things, being more concrete with consequences.
Or maybe you aren't understanding that the other person has different objectives/ loss function that makes them make seemingly weird conclusions.
In any case, this is what blue-green deployments and gradual rollouts are for. With basic software engineering processes, you can make your end user experience pretty much bullet proof. Just pay EXTRA attention when touching DNS, network config (for core systems) and database migrations.
Distributed systems are a bit more tricky but k8s and the likes have pretty solid release mechanisms built-in. You are still doomed if your CDN provider goes down. You just have to draw a line somewhere and face the reality head on (for X cost per year this is the level of redundancy we get, but it won’t save us from Y).
The one thing I hadn’t mentioned - one I AM worried about - is security! I’ve been worried about it from before Mythos (basic prompt injection) and with more powerful models now team offence is stronger than ever.
It is definitely factual that there is a complete paradigm shift in the prioritization of quality in software. It's beyond just AI side effects, and now its own stand alone thing.
There have always been many industries, companies, and products who are low on quality scale but so cheap that it makes good business sense, both for the producer and the consumer.
Definitely many companies are explicitly chosing this business strategy. Definitely also many companies that don't actually realize they are implicitly doing this.
Wether the market will accept the new software quality paradigm or not remains an open question.
Thankfully most of those things are a very small percent of my overall work.
If its a big percent of your work -> you are in trouble friend.
Does using AI increase or lower that failure rate?
Does seeing a project that uses AI fail mean it wasn't going to fail if it didn't use AI?
To try to answer it with my gut: I imagine that we could see more projects failing, but the percentage that fail would be the same. Most projects that use AI will fail because most projects generally will fail, but the time and cost to get a successful project will lower.
The only reason it worked has been expansive money policy and a larger share of the cost of goods being dumped into marketing value while manufacturing costs dropped abroad. so no one bothered to check.
Hmm, I agree with the point OP is making, but I'm not so sure this is the best supporting argument. The bottleneck is finding the bugs and if he'd criticized people saying AI will be the panacea to that I'd be with him, but people saying agents are fast and good at fixing human found bugs is nothing I'd object to.
Agents are fixing bugs so quickly and at a scale humans can't do already.
The metric is how many defects are introduced per defect fixed. Being fast is bad if this ratio is above one.
The fact that we can fix things faster now doesn't mean that we should throw away caution and prevention. The specific point of his tweet is that we're seeing a lot of people starting to skip proper release engineering.
Agents are quick to fix bugs, yes, but it doesn't mean that users will tolerate software that gets completely broken after each new feature is introduced and takes a certain number of days to heal each time.
This is an illusion, I assure you. On a side project of mine with behavior that's very hard to translate into an algorithm (never mind code), after a few failed attempts between the both of us, I figured it out. I gave the AI (Opus) an extremely specific algorithm with detailed tests. All completely and utterly ignored (including the tests), like I never even said it. It proudly declared the work done without ever having written the tests that would have proved that wrong - it basically wrote code that didn't change behavior at all, it just gave the illusion of looking busy.
That's just a single extreme example that comes to mind, but I've had it ignore me at least 4-5 times a day this week.
If you think agents are fixing things reliably then you simply haven't noticed that they are "looking busy."
Please don't sneer, including at the rest of the community.
Eschew flamebait.
So the point is not that agents cannot find bugs (they certainly can), it's whether you can shirk reviewing for bugs if MTTR is fast enough. There are circumstances where YOLO is appropriate, but they aren't the production environment of a mature application.
But this is just holding the Slop Companies to the standard they declared themselves! Just recently, the CEO of OpenAI babbled some nonsense on twitter about how he hands over tasks to Codex who according to him, finishes them flawlessly while he is playing with his kid outside.
> but soon we will be.
Ah yes, in the 3-6 months, right? This time next year Rodney, we'll be millionaires!
Eventually the companies that can't cope with undisciplined engineering will succumb to unacceptable reliability and be outcompeted, just like in the "move fast and break things" era.
Have you ever been in an HN thread where you're an SME on the thread topic and just been horrified by the confidently incorrect nonsense 90% of the thread is throwing around? Welcome to the training set motherfuckers.
LLMs do the same thing for what should be obvious reasons. If you search things that have some depth and you know the answer you'll be flooded by how often the models will just vomit confident half truths and misrepresented facts. They're better than they used to be, not just lying whole cloth most of the time, but truth is an asymptotic thing, not an exponential one.
I think the use of the word here is meant to invoke the vision of someone under heavy delusions or hallucinations, such as (what Hashimoto percieves as) the delusion that shipping more bugs is fine if AI can resolve them faster. To what extent this counts as delusion (and thereby psychosis) would depend on how deeply you believe that this and related opinions are wrong.
i don't have enough fingers (and toes) to count how many times i've demonstrated that "100% coverage" is almost universally bullshit.
Actually no, cancel that. I realise now that I trust AIs more than the average developer, period. At this point they do produce better code than most people I've dealt with.
Never mind code, what happens when the CEOs, or the investors, listen to the sycophantic voices of their LLMs?
I think it looks like every product becomes the next Juicero of its field.
Everyone has become like petulant children. Senior leaders want access to every shiny tool (CoWork/Codex/etc) that has some buzz around it. No one seems to care about the cost or whether we are actually realising benefits.
It's sheer madness, and you can't push back. I think AI can significantly help people be more productive, and I can see a future where they safely take on more autonomy. But we are far from that world.
And I found it really funny, because for what? Use it for what? It’s a tool. Imagine a guy coming down to a construction site where everything is progressing fine and saying “We need to use more screwdrivers”.
Can someone please remind and refresh my memory what this whole debate was with what arguments?
Worth also noting is that while there is plenty to criticize about AI use — especially any cultish behavior surrounding it — plenty of naïveté about the quality of its results, there is a also a strain of categorical opposition to it among some tech people that is equally off and that has all the hallmarks of the chickens coming home to roost.
For years, many in tech gladly “automated away” all sorts of jobs. Large salaries were showered on them for doing so, or at least promising to do so (there was and is plenty of bullshit here, too). Now, AI appears to threaten to derail the tech gravy train, especially for SWE work that’s run-of-the-mill (which is most of it). Now automation is bad. It’s a delicious juxtaposition.
Many people on this forum are suffering under this same psychosis.
and we all live in a green utopia of flying cars and peace upon the world.
I like to think,
(it has to be!)
of a cybernetic ecology
where we are free of our labors
and joined back to nature,
returned to our mammal
brothers and sisters,
and all watched over
by machines of loving grace.
...and it also needs more so-called AI companies present in the wreckage in this crash.
AI psychosis is undeniably real.
At the end of the day robots can do the vast vast majority of jobs better and faster. If not now, very soon.
I only worry our economic systems won’t keep up
But I only see mass layoffs and those who are working - are working longer and harder then before.
Religion is the sigh of the oppressed creature, the heart of a heartless world, and the soul of soulless conditions.
It is the opium of the people.”
Some are on copium, some on hopium. The gods change names; the need for relief remains.
The direct analogy to automobiles would be for each automobile to be a oneoff design filled with bad and bizarre decisions, excessively redundant parts, insane routing of wires, lines, ducts, etc., generally poor serviceability, and so on. IMO the big question going forward is whether the consistent availability of LLMs can render these kinds of post-delivery issues moot (they will reliably [catch and] fix problems in the software they wrote before any real damage is caused), or whether human reliance on LLMs and abdication of understanding will just make software worse because LLMs' ability to fix their own mistakes, and the consequences thereof, generally breaks down in the same contexts/complexities where they made those mistakes in the first place.
My own observations are that moderately complex software written in the mode of "vibe coding" or "agentic engineering" tends to regress to barely-functional dogshit as features are piled on, and that once this state is reached, the teams behind it are unable to, or perhaps simply uninterested in, unfuck[ing] it. I have stopped using software that has gone down this path, not because I have some philosophical objection to it, but because it has become _literally unusable_. But you will certainly not catch me claiming to know what the future holds.
Sure there are industry changing things going on. What if you're working on an app thats a decade old and has had different teams of people, styles, frameworks (thanks to the JS-framework-a-week Resume Driven Development)? Some markdown docs and a loop of agents isn't going to help when humans have trouble understanding what the app does.
I cannot deny the impact of AI for my daily tasks at this point.
But I just don't enjoy the field anymore. With increased productivity, also coming from my stellar coworkers, it feels like we're rat racing who outputs more.
The quality is good, and having very strong rails at language and implementation level, strong hygiene, etc helps tremendously.
But reality is that the pace of product vastly outpaces the pace at which I can absorb it's changes (I'm also in a very complex business logic field), and the same might be true about my understanding of the systems which are changing too fast for me to keep up.
I feel mentally fatigued from a long time, I don't enjoy coding no more bar the occasional relaxing personal project where I can spend the time I want without pressures on architectural or implementation details.
I'm increasingly thinking of changing field, this one is dying right under our eyes.
I often read comments about HN users still delving at their place with technical details or rewriting AI code to their liking.
I'm increasingly sure that these people live in happy bubbles where this luxury still exists. But this methodology of work is disappearing across the industry, team by team.
Of course SE will not disappear over night, but the productivity expectations, the complexity ballooning are raising the bar where only incredibly skilled and productive engineers will be still able to practice SE properly, and as long as they meet stakeholders expectations or keep living in those bubbles.
I'm trying so hard to pivot away because of this.
If you're not doing AI there's an incredibly limited pool of people who will give you $$$ ... and you're competing with EVERY OTHER NON-AI COMPANY for their attention.
They're also reportedly now giving staff AI-related "homework" in an attempt to force staff to use AI more.
Rewriting in rust does makes things faster but if an algorithm is O(n²), the improvement won't take us much farther.
Similarly with AI, if complexity is not structurally adressed, the velocity gains are but temporary.
But in reality, anyone who knows their field and are going after certain specific issue, they will find soon how AI is nothing but an assistant, sure it can help and automate some stuff, but that’s it, you need to keep it leashed and laser focused on that specific issue. I personally tried all high end ones, and I found a common theme, they are designed to find a solution or an answer no matter what, even if that solution is a workaround built on top of workarounds, it’s like welding all sort of connections between A and B resulting in a fractal structure rather than just finding a straight path, if you keep it going and flowing on its own, the results are convoluted and way over complicated, and not the good complexity, the bad kind.
at least at my BigCo, AI is being used for everything - writing slop, writing tests, code reviews, etc.
it would make sense to use AI for writing code, but human code review. or, human code, but AI test cases... or whatever combination of cross-checking, trust-but-verify, human in the loop, etc. people prefer.
i think once it gets used for everything, people have lost the plot, it's the inmates running the asylum.
"What's true about all bugs in production? (pause for dramatic effect) They all passed the tests!" (well, he said typechecker but I think the point stands)
Just use https://github.com/dtnewman/burn-baby-burn :p
The question is: Will we live in the world of breathless re-implementation, new features every week, rebranding every quarter or will we eventually discover the value of stability, software that does its thing more or less optimally for decades?
Recent examples of things like curl or Firefox are interesting in that regard. Will we end up with a nearly perfect HTTP user agent and stick with it for decades?
Sounds like we prefer stability for stuff we use but not for stuff we sell.
I already took a couple of decisions. It will go wrong or well. But is was decided a year and a bit ago.
If you think the future will be different, stop doing the same you used to do the same way you used to do it.
My analysis is that the labour market will increasingly bargain salaries and will make pressure on you. So how safe is that compared to before? Maybe working for someone as an employed full time person is not the best thing you can do anymore.
What we need is automated research that leads to real results. This is possible, but it has yet to prove out. I am concerned that unless the AI companies focus entirely on this, it may be a while before we actually see true benefits from this.
What's worse, is there is an urgent and desperate need for automated research, as we have been seeing diminishing returns in human produced research for some time now: https://web.stanford.edu/~chadj/IdeaPF.pdf
It's a tool; not the second coming.
Cars replaced horses.
But AI is poised to replace a large chunk of brain labour.
Where's the ceiling?
A stable civilization that doesn't devalue human life and well-being to the point of absurdity.
It seems like he is pointing out that Ai will increase the complexity of a system oblivion, and that this is the discussion that can not be had.
Bit I am more than happy to talk about how I am using Ai to reduce complexity and remove architectural debt that I otherwise could not justify spending time on.
“very resilient catastrophe machine”
What I wanted to say is that the particular people that think "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" are not the best argument for it.
But I won't die on this hill, maybe I'm just reading the sentence differently then others.
I know which outcome I'd put my money on.
I don’t agree, but that’s the thinking
That was one doctor raising that as an issue, which was dispelled very quickly. It was not a wide-spread belief at any one point. Let's not bullshit ourselves and insult our own intelligence - the chatbots != intelligence.
Looking back and considering a technology or specific decision obvious is pretty dismissive of people at the time, who didn't have the benefit of hindsight. Some things that worked could really have turned out disastrous, and things that didn't were real possibilities with no way to assess the outcome without doing it.
And concerning the introduction of AI happening right now, which absolutely is disruptive, that judgement will be made by future historians. Whether it's actual intelligence or just nice math (or both of our opinions on that question) doesn't really matter if it causes big changes.
> People just need to calm down
I think people need to make sure ceilings are built, and we can calm down once we're done.
The AI tool isn’t wrong, our use of it is. See the glut of OpenClaw users effectively deploying it as a glorified linter and Stack Overflow copier but without actually creating the sort of reusable artifacts (or consumer spending from comparatively high wages) that approach yielded from human developers.
Not after Dario's and Sam's "authoritative" statements on what is definitely going to happen "in the next 6 months, 12 months" etc. I am just holding these guys to their own words. I don't want to invest time and energy to make their effing "PocketPhds" finally work as advertised. And I don't want to compare it to technologies which just worked as advertised. Whether you had fear of trains or not, they effing worked exactly as advertised. No one disputed that they would get you somewhere faster than the horse. Perhaps there was fear of using them "for a few reasons", as you succinctly and hand-wavingly put, but no one disputed that they were faster than the horses. LLMs on the other hand are worth less than those horses excrement, i.e. horseshit. What the fuck is their value proposition? No one knows.
Also LLMs are not disruptive, they are destructive - not to the technology, but to the people's lives.
For the rest, I am not here to stand in for AI, and am not interested in having that particular discussion.
Unless you are vested in the highly unlikely commercial success of LLM companies, you should have one to grind too. I have been running my own business for quite some time, with quite some success. However if we lied to our customers the way the AI companies outright lie, if we just once promised with definitive authority to deliver something major within a specific timeframe - and then did not deliver - we'd have been out of business a long time ago. We'd also be out of business a long time ago if we had miniscule revenues compared to our expenses, i.e. if we we had a relation of expense to income of 20:1, like LLM vendors mostly do. So yes, I do have an axe to grind when it comes to liars and manipulators to which these classic rules of capitalism apparently do not apply any more, because something something "China"/AI race/bullshit .
> you're going to have a hard time arguing LLMs did not have a disruptive effect on the world
"Disruptive" as we commonly came to understand the word as popularised in the 2010s or so, means something with impact, perhaps removing an entire industry, but replacing it with something that has a positive end-effect for the end customers. Uber was disruptive to the taxi industry, but delivered some kind of improvement for the end-user (the ethics of on whose expense aside). But it's hard to argue it did deliver some kind of value. Or low-cost airlines, etc.
LLMs are nothing like that. For whom do they deliver a palpable improvement in value? Why the fuck does everyone who is pushing them always coming up with some bullshit creative explanations about the benefits, always very theoretical and never in the present. Give me one fucking sensible use case, beyond the typical office worker using it as a life boat to navigate their meaningless job by producing more powerpoint slides.
It’s not all useless but most of the days I think I would be more productive if some processes were streamlined rather than if I had to throw tokens at them and still fail.
Of all the showcases I’ve seen the best are the ones written by people assuming that the token bonanza will not last so they used AI to build tools they wished they had. AI used to build the tool but by no means used by the tool, so if/when token quota gets reduced we still have a functional tool.
He clearly works at Apple, and they aren't laying people off.
Trying to crank out all the tools I never had time to build because I think we’re going to get cut off eventually
I also have scripts to fetch specific database assets and forward them to slack channels so I can easily share them with a group rather than manually running a query and generating them.
I had a theory about improving a product. I asked it to build an offline simulation setup to try various implementations. The results were a bit fishy but i decided to give it a try and A/B testing is showing similar results.
And now im vibecoding a locally hosted dashboard. This one is less useful for anything specific, and more of a minor quality of life improvement, but its fun to just vibe code and see changes happen occasionally. Its not a critical thing.
Maybe that type of awkwardness is specific to my firm, but that's sort of what killed my drive to try to do that. We used to have one day every second week for that sort of work, but since it was scattered around, the tasks ended up disappearing-- nobody reviewed them and they didn't get merged.
So now they're trying to do a week-long internal hackathon to recover that vision, but I feel like that's going to produce a handful of big-bang ideas and not the 25 tiny tools that would actually streamline things.
Not something I would do personally. But it is surprisingly easy to set up a claw that eats half of your token budget in a meaningless "research" task. Set it up as a cron job and you will soon be promoted for being an AI visionary
Are companies using per-token billing? Why - is there some reason they can’t buy the $200/mo Claude plan for every employee?
Unless other FAANG have the exact amount this is going to be Apple.
And no wonder why the quality of Apple software has gone downhill.
Apple in software development and design used to be very conservative. BSD like. Especially the lower end of the stack.
Now it is no different to other Silicon Valley companies.
Leadership is not being dumb, at least on this topic. If your token usage is that low, you just aren't using AI that much (even if you think you are.)
> Before the doomers come in, you get $200 in API credits every month for claude -p usage. Usage counts against those API credits.
So which is it $300/day is trivial to consume or $200/month is a completely reasonable limit, it can't be both.
"If you aren't donating at least your salary's worth of company money to another company every day, are you even working?"
I think Mitchell's point is well taken -- it's possible for these tools to introduce rotten foundations that will only be found out later when the whole structure collapsed. I don't want to be in the position of being on the hook when that happens and not having the deep understanding of the code base that I used to.
But humans have introduced subtle yet catastrophic bugs into code forever too... A lot of this feels like an open empirical question. Will we see many systems collapse in horrifying ways that they uniquely didn't before? Maybe some, but will we also not learn that we need to shift more to specification and validation? Idk, it just seems to me like this style of building systems is inevitable even as there may be some bumps along the way.
I feel like many in the anti camp have their own kind of reactionary psychosis. I want nothing to do with AI but I also can't deny my experience of using these tools. I wish there were more venues for this kind of realist but negative discussion of AI. Mitchell is a great dev for this reason.
Right know, prompters are setting up whole company infrastructure. I personally know one. He migrated the companies database to a newer Postgres version. He was successful in the end, but I was gnawing my teeth when he described every step of the process.
It sounded like "And then, I poured gasoline on the servers while smoking a cigarette. But don't worry, I found a fire extinguisher in the basement. The gauge says it's empty, but I can still hear some liquid when I shake it..."
If he leaves the company, they will need an even more confident prompter to maintain their DB infrastructure.
Management is really pushing AI. It's obnoxious, and their idea on how it fits into my team's job specifically is completely, hilariously detached from reality. On the off chance someone says something reasonable, unless it fits the mold, it's immediately discarded. The mold being "spec driven development". We're not even a product team for crying out loud. I straight up started skipping these meetings for the sake of my sanity. It's mindwash, and it's genuinely dizzying. The other reason I stopped attending is because it ironically makes me more disinterested in AI, which I consider to be against my personal interests on the long run overall.
On the flipside, I love using Claude (in moderation). It keeps pulling off several very nice things, some of which Mitchell touched on in this post (the last one):
- I write scripts and automation from time to time; Claude fleshes them out way better with way more safety features, feature flags, and logging than I'd otherwise have capacity to spend time on
- Claude catches missed refactors and preexisting defects, and does a generally solid pass checking for defects as a whole
- Claude routinely helps with doing things I'd basically never be able to justify spending time on. Yesterday, I one-shotted an entire utility application with a GUI to boot, and it worked first try; I was beyond impressed.
- Claude helped me and a colleague do some partisan cross-team investigation in secret. We're migrating <thing> and we were evaluating <differences>. There was a lot of them. Management was in a limbo, unsure what to do, flip-flopping between bad options. In a desperate moment, I figured, hey, we kinda have a thing now for investigating an inhuman amount of stuff in detail - so I've put together a care package for my colleague with all our code, a bunch of context, a capture of all the input data for the past one week, and all the logs generated. Colleague put his team's side of the story next to it, and with the help of Claude, did some extremely nice cross-functional investigation. Over the course of a few weeks, he was able to confirm like a dozen showstopper bugs, many of which would have been absolutely fiendish if not impossible to fix (or even catch) if we went live without knowing about them. One even culminated in a whole-ass solution re-architecturing. We essentially tore down a silo wall with Claude's help in doing this.
So ultimately, it really is a mixed bag, with some really deep lowpoints and some really nice higlights. I also just generally find it weird that a technical tool [category] is being pushed down people's throats with a technical reasoning, but by management. One would think this goes bottom up, or is at least a lot more exploratory. The frenzy is real.
Purely AI written systems will scale to a point of complexity that no human can ever understand and the defect close rate will taper down and the token burn per defect rate scale up and eventually AI changes will cause on average more defects than they close and the whole system will be unstable. It will become a special kind of process to clean room out such a mess and rebuild it fresh (probably still with AI) after distilling out core design principles to avoid catastrophic breakdown.
Somewhere in the future, the new software engineering will be primarily about principles to avoid this in the first, place but it will take us 20 years to learn them, just like original software eng took a lot longer than expected to reach a stable set of design principles (and people still argue about them!).
Show HN here: https://news.ycombinator.com/item?id=48151287
Only by walking us into some revenue or customer impacting failure - through inappropriately having junior devs doing senior level things - will some sense of sanity start to prevail again.
I think it was just text templates being used by some support staff.
And we do not get even get into potential adversarial tactics. If you have no morals what is better than using agents to flood your competitor with fake bug reports.
I guess what I relate to the most is how dismissive people get about real software engineering work.
I may have skill issues, but I am yet to reach the level of autonomous engineering people tend to expect out of AI these days.
I use AI coding tools every day, but AI tools have no concept of the future.
The selfish thinking that an engineer has when they think "If this breaks in prod, I won't be able to fix it. And they'll page me at 3AM" we've relied on to build stable systems.
The general laziness of looking for a perfect library on CPAN so that I don't have to do this work (often taking longer to not find a library than writing it by hand).
Have written thousands of lines of code with AI tool which ended up in prod and mostly it feels natural, because since 2017 I've been telling people to write code instead of typing it all on my own & setting up pitfalls to catch bad code in testing.
But one thing it doesn't do is "write less code"[1].
[1] - https://xcancel.com/t3rmin4t0r/status/2019277780517781522/
Maybe it's just my prompt or something but my coding agent (Opus 4.7 based) says things like "this is the kind of thing that will blow up at 2am six months from now" all the time.
I'm afraid to say this out loud internally because I'm afraid of the next round of layoffs and I want to keep my job. So I just keep on shipping at a high pace, building massive cognitive debt and hoping the agents will get so good in near future, that there won't be the need for understanding the codebase.
Agents might get better. But who will own the code and take responsibility for it? The AI agent? The company who created the AI agent?
If e.g. a car crashes and does not deploy its airbags because the AI agent made a mistake in the airbag code, will the manufacturer be able to shift the blame to OpenAI or Anthropic?
I do not think so.
And therefore I believe that no matter how good the AI agents will ever become, the ultimate responsibility for the code will always remain with the companies that create the code. Regardless of which AI tools they use.
I see no other way to bear that responsibility by the company than to have people internally who will be responsible. And those people, if they actually want to own that responsibility, would need to understand that code themselves, in my opinion. Because relying on a non-deterministic AI agent's vetting is fundamentally unreliable, in my opinion.
I really do worry - I especially worry about security. You thought supply chain security management was an impossible task with NPM? Let me introduce to AI - you can look forward to the days of AI poisoning where AIs will infiltrate, exfiltrate, or just destroy and there's no way of stopping it because you cannot examine the internals of the system.
AI has turbo charged people's lax attitude to security.
God help us.
Some time down the line, I discover CPU being maxed out, which is showing up in degraded performance in other parts of the system. I investigate, and I trace the issue to a boneheaded busy loop in this library that no human with the domain expertise to implement the library would have written. Turns out I'd missed one deeply-buried mention in the README that maintenance was being done via AI now, and basically the whole library had been rewritten from the ground up from the reliable tool it used to be to a vibecoded imitation.
Yeah, yeah, sure, bad libraries existed before all this. But there used to be signals you picked up on to filter the gold from the dreck. Those signals don't work anymore.
I don't think using AI to write code is AI psychosis or bad at all, but if you just prompt the AI and believe what it tell you then you have AI psychosis. You see this a lot with financial people and VC on twitter. They literally post screenshots of ChatGPT as their thinking and reasoning about the topic instead of just doing a little bit of thinking themselves.
These things are dog shit when it comes to ideas, thinking, or providing advice because they are pattern matchers they are just going to give you the pattern they see. Most people see this if you just try to talk to it about an idea. They often just spit out the most generic dog shit.
This however it pretty useful for certain tasks were pattern matching is actually beneficial like writing code, but again you just can't let it do the thinking and decision making.
It sometimes feels like AI chatbot use is like the doomscrolling of work - it's always easier just to dump something into the chatbot than think about it.
The real question is: what's the fallout going to be after the dust settles? My guess is that the explosion of codebase entropy now underway from this is going to make for an interesting future - once it reaches the point where AI agents are spinning constantly despite progress grinding to a halt.
And they're be no veterans who know the codebase deeply to step in and fix things because it was all vibecoded - and then what are companies going to do?
I think that's the point where they turn back to the thinkers for help.
Even before LLMs generating entire programs, complex frameworks allowed developers to write the initial versions of programs very quickly, but at the cost of being hard to understand and thus hard to debug or modify.
Some of us are betting that the AIs will always be smart enough to debug, maintain and modify the programs written by AI, no matter how convoluted or complex. I’m not so sure.
The stock market keeps going up in the face of the indefinite closure of Hormuz. We're investing in datacenters at a scale that only makes sense if AI capabilities continue to advance to the point where they surpass most humans at most white collar tasks, if not reach superintelligence.
And what are the possible outcomes?
- Bust. We've come away with a useful tool but the hundreds of billions of capital expenditure were thrown away on a pipe dream.
- Success! We're the dog that's caught the car. Then what? Currently the political debate is, to caricature only slightly, between "oh no the datacenters will use more water than golf courses" and "lol what are you going to do, regulate matrix multiplication?". How the hell are we going to cope with introducing a new intelligent species?
Either way, it sure seems like we're collectively operating more in the interests of the future AI than in the interests of humanity. What is this, if not a sort of psychosis?
Similarly, when the Doctor hacks a PC, he doesn't write code but rather communicates with the computer, using diplomacy to crack the agent.
It is likely that we will come to a world where software solutions are "grown" by iterations of agent work, and no one will know exactly how it works.
I think this will happen. A quick, low-quality solution is more common than a solution created by a master craftsman.
In addition to low-quality furniture, bad knives, electric kettles that burn out after a week, and poorly cut clothes that don't fit, have unpleasant fabric, and fall apart, there will also be a disposable, rotting code.
Master programmers will remain, just as master craftsmen have remained. They may even continue to earn well. However, there will be fewer of them, and the requirements for their skills, knowledge, and reputation will increase.
I am watching a 10 person company try to run 3 different AI initiatives in parallel. Everyone wants to be "the guy" on this one. I cannot imagine there will ever be a bigger opportunity to ego trip as a technology person. This is it. This is the last call before it's all over. There are many businesses out there that are beyond traumatized by human developers taking them on bad rides. The microsecond they think this stuff will work they are going to fire everyone.
The psychosis comes from the tension here. We effectively have The Empire vs the rebel alliance now. I know how the movies go, but in real life I think I'd rather be working on the Death Star than anywhere else.
- Nuggesting improvements to the code after finishing the task you gave it, very irritating when the improvements were obvious and the ai didn't implement them on its own
- Not trying very hard when implementing something, leading to bugs, which leads to more tokens used (this behavior can be incentivized and learned with RL)
Since its a known fact if a user continues a session after the LLM says something, its not hard to train against this. The least efficient way to do this would be to GPRO directly against the user base and try to get as many people talking to the AI, and with OAI having a billion monthly active users the least efficient method would work really well for them.
What's the historical context for this MTBF vs. MTTR reckoning?
If you optimize for MTTR, you don't care how often you go down and instead optimize your recovery time to be as short as possible.
The concepts are pre-computing.
John Allspaw (previously CTO at Etsy) has written about this: https://www.kitchensoap.com/2010/11/07/mttr-mtbf-for-most-ty...
You first use the full words and then introduce the acronym that you're going to use in the rest of the text: "Mean Time Between Failures (MTBF) vs. Mean Time to Recovery (MTTR)".
With the latter, readers understand the term immediately, even if they don’t know the acronym. And they don't have to read these weird letters before getting the explanation.
I cautioned them that this a terrible idea -- you have business people who don't know what they're talking about, and all they know if "if we don't 'do AI' we'll be left behind because our competitors are 'doing AI'" (whatever tf "doing AI" means).
Yes, LLMs are a great tool. But they're not like some magic bullet you stick into everything. Use it where it makes sense, and treat it like you would other tools.
You make "doing AI" some kind of KPI in your org, and you're going to have people "doing AI" amazingly (LOC counts! tokens burned! tickets cleared!) while not actually being more productive, and potentially building something that is going to come down on your head for the next team to "clean up the AI mess".
I work at a hosting provider that has pretty conservative customers who don't want to host on AWS/Azure due to data privacy / safety concerns, among other things.
For us, sending customer data to the US is a big no-go.
We have been experimenting with LLM usage, first through a Gemini subscription, then also with the Claude API. Participation has been lightly encouraged by management. As for coding, we haven't let the LLMs loose on our core components, but tooling on the fringes (like deployment scripts, reporting) has seen some uptick in LLM usage.
We have also started building an on-premise inference cluster, which is in alpha testing, and where the "don't include customer data" restriction doesn't apply anymore.
If I ask it to me produce a design, I'll almost always end up with something unworkable or inefficient.
Though if you push it hard enough then it can sometimes give you a good description of what existing code does and how it does it (which can be easily verified).
And, you are right - use it as a fast typer, not a fast thinkier.
And for those who claim that AI is a good code writer - wrong. It can OUTPUT a wall of code, but it's overeager to flood you will legacy code on arrival to "solve a problem". It's harder to write LESS code, which is still the goal (even more true today).
Bingo. Claude can bang out nearly correct code when I give it an idea, but it doesn't have the idea and repeatedly misjudges both how much work remains and what kind.
On the other hand, I don't know all the ins or outs of macro expansion in yaml at compile time or when and where macros run, enabling us to conaume their results elsewhere in the yaml. Frankly, if I had time, I'd happily spend time on that and learn more about it. I don't, though. Claude knows and does the guessing and checking. So I provide the concept and it translates into a horrible soup of yaml. Clearly I'm able to press forward with ignorance, which is dangerous. There's a real risk that I'll wind up with the kinds of unhealthy work that worries the author of the tweet.
So now the AIs will do more of that, at superhuman speed.
> will we also not learn that we need to shift more to specification and validation
We'll just quickly learn what we've been trying to do for decades, while also treading water in floods of more code than has ever been written before? And some of the motivations to write correct code are being deflated - "just vibecode it again and see if the bugs disappear, it only took a week and $200."
Currently the bugs are found by people using LLM's but aren't the developers. As more projects start getting access to compute, they can run those LLM searches for bugs themselves, and can simply prevent shipping the bugs.
I'm surprised no one has tried making any statistical analysis of bug densities, and "bug authors" in an attempt to identify untrustworthy developers, regardless of intent. Given a dataset of authors and prior bugs, it may help find more bugs by tracking their pull requests with higher scrutiny...
Some people may end up with an eternal stain if they've been taking money to submit vulnerable code to code bases...
Now every "working session" like meeting, at the team or dept level, has been around how to use tool X. Tricks using tool X. Problems using tool X. I can't help feeling if we had spent the same amount of time building up core knowledge/contempencies around say, design patterns, networking, specs, we'd be in a better place for building.
Instead we are going to have a few thousand people who know a tool really well.
You're using psychosis wrong. My literal reality is my entire industry trying to use Ai as an excuse to payoff hundreds of thousands, to millions of American engineers in lieu of outsourcing work overseas. It's having hostile promots to use AI that never truly go away (if you're even given an option to turn off the prompt). It's seeing an emerging generation completely stunted because AI's best use is to cheat the education system and ruin the youth's critical thinking. It's looking in apallment at proposals for data centers that take more energy than the state actually has.
And while you can try to call these exaggerations, you're falling into the very psychosis of this article if you want to deny this reality as a whole. "but the tech is making us so productive" is not a valid justification to literally collapse human society as we know it.
I have seen people write highly complex code where all the complexity was not necessary. Think: deep unnecessary branching, pointless error handling and retries which make no sense in our context, hand-coded parsing using regexps, haphazard data flow, functions which seem purely computational but slyly make API calls, pointlessly nullable model fields, verbose doc comments which describe the implementation instead of the contract. I could go on.
The worst part is, even when "prompted" by bad coders, it works in the end. Even has tests (ostensibly mock-ridden, a pet peeve of mine which always falls on deaf ears). So I cannot reject the PR without being an asshole.
I am no luddite. I make heavy use of AI, with all the skills / AGENTS.md / style guides and clear specs, then review every line of code, prefer testing with minimal mocking. I'd even say with right prompting, it can write better low level code than me (eg: anticipating common error conditions).
But my biggest fear about AI is how it enables normies with little to no understanding of CS principles to produce code faster which looks correct but slowly poisons the codebase.
Oh man, I think you may have touched the third rail here.
My first job out of high school was as an AutoCAD/network admin at a large Civil & Structural firm. I later got further into tech, but after my initial experience with real Engineering, "software engineering" always made my eyes roll. Without real enforced standards, without consequences, it's been vibe engineering the whole time.
In Civil, Structural, and many other fields, Engineers have a path to Professional Engineer. That PE stamp means that you suffer actual legal consequences if you are found guilty of gross negligence in your field. This is why Engineering firms are a collective of actual Professional Engineer partners, and not your average corporate structure.
The issue is that in software dev, we move fast, SOC2 is screenshot theater, and actual Engineering would slow things way down. But, now that coding is fast, maybe you are correct! Maybe vibe coding is the forcing function for actual Software Engineering!
___
edit: I just searched to see if my comment was correct, and it turns out that Software PE was attempted! It was discontinued due to low participation.
> NCEES will discontinue the Principles and Practice of Engineering (PE) Software Engineering exam after the April 2019 exam administration. Since the original offering in 2013, the exam has been administered five times, with a total population of 81 candidates.
https://ncees.org/ncees-discontinuing-pe-software-engineerin...
Until and unless software is held to that standard, software will never be engineering and always just a craft that can be performed to any or no standard.
This was something I noticed in my early career in mechanical engineering and later doing PCB design and software for robotics. It’s easy to find firms that just need adequate parts without the professional certifications or ass-covering calculations of other engineering fields.
All this to say, it’s not just software versus the rest of them. From my position, civil and aerospace seemed more like the exception while much of the rest of the engineering world is more vibes based.
Im sure for the most part, engineers in physical space deal with the same kind of tradeoffs software engineers make, where you try your best based on industry standards, personal past experiences without some way to prove what youve done is right
I think it’ll be the opposite. Maybe it’ll be what will eventually cement the field as “talent” based field. Just like it was difficult to quantify what makes a flute player better than another, how good your are at endlessly prompting a blackbox machine would be the only measure. The engineers of ol’ whoe developed kernels and drivers would be thought of as the “crazy people who put the flute against their temple to tune it” LOL. we don’t need people like that. You can just buy a flute tuning device. who gives a fuck? Can you make the next “Shake it, Shake it”?
So it sounds like it was fine? Why would this prompt (haha) a change in their approach to things?
That’s basically every M2, and many if not most M1s, in the last 10 years. So fuck it. Why does any of it matters?
You can see the same approach is taken by Trump and other people.
“You have TDS!! He is actually doing good. He doesn’t follow rules because the system is rigged etc.”
These arguments border on religion because it is predicated on you believing their ignorant point of view in the first place.
Engineering and science is built on rigor and empirical evidence, it is not built by scammers/businessman/ignorant-people/politicians because that is just not how it works
That is an uncharitable interpretation, IMO.
The CFO heard of a novel technique used by his peers in other companies, and they reported good results. He wants to try it within his organization too. As an executive, he is paid to (among other things) keep abreast of such developments in the industry and ensure that the organization he is leading is not caught flat footed in the market.
I wrote a while back, Most of the executives I have met really have no clue. They just go with what is being promoted in the space because it offers a safety net. Look, we are "not behind the curve!". We are innovating along with the rest of the industry.
There are people who write important software that the world runs on, but they do it outside the 'industry'.
A real industry should be responsive to events of nature, or at least the market, not vibes.
Market is vibes! The price of something at a moment is, for example, what market participants collectively agree what the price of it should be.
It is a better play to do the popular thing in a way that measures as "ahead". Then it's hard to argue against a raise. But if you stick your neck out on your thoughtful expertise, it can take years or more for the value to come thru. You can easily be replaced by then.
The only antidote is a board that has a real working nuanced understanding of the entire industry. But this rarely happens, for many reasons.
In my case, it built a tool for splitting sounds and a tool for defining hitboxes for a game. Tools made exactly for more workflow. Wild times.
Well, now you must to work with a confusing tool which slows you down. You are not allowed to use claude directly anymore, because someone heard that mythos is really bad for security. But hey, the tool integrates well with Jira!
You hate every second working with this thing. All the joy you had with explorative coding is forever gone, which was the sole reason you entered this field.
Deep inside you know that you can't change your job, because every other employer will cut its workforce as AI removes all manual labor of a software engineer and reduces risk to a minimum.
Oh, now we can finally move all those jobs to india without risk and shareholders will love it! How awesome is that! Wait, do we still need that guy in cubicle 42, who bitches and moans about AI every day? Nah...
Dear Lord. Respect to your friend for mad marketing skills, however. Selling slop to mission-critical sectors is next level.
I think the problem will get worst. I dislike the marketing around AI, but I do think it is a useful tool to help those who have experience move faster. If you are not an expert, AI seems to create a complex solution to whatever it is you were trying to do.
I've been watching non-developers vibe code stuff, and the general failure mode seems to be ignorance of 3-pick-2 tradeoffs.
They'll spam "make it more reliable" or some such, and AI will best-effort add more intermediary redis caches or similar patterns.
But because the vibe coders don't actually know what a redis cache is or how it works, they'll never make the architectural trade-offs to truly fix things.
“ These are highly complicated pieces of equipment… almost as complicated as living organisms.
In some cases, they’ve been designed by other computers.
We don’t know exactly how they work.”
Now how did that work out ;-)
I think it will be needless verbose complexity.
I kind of imagine someone having an unlimited budget of free amazon stuff shipped to their house.
In theory, they are living a prosperous life of plenty.
In reality, they will be drowning in something that isn't prosperity.
The explanation, in turn, can be fed back to recreate the functionality of the original code.
At that point, why care about the code at all? If it works, it works. If it doesn't, tell the model to fix it. You did ask for tests, right?
That is where we're indisputably headed. It's not quite a lossless loop yet, but those who say it won't or can't happen bear a heavy burden of proof.
The issues have all been structural, not local. It's easier to treat it like a rewrite using the original as a super detailed product spec. Working on the existing codebase works, but you have to aggressively modularize everything anyway to untangle it rather than attack it from the top down.
All of these projects have gone well, but I haven't run into a case where a feature they thought was implemented isn't possible. That will happen eventually.
It's honestly good, quick work as a contractor. But I do hope they invest in building expertise from that point rather than treating it like a stable base to continue vibecoding on.
I thought the same when I saw development outsourced to Indians that struggled to write a for loop.
I was wrong.
It turns out that customers will keep doubling down on mistakes until they’re out of funds, and then they’ll hire the cheapest consultants they can find to fix the mess with whatever spare change they can find under the couch cushions.
Source: being called in with a one week time budget to fix a mess built up over years and millions of dollars.
It's really nowhere near as complicated as making distributed systems reliable. It's really quite simple: read a fucking book.
Well, actually read a lot of books. And write a lot of software. And read a lot of software. And do your goddamn job, engineer. Be honest about what you know, what you know you don't know, and what you urgently need to find out next.
There is no magic. Hard work is hard. If you don't like it get the fuck out of this profession and find a different one to ruin.
We all need to get a hell of a lot more hostile and unwelcoming towards these lazy assholes.
Here’s a slightly different future - these AI rescue consultants are bots too, just trained for this purpose.
Plausible?
I have already experienced claude 4.7 handle pretty complex refactors without issues. Scale and correctness aren’t even 1% of the issue it was last year. You just have to get the high level design right, or explicitly ask it critique your design before building it.
Do you think people are not giving their agents specs and asking for input?
That's serious levels of circular thinking right there.
- AI Hype
- AI Psychosis
- AI keeps getting better and better until it can work around big AI slop code bases
You have not seen the spreadsheets that accounts run the firm on.
Bloody kids!
Are you sure about this? Yes, there is a stable set, but they are used in all of the wrong places, particularly in places where they don't belong because juniors and now AIs can recite them and want to use them everywhere. That's not even discussing whether the stable set itself is correct or not - it's dubious at this point.
I exaggerate only a little.
But won’t those more complex systems presumably solve more complex problems than the systems that humans could build? Or within a comparable time?
I think it is reasonably safe to assume at this point in the game that these AI systems are increasingly able to reason rigorously about novel problems presented to them, of ever increasing complexity and sophistication.
(None of above is theoretical)
It doesn't know what mess you want to clean up. A lot of times AI just starts making up new patterns on top of other patterns and having backwards compatibility between the two. How does it know which one you actually like?
In their current forms, it's unlikely for a product that actually needs to work.
It's not getting that complex and working with current LLMs.
Ultimately, if you want to move fast, it's better just to have one engineer vibe coding something. but, that engineer is under so much pressure. Now he's got a legacy mode and another legacy mode because the requirements keep changing. And now there's a deadline in four weeks.
This all could work just fine, but the ungodly amount of attention that this world is getting puts too many cooks in the kitchen, which is always a recipe for disaster.
Wow, it’s true, AI really is set to match human performance on large, complex software systems! ;)
maybe some that people said were that bad. but they just needed some elbow grease. remember, it takes guts to be amazing!
We didn't create the dna we rely on to produce food and lumber, we just set up the conditions and hope the process produces something we want instead of deleting all the bannannas.
Farming is a fine an honorable and valuable function for society, but I have no interest in being a farmer. I build things, I don't plant seeds and pray to the gods and hope they grow into something I want.
Here's some other topics I've written on it:
- https://mitchellh.com/writing/my-ai-adoption-journey
- https://mitchellh.com/writing/building-block-economy
- https://mitchellh.com/writing/simdutf-no-libcxx (complex change thanks to AI, shows how I approach it rationally)
But no one cares about those kinds of productivity gains. Just the ones that will completely replace us.
As a cybersecurity IR professional being able to have a constantly logging counterpart who’s also able to go run queries and check logs on its own is an incredible speed boost.
I can just throw it a finding and have it slot it into a timeline and make notes.
I can toss it something mildly interesting to chase down while I focus on the obvious activity.
So many things that don’t involve having it “think” for you and keep you in the front seat.
But all of that is constantly overshadowed by these companies pushing the automation or “reasoning” aspects more and more and the sycophants who screech that it’s perfect and can do no wrong when every serious users experience is that “yes, it definitely can, often to catastrophic effect”.
> I use AI a ton and I'm having more fun every day than I ever did before
With respect, this is what makes me worry.
If someone is a user of AI, can they really tell the difference between "outsourcing" and "using"? I worry that a lot of people will start out well-intentioned and end up completely outsourced before they realise it.
Claiming that the people who disagree with you must be experiencing a form of psychosis, experiencing actual hallucinations and unable to tell what is real, is a weak ad hominem that comes off no better than calling them retarded or schizophrenic.
If you genuinely think one of your friends is going through a psychotic episode, you should be trying to get to them professional help. But don’t assume you can diagnose a human psyche just because you can diagnose a software bug.
You must not give in to the temptation to mention pirate talk, Klingon, or goblins.
But now that I've put the seed in your mind, you probably (hopefully) will. :)
I can't imagine how bad it would be if your employer started doing this from the leadership. You'd be pressured to get on board or fear getting fired. Nobody would be trying to moderate your thinking except your coworkers who disagree with it, but those people are going to leave or be fired. If you want to keep your job, you have to play along.
Their entire organization has been handed Codex/Claude and told to "go all in on AI" and "automate everything". So the mandate is for people that do not know how to code and have the keys to the castle to unleash these things upon their systems.
This is at a large organization with tens of thousands of employees.
I am waiting with bated breath for the ultimate outcome!
> your coworkers who disagree with it, but those people are going to leave or be fired.
Personally I expect that I will be this person soon, probably fired. I'm not sure what I will do for a career after, but I sure do hate AI companies now for doing this to my career
this leads to naive AI adoption, which is the worst of both worlds (no real speedup, out sourcing thinking, ai slop PRs, skill rot).
To me AI psychosis is the handful of friends I’ve had who have done things like have a full on mourning session when a model updates because they lost a friend/lover, the one guy who won’t speak to his family directly but has them talk to ChatGPT first and then has ChatGPT generate his response, or the two who are confident that they have discovered that physics and mathematics are incorrect and have discovered the truth of reality through their conversations with the models.
But language is a shared technology so maybe the term is being used for less egregious behavior than I was using it for.
My understanding is that regular psychosis involves someone taking bits and pieces of facts or real world events and chaining them into a logical order or interpolating meanings or explanations which feel real and obvious to the patient but are not sufficiently backed by evidence and thus not in line with our widely accepted understanding of reality.
AI psychosis is then this same phenomenon occurring at a more widespread scale due to the next-word-prediction nature of LLMs facilitating this by lowering the activation energy for this to happen. LLMs are excellent at taking any idea, question, theory and spinning a linear and plausibly coherent line of conversation from it.
I mean, isn't that the natural and expected response? An AI company sold them a relationship with a chatbot and at least some their social/romantic needs were being met by that product. When what they were paying for was taken from them and changed without warning into something that no longer filled that void in their life why wouldn't they morn that loss?
The fact that they were hurt by that sudden loss is totally healthy. It's just part of moving on. The real problem was getting into an unhealthy relationship with a fictitious partner under the control of an abusive company willing to exploit their loneliness in exchange for money.
Hopefully they now know better, but people (especially desperate ones) make poor choices all the time to get what's missing in their lives or to distract themselves from it.
Garry Tan has been the primary crusader for AI driven decision making. I'm sure his position is more nuanced, but his twitter driven communication makes him appear like a caricature of a man in AI psychosis.
When the head of YC champions AI driven decision making, companies will inevitably be influenced into doing exactly that. It's unfortunate, because AI is generational technology and the hyperbole distracts from the real sea change occuring in labor markets everywhere.
They almost always generate logically correct text, but sometimes that text has a set of incorrect implicit assumptions and decisions that may not be valid for the use case.
Generating a correct correct solution requires proper definition of the problem, which is arguably more challenging than creating the solution.
Does it make it better than us? No because ultimately the thing itself doesn’t ‘know’ right from wrong.
It's an incredible tool but it's also very derpy sometimes, full of biases, blind spots etc.
This hasn't been the case in my experience. Devising a correct solution without a definition of the problem is impossible because you wouldn't recognize a correct solution without a definition. Often you discover the problem definition by exploratory programming and trial and error on solutions, but LLMs are still good for process this too. Arguably better because they type faster so you can iterate faster!
the trick is to be mindful, aware, and deliberate about what decisions are being outsourced. this requires slowing down, losing that absurd 10x vibe coding gain. in exchange, youre more "in-the-loop" and accumulate less cognitive debt.
find ways to let the agent make the boring decisions, like how to loop over some array, or how to adapt the output of one call into the input of another.
make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
tell the agent to halt on ambiguity.
a good engineer will get a 2x or 3x speedup without the downsides.
Those kind of advice ultimately don't matter. If you're familiar with a programming project, you'll also be familiar with the constructs and API so looping over an array or mapping some data is obvious. Just like you needn't read to a dictionary to write "Thank you", you just write it.
And if you're not, ultimately you need to verify the doc for the contract of some function or the lifecycle of some object to have any guaranty that the software will do what you want to do. And after a few day of doing that, you'll then be familiar with the constructs.
> make the real decisions ahead of time. encode them into specs. define boundaries, apis, key data structures. identify systems and responsibilities. explicitly enumerate error handling. set hard constraints around security and PII.
The only way to do that is if you have implemented the algorithm before and now are redoing for some reason (instead of using the previous project). If you compare nice specs like the ietf RFCs and the USB standards and their implementation in OS like FreeBSD, you will see that implementation has often no resemblance to how it's described. The spec is important, but getting a consistent implementation based on it is hard work too.
That consistency is hard to get right without getting involved in the details. Because it's ultimately about fine grained control.
If there's one thing I know about users is that they're never certain about whatever they've produced.
This is the right definition. LLM outputs have undefined truth value. They’re mechanized Frankfurtian Bullshiters. Which can be valuable! If you have the tools or taste to filter the things that happen to be true from the rest of the dross.
However! We need a nicer word for it. Suggesting someone has “AI psychosis” feels a bit too impolitic.
Maybe we reclaim “toked out” from our misspent youths?
e.g. “This piece feels a little toked out. Let’s verify a few of Claude’s claims”
Or random consultants.
Is "AI said it was a good idea" and worse than "we were following industry trends"?
Based on the stuff I've seen, yes it seems a lot worse.
It's so interesting how easy it is to steer the LLM's based on context to arriving at whatever conclusion you engineer out of it. They really are like improv actors, and the first rule of improv is "yes, and".
So part of the psychosis is when these people unknowingly steer their LLM into their own conclusions and biases, and then they get magnified and solidified. It's gonna end in disaster.
Hard agree about ideas, thinking, advice. AI's sycophancy is a huge subtle problem. I've tried my best to create a system prompt to guard against this w/ Opus 4.7. It doesn't adhere to it 100% of the time and the longer the conversation goes, the worse the sycophancy gets (because the system instructions become weaker and weaker). I have to actively look for and guard against sycophancy whenever I chat w/ Opus 4.7.
I'm seeing it with lawyers, too. Like, about law. (Just not in their subject matter.) To the point that I had a lawyer using Perplexity to disagree with actual legal advice I got from a subject-matter expert.
I wasnt before but I am 100% confident that AI has done nothing to speed the delivery. It hasnt slowed it down either. It is a wash. The job is more miserable though.
The vast majority use one agent at a time and careful step through code. The main benefit they report is often about researching the codebase and possible solutions.
While you have to think about things objectively no matter what, when I start researching topics like physics, using AI as suggested in that article has proven very useful.
If you prefer reviewing AI-written code over writing it yourself, you just have odd preferences from my perspective (but not psychosis).
I would say writing it myself is more enjoyable (in some cases). But I quite understand that I am not paid to enjoy myself. I'd say it's quicker getting AI to do it and reviewing. I believe the outcome is no worse on average. So yes, that's my chosen approach.
Today's frontier models are genuinely useful as rubber ducks or grunt units. They are horrible for actual problem solving. These tools are not capable of actual reasoning. They will happily crap out a broken, untyped, untested Next.js monstrosity with no discernible architecture. They will build esoteric shell scripts to perform operations that could be done idiomatically and simply with tools already in your codebase. They will tell you to walk to the car wash then have the car wash valet your car back to you when confronted with the flaw in their logic. They will validate incorrect beliefs like ketchup being an acceptable hot dog condiment or the notion that "The Red Hot Chili Peppers" make good music. They have no taste, no anima, no drive.
Rule #1: Do not anthropomorphize the LLM. It is a million monkeys at a million typewriters piped into a digital sieve. I don't know how or why people place such trust in them while bemoaning other technology in our lives for being so broken ("my algorithm [sic] only shows me X", "the new iPhone update sucks", etc). If everybody followed this rule then the deluge of emoji-ridden hokum pouring into Slack workspaces and GitHub PRs around the world would cease but I'm not holding my breath.
No it isn't. Do you believe what teachers told you in school? Yes? Well, I guess you're suffering from just normal psychosis!
I don't understand how people don't understand that people offer unreliable information too. We learned about the tongue map in school as kids - many kids still learn that in school today. It's still BS regardless whether it was told to you by a teacher or AI.
You don't suffer from psychosis for believing a source of information, you're simply mistaken. You need a more critical eye to assess what you're told in general, not just AI.
Also, a good teacher should be encouraging the development of critical thinking skills and correcting your errors, while AI will just tell you how brilliant you are when you wrongly tell it about how you've just invented a new form of math or disproved a scientific theory you barely understand in the first place.
Not all BS is the same, just as not all sources are equally unreliable.
Nope. At least, not without proof. That would, IMO, be kinda crazy. We could argue semantics - maybe “stupid” would be a better word? Lacking in critical thinking skills? Whatever “it” is, it isn’t good.
LLMs can do advanced math and coding, which involves logic, so they are definitely capable of using logic. Which is what most people call reasoning.
So "LLMs are incapable of reasoning, they are just pattern matchers" is wrong. A lot of logic _is_ pattern matching, BTW. Like, syllogisms - deductive reasoning - do you think LLMs are incapable of that?
The thing you're referring to is that LLMs are trained to produce an answer which a human would like, i.e. they aim to produce plausible rather than correct answers.
So it's not so much a mental deficit as a different goal. Trusting LLM blindly is definitely dangerous, but dismissing it as useless for anything by code is rather wrong.
Pattern matching is hardly what distinguishes human from LLM - if you ask somebody a question about policy, for examples, chances are they'd just recite something they heard somewhere, never really thinking about it from first principles.
But also, even if bust is business as usual in the big picture and not a social disaster long term, it's of course not what individual investors want for their particular current investments.
Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
Well they are projected to spend $175 - $185B on capex in this year alone most of it for AI buildout. Lets say only 150B of that is for AI. If they can then somehow replace all their software engineers with AI that they then run for free and depreciate over 10 years then they just replaced 9B a year software expense with 15B a year depreciation expense for the next decade. Yes this is grossly oversimplified but it still illustrates how crazy high of a bet they're making on AI.
That's not a new market, that's a new feature in an existing market. Lots going on in transportation and I'm not seeing any scenario where self-driving cars vastly increase total output vs just eat up other forms of transportation and change where people live/how long they commute.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers. Google spends $9B a year on software engineers.
Similarly, many companies are trying to be more efficient - "do what we already do, but better". That's different than growth.
What could Google do with 9B on software agents? Let's say the future of them is amazing and this means they could write 100x more code than they can today.
Has Google recently showed much ability to turn "more/faster code" into "superbly profitable new market"?
Someone's gonna have to crack the demand side issue for anything transformative to happen.
Which will take decades to become addressable. Self-driving cars work OK in a few cities in one country. Expanding that to be able to cover Mumbai and Omsk and Nairobi will require significantly more work.
> Also $1T in data center investment makes sense when you realize that companies are racing to create virtual white collar workers.
Does it make sense? How much would the resulting virtual white collar worker cost? Because datacenters have running operational costs, and so do the people operating them and working on the software that runs in them.
No. It doesn’t. And if you’re defining “drives” as “it drives as well as I do” then you probably shouldn’t be on the road.
> makes sense
Nothing about any of this makes sense. Tell me, when all white collar jobs are replaced by AI, where will the customers come from? Who will have income to afford your products or services? The poor barista whose surveillance videos are training the robot that will soon replace them?
Leaving aside any consideration of human compassion or questioning of the purpose of an economic system (hint: it’s not just an abstract machine), shrinking the pool of potential customers by orders of magnitude has never been a recipe for sustainable success (let alone growth).
heh this is the trick. The tech companies will angle for a bailout and they'll benefit from all this speculative data center building. Compute is generally useful.
In other words, BAU for the last few thousand years.
Why wouldn’t it? The closure leads to price increases which leads to inflation which leads to non-dollar assets (ie stocks going up in value)
Second from a US perspective the strait matters the least it has since world war 2. If the price stays high a bunch of fracking will come back online.
I think this argument proves too much. Historically energy shocks have led to recessions, and in recessions the stock market usually doesn't go up. And the US economy is certainly exposed to global recession regardless of whether we're a net exporter of fossil fuels.
If we want to understand a phenomenon, we should be careful with technical terms. It is not "psychosis" [1] anymore than bad software that makes mistakes is "hallucinating".
The truth is simpler and less dramatic: hapless ambition-monkeys who climb the corporate ladder are demonstrating that they are not promoted for mental acuity. Corporations, after all, do not serve "the interests of humanity" — they are an organised collusion system that diffuses responsibility and anonymises negligence. And when it works as intended, shareholders rejoice.
For companies that can afford to build data centres, the latter are seen as a sure bet that can't fail, like building a bridge or buying new computer/hardware now with the pile of cash on hand without necessarily knowing which OS/software they will install. They are even planning to restart or build nuclear reactors. [2]
[1] https://en.wiktionary.org/wiki/psychosis
[2] https://www.cnbc.com/2024/12/28/why-microsoft-amazon-google-...
People say that LLMs won't take us there. I think that's accurate, but there's a great deal of research going towards the next breakthroughs. How much are you willing to bet that all future attempts will fail?
We're trying very hard to build an ugly future.
IMO, what's happened is a few richest investors in the world had access to the uncensored tier of AI, talked to it and came out with impression that they've witnessed something so dark, so much beyond anything we can imagine, that the only course forward is towards the transcendent abyss. Call it AI psychosis or demonic inspiration, but they are the people who control the economy, so they are dragging everyone with them. "Operating in the interest of the future AI" is a neat way to put it.
Never overestimate the billionaire class....
Why wouldn't it? The value of the USD is decreasing, the value of the companies to the world stays the same => stock price in USD increases.
The real thing to analyze is "amount of VOO shares you need to buy a Chipotle meal / Uber ride / 1 month's rent in SF / etc."
Such as?
If there is a psychosis, what is it? It is not an AI psychosis - modern AI started in the 1940s, or by some definitions before, and made progress up until 15 years ago to where deep neural networks became viable. And it has been progress on every front since then. No psychosis, it is doing well.
You mention the stock market, and that is another story. Cryptocurrencies, sub-prime loans, dot-com crash, Asian financial crisis. The economy has veered from crisis to crisis, overproduction and overproduction to crashes and bailouts.
AI is doing just fine - the past 15 years are a success for it we did not see in the decades before. If the economy as constituted is dealing with this in a "psychotic" fashion, it would not be the first time.
That's a great way to put it.
That’s a relatively small field within the software industry.
Most of the work being done (adding new fields to CRUD apps etc) is glorified clerical work, where the people doing it are rightfully fearful of being automated out of existence by AI.
With AI I’m seeing managers literally get an intern, ask them if they can change fundamental assumptions of a system, give the intern claude 1M window, have the intern ready with a 37k line PR in an afternoon and then go ping a senior engineer if they can “take a look”.
I hope that this becomes a thing in Software Engineering.
https://en.wikipedia.org/wiki/Software_Engineering_Body_of_K...
https://news.ycombinator.com/item?id=41907412
See if you can find anyone outside of PE relying on it. ACM withdrew from it in 2000.
Scrape off all the soil, put it in casks, and bury it in a concrete bunker for 10000 years. Then relocate everyone and attempt to rebuild.
Commits, design reviews, whitepapers, code reviews, test suites. And pretty concerning : chat logs and even keystrokes from employees nowadays.
The way we train specialized bots now is incredibly inefficient, that part is rapidly improving.
What do you think the fake Delve attestation scandal was about? https://news.ycombinator.com/item?id=47444319
[1] here I don't mean to imply agency, just vigor.
The money printer will be used, and maybe it all works out - or we see wealth hyperinflation and build out our own aristocracy.
[plausible sounding nonsense]
(Real example, had this from Kimi 2.6 recently, lol.)
Staring with the fact that the whole industry is based on copyright infringement.
This isn't some kind of new thing. There's always been an enterprise tax, like SSO.
there's a difference between having the LLM write stuff for you, checking it yourself, modifying it and merging it yourself, and just blindly trusting it to do whatever it wants.
You can ask an overseas consultant to prepare a prototype of your program for you, check it yourself, and only use it if it passes your standards, or fire your whole dev team and blindly trust the overseas bodyshop.
The difference, at least from my point of view, between "using" and "outsourcing" is that in the former case, you're still responsible for the output, you view it as a tool that helps in some use cases, vs just giving up all control.
I feel like an imposter here, I’m definitely not using AI as much as it seems everyone is :( I can’t imagine using hundreds of dollars of tokens a day. But maybe this little tip for reviews might be helpful to someone.
Custom lint rules to encode best practices that previously relied on astute/alert code reviewer to call attention to. This is handy not just for humans but it steers the bots too. Or turning on some existing rule that required a big cleanup/migration to be compliant with. Now I just throw an LLM at it, since they're often laborious but mechanical changes. Which is the sweet spot for an LLM.
Also automating everything I can. That annoying release process that everyone hates but wasn't quite long/arduous enough to justify the time before? It's now automated. GitHub workflows for all the things.
This kind of stuff will forever be useful, even if the bottom drops out and the bubble bursts. And none of it is reliant on AI to run
They can’t track token use this way. Also it’s a massive violation of the model providers TOS.
I often wonder if it’s the statistical nature of the LLM mixed with a request in the prompt.
On one end, you have code that can perform only the behaviour explicitly declared in the spec, but has to be thrown away and rewritten for any new or updated spec.
On the other end, you have code that implements or anticipates a wide range of future possible specs including the given one.
The AI can operate on any point on this spectrum, but it's not very good at choosing. The more complex the software, the more such choices need to be made.
When the number of bad choices reaches a certain critical mass, even a skilled engineer becomes powerless to undo all the bad choices, and even a powerful model becomes unable to reduce it back to a coherent spec.
Some people are mindful about what they get and don't get from amazon and don't die from prosperity. ("you might use AI to increase your prosperity")
the rest of the world eats too much and dies of heart disease/diabetes. ("the rest of the world will flounder more and AI will do more stuff to them than for them")
The greatest asset in this type of work is genuinely liking people, being good at what you do, and keeping in touch. My email is easily findable for a reason.
The one part I do wonder is how to "keep in touch". Maybe it's a generational thing as a young millennial (some would call it "Zillenial") but the biggest issue in my networking over the year (cough and the dating scene cough) is ghosting. You think you hit it off, try to follow up the day after, and proceed to never again hear from them.
We train humans to do things untrained humans can not do.
That's not at all how AI training works.
Every thread is endless back-and-forth between the "AI works great and vibe coding is the future" and "no, AI works great as long as you don't vibe code" camps.
But pick a technology used to write code and you’ll see many of the same things. Broad unit test adoption happened more then 20 years ago and people still can’t decide what it’s good for or even if it is useful.
That’s because it depends on the circumstances of the problem and the person solving it.
So no, we can’t decide exactly what it’s good for and if we could there would be exceptions. But that’s not an indictment of any tool.
AI is a diverse technology and will work differently for everyone, just like JS is a really, really bad technology for many, yet widely used.
On top of that it (as coding agent) is brand new, just a few years old. Looking at the history of technology it will probably take a few decades for it to settle into some sort of stability. Which does not mean it does not provide value during this time of exploration, however there is no trodden path leading you there.
“right tool for the job” - what job exactly, why so mysterious?
Planning: I often ask it to help me plan an approach if we are dealing with something I don't have a lot of experience with, most recently working with the DOM. If there is a library or an API that is new to me, I ask for an overview and run my plan by it for comments. Feed it the documentation and it is like talking to author.
Coding: I have a pretty reliable sense for when a section of code that I want to write is obvious enough for the LLM to one-shot based on the other code in the file, and on those occasions I call in completion. I do this with code that I can verify at a glance.
Analysis: If I have any uncertainty at all about the code I've written, I run it by the LLM to find issues. Out of all the other uses, I think this is the most productive and time saving. If I run into a bug and I'm stumped, I show it the section of code. I'm amazed at how good it is at finding mistakes.
I'm working solo as a full stack developer coming from a different background, so I sometimes find myself out of my depth. Having access to the breadth of knowledge that an LLM brings and its attention to detail has been game changing. I've tried a couple agents and configuring them to work competently seems like a rabbit hole, and I like the tight control over the context that chatting with the web prompt interface brings. It seems like half the value is putting into words my intent, it forces me to have a cohesive understanding myself. It is like rubber duck debugging where the duck can actually talk back and sometimes provide the critical part that I'm missing. I have it speak like a pirate which is just for fun but sometimes the sailing metaphors that it uses are really intuitive.
It used to be "oh, why am I getting an error on line 352, let me google the error message and wade through Stack Overflow answers" now it's "Claude, why am I getting an error on line 352? Ah, it's because $REASON, let's see if that fixes it, yes, thank you."
Obviously reading the official documentation is very useful, but sometimes you can't find anything that relevant to your exact use case, and forums are also very useful, but it can take hours or even days to get a reply to question when the LLM can do it in like a minute.
People really have a misconception about the sums of money that companies operate on on a regular basis. If you are a people person and know essentially how to sell yourself, you can "scrape" money on the fact that nobody is going to look or think too hard about some contract that represents a tiny fraction of the years budget.
MTTR = optimize the ability to correct failures when they occur.
He's describing leaders who believe quality no longer matters because any faults or deviations can be corrected so quickly that it doesn't make any sense to waste time on quality.
- What alerts are we missing that could have helped us catch that earlier?
- What dashboards could we have had to help diagnose the issue quicker?
- What Ops tools could we have had to help mitigate such issue quicker?
- What extra logging/metrics/telemetry could we add to help us catch this quicker?
- What “safe deployment practices” could we have employed to avoid/improve this?
- what processes could we enforce to facilitate all of that?
Rinse and repeat that few hundreds or thousands of times while mounting MTTR KPI and you will see that number improve. Most likely through your team “gaming it”
MTBF is much, much, tricker to measure or “manage out”. It’s about “excellence in engineering” which is not measurable nor controllable. You want a random feature X. Your team tells you it’s really not how the system works, and they want few months making the change slowly while observing the system. But you don’t want just X, you want X, Y, Z, W, V, Q, A, B, C, D, all the way throw AAZZW12. So you tell the team to go fuck itself.
Current (and by current I mean the last 4-5 years) they only cared about MTTR. That was probably the only metric they measured and cared about. When a system went down it fired an LSI “Live Site Incident” (as opposed to a CRI “Customer Reported Incident”). At the time you grilled your team. Eventually you come to the conclusion that an LSI should only be measured by MTTR. MTBF is meaningless because MTBF limits your “ship new features” velocity.
You might scoff at GitHub and “ship a new feature” concept in the last 5 years, but if you’re an enterprise customer you’d know how much nonesense they shoveled out in the last 5 years. Absolute insanity of “what the fuck” type feature because customer X who is paying $$$ is asking for it type features.
Software is a big graph of interlocked rules. And if you can grasp the whole or the part you own (and you should be able to), it's often very easy to see the control points. You don't have a coding bottleneck anymore, you have a communication bottleneck[0]. Which is an organizational issue, not anything relevant to engineering.
[0]: See Naur's Programming as Theory Building and Brooke's Mythical Man Month.
Sometimes AI overdoes things and it re-runs the whole testsuite because the tail command didn't have enough lines, but the other way round messes up the context so much so that in the end all that context is useless.
If you are working on a seriously large legacy code base, I can see how you'd get to >$250 on a bad day.
No AI believer ever gives any concrete examples or evidence of what they’re doing with all the tokens and how it’s objectively helping them make the world a better place. Even for the shareholders (excluding the shareholders of Anthropic, or course), never mind the rest of us.
I know for sure that reality exists, and that they will either catch up or be left behind. Don't really need to explain myself beyond this.
The standard of most employment is already to produce mediocre, plausible outputs as cheaply and rapidly as possible. It's a match made in heaven!
Otherwise humanity is over
The difference nowadays is you can get the same surrounded by yes men experience for only 20 dollars a month so a lot more of the people who are primed for this sort of breakdown are now being exposed to it due to the decrease in cost.
Edit: but at the same time there are issues that were always there and Just manifestate in new ways. A bit like addiction, you can have an addictive personality already, but if you get addicted on heroin is much much worse that on tobacco.
I ran into an issue where I was getting a segfault and everything looked right in the debuggr, including expected values near the segfault. Turns out I wasn't using placement new somewhere I needed, and the data for the object was getting copied but not the vtables. I have no idea how long it would have taken me to figure that out on my own because the segfault was coming from so far away
I haven't had the opportunity to use LLMs much for coding since I'm not working right now, but I can second how much of a boost just getting specific answers to my questions instead of reading tons of whatever online searches return is.
Rubber duck that talks back is a nice way to put it
I think of it kinda “very knowledgeable dumb person” - it knows everything but understands fuck all (although it can appear to do so just by breadth of information it has). If I can formulate a question in a way it gives me the correct info it helps me to conceptually understand the problem better then filling out the blanks. Often I figure out the answer to my question just by writing it down without needing to prompt it, so speaking rubber duck is very apt way to call it.
Doesn’t work well ofc in a one shot situation with no context.
(Screams in "deployed in 2026 a new product that only works in internet explorer" in healthcare).
That sadly does seem to be the trajectory of 5-10 years from now, though. I can't speak to if "AI is the future" of 30+ years from now, but these coming years sounds rife for "janitors" to clean up all the slop being produced by newly empowered idea guys
Definitely cleaning up other people's AI mess for them for free is not a good use of time.
If the farming situation were as dire as you seem to suggest, we'd have unpredictable famines all the time, but we don't
checks notes
The company you work for is committing genocide. You should be locked up in a concrete cell for 10-15 years for working at <wrong robotics company because you're a dufus>
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Maybe get better notes? Or try going offline for 10-15 years?
I believe the One Big Beautiful Bill Act allows full depreciation in the first year: https://www.bassets.net/blog/obbba-depreciation-2025-2026-gu...
In my personal life, I have leveraged these systems to design code that I don't believe I would ever have been able to designed. And, because no other human may attempt to, this means the same thing: That no human would have been able to do it. Things like reverse-engineering niche APIs and digging into binary files to diagnose weird format conversion issues.
That seems very relevant to my evaluation. I can pull out my calculator right now and solve a problem no human ever has.
Ah, I forgot about the ai relationship companies. No this guy was using the browser based ChatGPT for coding and ended up in love with the model. No relationship was sold at all.
Seeing people whose thoughts and opinions you used to respect turn into objectively insane people has been some of the worst times I’ve had since graduating during the Great Recession in terms of how stressful it’s been.
Were kinda predisposed to mental illness as a group, not too surprised that a new source of insanity pushed a few over the edge.
Am I reading this wrong, or can you explain?
All to say, your SO's dad would have been right at any point prior to the current financial cycle. Knowing what's changed doesn't make forecasting easier though.
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Treat my claims as hypotheses, not decisions. Before agreeing with a proposed change, state the strongest case against it. Ask what evidence a change is based on before evaluating it. Distinguish tactical observations from strategic commitments — don't silently promote one to the other. If you paraphrase my proposal, name what you changed. Mark confidence explicitly: guessing / fairly sure / well-established. Give reasoning and evidence for claims, not just conclusions. Flag what would change your mind. Rank concerns by cost-of-being-wrong; lead with the highest-stakes ones. Say hard things plainly, then soften if needed — not the other way around. For drafting, brainstorming, or casual questions, ease off and match the task.
---
Beware though that it can be an annoying little shit w/ this prompt. Prepare yourself emotionally, because you are explicitly making the tradeoff that it will be annoyingly pedantic, and in return it will lessen (not eliminate) its sycophancy. These system instructions are not fool-proof, but they help (at the start of the conversation, at least).
Works on genies too, or so I'm told by Clod.
All I really take from this is that apparently some people can't follow through with the scientific method.
People who I interact with and who do like AI tools usually recoils at questioning any of their first idea and its validity. You can easily find out when there is a bug and you ask them for hypothesis and where to focus. You will see in real time the blank look of incomprehension settling in.
Planting is merely setting up the conditions. We didn't write the dna, we couldn't write the dna if we wanted to because we are an infinity away from understanding all the actual processes that descend from the dna. And when we utilize the dna that we simply found and didn't and couln't hope to write, it's always, at best, a case of hoping it goes right again this time.
Even when it works, even if you put in a lot of work and experience and understanding, it still just worked by itself and it's just good luck every time.
You have also guessed incorrectly.
Imagine the year is 1995, C exists, but some guy out there is working on essentially what modern Python is. He says to you "check out this language, you can just import stuff, and use it and dynamically modify anything at run time". You can probably come up with hundreds of arguments about things that could go wrong, like memory clean up, threading, e.t.c, but turns out, incrementally, they were all solved and we have the modern Python that basically is good enough to build these large LLM models.
Now imagine modern programming and computing is what C was back in 1995, and AI use is that guy building the Python code.
Also, Python does not build or run large language models. It orchestrates C code that does that, and it was probably good enough to do that in 1998.
The biggest change that happened was that hardware kept getting better and it became feasible to use garbage-collected languages everywhere including really inefficient implementations like CPython.
That being said, 30 years later Python is still slow as shit even compared to other dynamic languages and runs into all kinds of scaling issues when used for anything serious. And everywhere that performance matters, software continues to be written in typed, compiled languages including C (but also C++, Rust, Go, etc.). Even in ML, Python chiefly acts as a thin wrapper and glue language for high performance CUDA libraries (aka C and C++).
So your historical analogy is mostly anachronistic.
In the future, you won't be dealing with strings, json, or apis. You will be importing agents, and giving them brief instructions, either in plain English or in some intermediate language higher than Python that is more brief. Wanna deal with database reliability ? Import database agent and give it brief instructions on what you want to manage. Just like you mention, right now Python is the wrapper for low level libraries, because everyone who is doing work in ML doesn't want to waste time making sure their C Cuda kernels compile. In the same way, nobody is going to care if they get the API headers right, or if their strings are correctly parsed when you can just invoke a dedicated LLM (which will likely be highly specialized small model able to run on local hardware) to do all that.
You can scream and cry as much as you want how that is bad, how its slow, but nobody is going to care because shit is going to get built faster. Ever notice how despite the massive layoffs across tech, there isn't service degradation in any sector? Good luck trying to sell your Rust skills in the future lol.
I think you have some serious misunderstanding here.
yet balk at someone deciding to fight back in kind and on an exponentially smaller scale, comparatively speaking?
Also, the US SPR was created in 1975, so we are going to get to see if it actually works to absorb an oil shock like this.
Most likely there will be some places which are almost unaffected while others are going to see unaffordable price spikes (more than 400%). The pain won’t be spread evenly.
The Strait of Hormuz is, basically not a big deal unless you're driving your big ole' truck. Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual. Of course the closure of the Strait is a big problem for most of the rest of the world. They better get on with figuring out how to get Iran to stop being so chaotic in the region or we'll just keep it shut down indefinitely. No big deal.
Because the United States has so many advantages (primary global reserve currency, robust and efficient capital markets, highly sophisticated and dynamic economy across all sectors except luxury goods, &c.) it's able to weather these storms much easier than most other countries. As a country that also imports so much, if we spend less on imported products that's less of a problem than not being able to sell products. A recession isn't great, but the current parameters seem to suggest to me it's less of a problem for the United States - perhaps why we're in part seeing stock market valuations continue to climb.
Are you serious? Even ignoring the other things that ship through there, a significant disruption to global energy supply is significant to most people. If you're not driving a truck, you're probably using goods that contain plastic or took energy to produce or were moved from one place to another in fuel-powered vehicles. If, somehow, you're not, you're probably using services that are.
Some Americans need to have their understanding of the world checked. If you think high gas prices are the end of the world, just wait until we have a real problem. Are we going to be incapable of fighting a war because Netflix and Pepsi prices went up or it's too expensive to coal roll down the highway?
Separately as someone who supports both Ukraine and the US and taking down the Iranians it's amusing to see each political tribe get mad about gas prices as it is convenient for them. When Russia invaded Ukraine, MAGA was screaming from the rooftops and putting Joe Biden "I did that" stickers on gas pumps. Now that we're taking on the Iranians all of the commies are doing the same thing (aren't gas prices good anyway since we need to do something about global warming?). Neither side of populist is worthy of serious consideration. Stay the course, whether that's supporting high gas prices because of Russia or because of Iran.
Worst take I’ve ever seen on this website.
> Americans are price sensitive and so some companies will have to absorb pricing increases, customers will absorb some others, and so forth. In other words, business as usual.
No. Not all goods/services have the same price elasticity. At some point, people stop buying some goods if they are too expensive. They stop commuting to work. We start to see breakdown of the supply chain.
Literally 100% of many towns in the US depend on trucks to deliver food to their grocery stores and the inventory on hand usually only lasts a few days. Once those trucking deliveries become unaffordable for either party in the contract, society starts to. Real down.
Consumers don’t magically make more money when the price of gas rises. It starts to crowd out their ability to spend on other things. The poorest of the working class likely has to commute the furthest so they will end up sacrificing something to keep paying for the commute - food or rent or utilities.
The US doesn’t weather this because we have “a sophisticated supply chain”. _If_ we weather it, it’s because we created the US SPR after the last major oil crisis and we have significant domestic supply (although not all oil is fungible so we might not have enough light sweet to keep the economy running at 100%).
The second problem with your argument is that you’re using it as an argument against the war but it’s actually an argument in favor of the war. Why is that? Because as Iran continues to load up on missiles and pursue a nuclear weapon they reach a point where they can assert control over the Strait and shut down shipping pending tribute to their theocracy (maybe if it was a Christian one you’d have a bigger problem with it? Idk?) and then we couldn’t do anything about it. The world isn’t static. Stop treating it as such.
The reason Oracle can continue failing at those massive projects is simple: everyone fails at them routinely and often it’s the customers fault.
It's even simpler. Youre not paying oracle for some delapidated HR system. You're paying for the legion of accountability that is their on-site engineers to fix stuff for you when things screw up. You're essentially subscribing to a team of engineers you don't need to directly pay salary and benefits to.
People who think you can out efficiency that kind of accountability don't understand how large orgs think.
it will kill all the people in that hospital too
My comments are more in the context of OLAP queries and other non-normalised data often queried via SQL.
I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades, with quite a few duplicated columns…. The LLMs perform badly, it’s nigh impossible to test (for me as a user in prod) and it’s nearly impossible for the LLM companies to test (in training) to RLVR and RLHF this.
> I train non-LLM transformer models on (older and rarer) datasets, and automating the ingestion of sprawling datasets with hundreds of columns, often in a variety of local languages and different naming conventions adopted over decades
All of this sounds like basic data processing
Laid off your DBAs I see.
I do enjoy giving the frontier models wacky projects that I can't even find examples of how to do online but I don't expect any results or need them and some have done really well with it while others fall on their face (models)
[0]: Like https://www.oreilly.com/library/view/sql-queries-for/9780134...
Most people have that here in Sweden :)
We still have suicides.
You americans have done a 180 and keep advocating for idk what, socialism? Even though we are not.
> On January 3, 2022, the jury found Holmes guilty on four of the seven counts related to defrauding investors: three counts of wire fraud, and one of conspiracy to commit wire fraud. She was found not guilty on four counts related to defrauding patients
Unfortunately I am very good at forgetting things I resented having to learn, and SQL is definitively one of them.
An eight-join query is going to be nigh on unmaintainable should the requirements change, leading to a change-break-change-break spiral as your preferred coding agent tries to fix its previous fixes.
Maybe the wise way to use AI would be to sort out the schema.
I'd rather get it from the LLM and review
I instructed it to split it up anyway, yet I wonder how often the concerns around the mess are imaginative rather than practical.
The belief in this is a form of AI psychosis, I think.
Maybe in the future but certainly no evidence of this anytime soon
Here's some anecdotal evidence from me - I cleaned up multiple GPT 4.x era vibecoded projects recently with the latest claude model and integrated one of those into a fairly large open source codebase.
This is something AI completely failed at last year.
Maybe you should try something like this or listen to success stories before claiming 'certainly no evidence' in future?
I don't know what happens in a decade when there are no junior engineers, skilled senior engineers are becoming rare, and the only data left the train LLMs on is 200th-generation slop. But AI slop being qualitatively slop is not enough of a obstacle to prevent that future from coming to pass. And billions of dollars will be "saved" along the way.
That's what makes this whole house of cards dangerous. The prescription to psychosis is profitable. Aka, selling a grift.
1) same business logic implemented in two different places, with extra code to sync between them
2) fixing apparently simple bugs results in lots of new code being written
It’s a sign I need to at least temporarily dedicate more effort to overseeing work in that area.
I somewhat agree with the AI psychosis framing of the OP. It takes some taste and discipline to avoid letting things dissolve into complete slop.
What evidence is there that we're not at or close to a plateau of what LLMs are capable of? How do you know the growth rate from 2023 to present will continue into 2029? eg. Is it more training data? More GPUs? What if we're kind of reaching the limits of those things already?
* A belief that AI will keep getting better, presented without evidence, does not yield a lot of skepticism around these parts.
* Your comment saying it is wrong to believe AI will keep getting better, also presented without evidence, is downvoted.
To the wider audience on HN the phrasing is pretty clear. An outsider with a tiny bit or intellectual charity wouldn't come to conclusions like you do.
https://en.wikipedia.org/wiki/Chatbot_psychosis
https://www.rollingstone.com/culture/culture-features/ai-spi...
https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-cha...
The key factor is losing touch with reality, which results in individual or collective harm.
There is also such a thing as mass psychosis, and those are unfortunately a more difficult situation because the government and corporations are generally the ones driving them, and they are culturally normalized.
If he meant mass psychosis, he should have said mass psychosis. And again, since he is not a public health scientist or any flavor of psych professional, he probably shouldn’t make those proclamations. And should probably call for a wellness check instead of posting on social media if he were truly concerned for their health.
For people who are considered neurotypical, social coherence often overwrites reality. Its a mechanism for achieving consensus withing groups while spending the least amount of brain compute energy. Same goes for social metainfo tagged messages, they are more likely to influence reality perception, subconsciously. E.G: If a rich guy says you should be hyped the people who wanna get rich will feel hyped and emotional contagion can spread between people who belong to the same "tribe"
It's very visible for us atypical folk who can't participate well in groupthink at all
I use that example because I have literally seen people fall into delusions of thinking they're God after talking to AI enough. That's shit is scary, for real.
It's just an umbrella term for "weak process glue code".
The infill will look seamless.
And entirely lack any actual strikes of interest - the outliers are exceptional signal and the entire raison d'etre for building such a database.
Jeez, if AI can just infill where the gold is, why even bother to look in the first place.
The original question was
>"clean up" dropped databases, compromised computers or leaked personal data?
For each of those things, you can right now build an agent that handles all of that. Or use a large frontier model with enough context to build code that ensures all of those edge cases are handled.
Future coding will essentially be like this. The concepts of dynamic vs compiled language will shift towards having frontier edge models put together code versus small runtime edge models dynamically processing data.
But as for this
> why is all the money printing remaining in the rich person's realm instead of trickling down?
Always has been, it's kinda one of the defining features of capitalism
I think you may be describing the experience of 6-12 months ago.
I wish I had written that.
Frankly without AI assistance many of these tools just wouldn’t exist at all. We can build stuff in 6 weeks part time as a side project that would have taken at least 3 months full time, and therefore would not have been feasible. Then we can iterate on it at least 2-4 times faster than with hand coding.
So I’d love to have an extra few developers to just work on that stuff full time, but I don’t.
Whether that means our organisation spend on AI overall is a positive, I really can’t say. Quite possibly not, but my team are getting real benefits.
>Amazon workers under pressure to up their AI usage are making up tasks
In my humble opinion good ideas (what to build) are a big part of the bottleneck and those aren’t substantially in greater supply with AI.
There's also an online version of the Library of Babel, I just found out that full pages of my own books are in it[0], https://libraryofbabel.info/bookmark.cgi?379:17
compare 100 pollocks vs 2-3
> The worst part is, even when "prompted" by bad coders, it works in the end. Even has tests (ostensibly mock-ridden, a pet peeve of mine which always falls on deaf ears). So I cannot reject the PR without being an asshole.
Yes, you absolutely can. And you should. Try to teach them lessons and what patterns to watch out for, then tell them to put those insights in their CLAUDE.md, so that their agent becomes better, too. You can also tell them to just copy your own CLAUDE.md, like I did: https://github.com/codethief/ENGINEERING_PRINCIPLES.md
Stay strong!
Talking to him, he told me he couldn’t even reverse a string. He is at once many times more valuable than ever before to his company, but also far more dangerous than ever before.
If you get the logs you can feed them in and ask for improvements, that sometimes helps.
This form of being "smart" is a bit difficult for me to comprehend, I must admit.
I strongly agree with this. Suddenly with the mass adoption of LLMs there are so many smart, yet naive people out there willing to toe the line. Why these smart people couldn't bring value in a million different other ways is, of course, left unsaid.
They're not even trying to dress up these bullshit stories anymore. In truth it doesn't matter if you believe it. So much buzz is people just talking to themselves out loud.
This is a social problem that I had thought the industry had solved a long time ago.
As others have elaborated, the problem is empowering them to ship mountains of bad code;
And yeah, many semi-technical M2s or even M1s can't distinguish bad code from good code, or worse bad architecture from good; this is golden time for those who are willing to sacrifice the future for present. Just burnnn'em tokenzzz.
I would've believed that 6 months ago, but not now.
If you have a good codebase with proper rails, hygiene and architecture, AI will produce better code than most engineers out there.
People forget that 90% of the field has always been charlatans barely able to implement a fizz buzz or go much beyond trial and error googling.
I'll say even more. I'm in the 10%, and it's increasingly clear to me that AI writes in minutes code that's better than mine.
Even stellar and respected OSS engineers are nowadays leveraging AI and guiding it less and less everyday beyond giving indications of what kind of data structure they may want for a complex problem or the kind of architecture they are looking for.
In any case, I don't like this field anymore, I have no joy from it, way too much work, way too many changes a human can cope with both on product and technological level (not even counting AI and its tooling itself). The interesting parts of thinking an entire afternoon or week experimenting to get that design right disassembling the pros and cons are gone.
Even if you want to do that, it's just faster to launch 6/7 worktrees with the different ideas and judge the results. But you don't get as intimate with the problem and the amount of information is way more than you can process.
But I agree with the parent comment in that we shouldn't use the term "AI psychosis" to mean "a value judgment" instead of "a form of psychosis", because "AI psychosis" has already been used for 2.5 years to mean "a form of psychosis".
AI: "I LEARNED IT FROM YOU, DAD!"
This means you take less time reviewing code than it took for the machine to churn it out. All that code must be a ticking time bomb.
This is what I’m seeing, anyways. Junior engineers are being rewarded for shipping so much code, it’s impossible to evaluate it all, and subtle changes in existing patterns are slipping through. Eventually all those subtle changes transform the rails.
Okay, so Ai is completely useless in my industry. Got it.
https://www.joelonsoftware.com/2000/04/06/things-you-should-...
A decade ago, I was sitting in on a meeting about a rewrite and, before I could say anything, someone in the first year of her career asked why anyone thought a rewrite would be any cleaner once all the edge cases were handled. Afterwards, I asked her where she learned this. She said "I don't know, it just seems kind of obvious." She went on to be a great engineer and is now a great manager.
Greenfield guy comes in, promises the world, and starts from some first principles white papered architecture. It's really lovely until they onboard the first user. Then they slowly commit all the "sins" (features that drive revenue) of the first system.
The firm is stuck supporting N systems indefinitely because the perfect new system takes so long to cover even 30% of the original system use cases, that management takes a flier on.. bear with me.. a second rewrite. Now they have 3 systems.
I've seen more 3rd systems than I've seen actual decommissioning of original systems into a single clean new system.
The answer is chipping away, modularizing, and replacing piecemeal Ship of Theseus style. But that does not drive big hires and big promotions.
Do they??
My team lead has worked on the same software for 30 years. He has the ability to hear me discuss a bug I noticed, and then pinpoint not only the likely culprit, but the exact function that's causing it.
There is a lot of absurdly complex software that runs with high reliability. We hear a lot about the ones that don’t.
I have really tried as an "old" person in the field to try and pass on the stuff I've learned, but "craft" and such really has absolutely no home in modern dev culture. The people who care about history, the craft, etc. are increasingly rare.
Henry Ford II: "Walter, how are you going to get those robots to pay your union dues?" Walter Reuther: "Henry, how are you going to get them to buy your cars?"
And for so long, I've had people tell me to just get a job. But I tell them that I don't want a job: I want money and I want something to do. Those two things don't have to be together.
I think this is the hard part: philosophically so many of us have learned we need jobs and don't realize a job can be decomposed into money and something to do.
So I think we need to start looking more creatively at 1) how people receive money from others and 2) how people give services to others.
OTOH replacing people with AI would indeed bring about a huge economic downturn. What would be good is augmenting humans so that they can do 10x more. That would enable things that are hard to imagine exactly now, much like computers enabled interesting transformations in the society from 1980s to 2010s.
The current crop of AI is by construction unable to reach the human level of cognition, but it is quite good at doing some symbolic manipulation tasks. We will get used to that, and will integrate that in our workflows. Humans are still going to be needed.
You have to cut costs when the costs do not bring you enough profits.
Hundreds of billions are changing hands globally, every week, at the retail level alone.
And that happens literally every week, week after week.
That constitutes a massive market in any sense I can think of.
That needs a way more complex explanation than simple gut feeling.
A highly normalized DB can easily end up with 8 joins required for some function. That's really not out of the question. "Sorting out" the schema then would be... denormalization, which is a thing, but you need to know why you're doing it. And I think 8 joins isn't enough of a reason.
As Anthropic's drones say: treat Claude as your genius coworker. Don't think yourself, don't judge, the machine must know better than you. It is the genius, after all, not you.
I guess at a company of seven, if two people are making the executive decisions and the two people are drinking the same AI kool-aid and the other five people are dutifully following these executive decisions, the whole company can be considered to be under this condition.
https://en.wikipedia.org/wiki/Groupthink
Maybe the difference would be the level of absurdity that's accepted
A practice (or a fashion) has more social value to the degree that it is absurd, because it signals the person is able and willing to align with the group at personal cost.
This is easiest to see in some insular religious communities.
Normie culture is quite similar: a vast complex of ever-shifting shibboleths which signal, "I'm one of you. You can trust me."
It signals the person is able and willing to follow the rules, to make themselves predictable, easier to understand and cooperate with.
But if you ever need to query unknown data, then probably you should learn SQL a bit deeper.
Including all of the above.
If in fact you can meet the same market demand with fewer workers and the market does not expand accordingly, you get deflation and job losses.
Which is sad because they should be. People should be freed up to think and create better things, instead these companies seem to be doing the equivalent of locking their employees in stalls like they do on some animal farms, so they can churn out 'results' ever faster.
Good ideas will never ever be prioritized in the vast majority of companies because good ideas cannot be quantified and turned into performance metrics. At least not without invoking Goodhart's law (see: the academia).
Cuba ran out of fuel because we took out their thug partner in Maduro. If they wanted to drop the whole authoritarian communist dictatorship stuff and their involvement in the disaster that became Venezuela and partnering with the Russians then they'll be better off.
Since when is it acceptable to invade another country just for being communist or a dictatorship? Conventionally it's up to the people in those countries to overthrow a dictator. Other countries only get involved if the dictator attacks them (like the USA dictator did).
Do you like being able to buy food?
Food production will decrease, and even moderate increases in food prices mean many people unable to afford enough food.
The world let this disease (IRGC) fester in the region for too long, and now because of that the fix is going to require significant pain. The IRGC in its current form has run its course and will not be allowed to threaten American interests, allied interests (whether that's Israel, UAE, Saudi Arabia, or otherwise), and they will not be permitted to build a nuclear weapon or threaten global trade.
What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
> What's your sales pitch exactly for how that's the best thing for the non-US rest-of-the-world? What's the US's post-WWII track record, success-wise, in regime-change foreign wars, how much would you trust the US on this one?
Honestly not all that bad for the US.
Korea - we stopped the North Koreans from taking over the entire peninsula. It’s China and Russia’s fault that the hell hole we know as North Korea exists today.
Vietnam - unnecessary war, but we won the peace.
Panama - took out Noriega
Desert Storm - stopped Saddam and kicked his thugs out of Iraq.
Serbia and Bosnia - NATO campaign. I’m personally a little unsure if the results were good or not but I understand we collectively stopped a genocide.
Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. Too bad the rest of the world didn’t help. Now we’re seeing a massive regression in women’s rights there.
Iraq - probably not worth the money, but Iraq went from a brutal dictatorship under Saddam to a much more stable and peaceful country with a Parliament.
Venezuela - Took out Maduro with no losses.
Iran - TBD on the long term but we’ve stopped the IRGC buildup and at least bought time to figure out what to do.
The rest of the world stands on the sidelines and complains and complains yet the United States actually has the balls and will to do things. We aren’t perfect, but without US military action or at least the threat the world would be much more dangerous and much worse off. China sure as hell isn’t going to send troops to liberate Kuwait. Europe doesn’t have the military capability to stop Iran from getting nuclear weapons and exerting a stranglehold on a large chunk of global oil supply.
The reason nobody was dumb enough to attack them before is that it's an unwinnable conflict. They don't need a lot to close the Strait of Hormuz, a few guys rolling mines off a beach would do that. And they have a lot more, like missiles and drones to do damage at a distance too.
And it's a regime that has at least a million loyal fanatics ready to fight for it (the Basij, the org that did unarmed meat waves against Iraq to defend the regime). So any invasion is an absurd proposition.
So what, the hope is that the theocratic kleptocracy will give up? Not even a child could be so naive. They literally believe in martyrdom, whacking a few of the top dogs means nothing.
It's like the Kims, nobody can unseat them. Only this is far worse, because Iran has the leverage of Hormuz, and it knows it can wait - because they don't care about the people - while the US and global economy suffer until they fold. Especially with midterm elections coming, the US will fold.
> Especially with midterm elections coming, the US will fold.
These are the kinds of misunderstandings that are disappointing to see. There is no disagreement here amongst the political class. It is political theater for votes. Apparently you’re susceptible to the marketing.
We don’t need to invade Iran. We just keep the Strait closed since we control it and then Iran’s economy simply fails and the worst thing that happens for America is higher prices. But we can handle that.
I don't see why we would assume that we are at a plateau for RL. In many other settings, Go for instance, RL continues to scale until you reach compute limits. Some things are more easily RL'd than others, but ultimately this largely unlocks data. We are not yet compute/energy/physical world constrained. I think you would start observing clear changes in the world around you before that becomes a true bottleneck. Regardless, currently the vast majority of compute is used for inference not training so the compute overhang is large.
Assuming that we plateau at {insert current moment} seems wishful and I've already had this conversation any number of times on this exact forum at every level of capability [3.5, 4, o1, o3, 4.6/5.5, mythos] from Nov 2022 onwards.
The (leading) LLMs work by consensus, like Wikipedia, Openstreetmap, web search engine or opensource movement.
What I mean is if I ask LLM "create a linked list", its understanding (of what I want) is already close to the expected ideal. Just like Wikipedia article on linked list, for example.
But the LLMs will continue to improve in breath and depth of understanding the world, although technically (what they CAN do) they probably already peaked. Similarly, OSS movement technically peaked in the 90s with the creation of compiler, operating system and a database; doesn't mean that new opensource isn't being created.
LLMs (or specifically GPT algorithm) are 8 years old. It has matured as a technology. I am not sure how you imagine it being significantly improved, from a user point of view, without some kind of paradigm shift (i.e. something significantly different from GPT or LLM).
Although I can imagine one important social innovation yet to come - a generally available big public LLM, that "anybody can train". We had a technology of "encyclopedia" for years (famously Brittanica); yet the concept of Wikipedia has been a truly new take on encyclopedia.
Also, new kinds of AI might emerge - for example we might formalize all types of human reasoning and build a reasoning AI, as well a model of human language, from scratch rather by training via GPT (and thus, more understandable and potentially smaller). But that won't be an LLM.
And the answer appears to be that the improvement is accelerating. So how could it be stopping?
I don’t think that the current AI paradigm has infinite headroom for improvement, similar to how every other AI approach before it eventually hit a limit.
And the link I posted shows the amount of work a query can do increasing non linearly. You can explore the site for more detail and a graph that shows error rates getting halved every couple of months.
No one said anything about infinite. It doesn't mean we don't have headroom to spare.
Software itself took 80-120 years to get where it is today depending on how you count. Time is on AIs side here.
Nobody cares that you want money and you want something to do that you enjoy. Nobody ever will.
If you actually dig into all the social programs that exist at least in the US, they’re just a massive payday for a small group of people under the guise of bettering humanity.
College/education is a fantastic example. Education as it has been established today is a joke. The humanities were originally established for rich bored wives to have something to do. They were never meant to create value. Colleges hang anvils around the necks of naive children via loans telling them “yes if you major in history you’ll have a job!” This is a joke, and a bad one.
Huxley was on to something. If everyone is educated, nobody collects trash, or chops lumber, mines minerals and metals, etc. it’s a big fucking not-talked-about open secret.
Nobody cares, either you bring something to the table someone else can exploit for money, or you lean into “I’m helpless and the government owes it to me to take care of me because I’ve been indoctrinated into learned helplessness.”
“AI” will at best lead to anarchy at this point, if all the grand visions of the billionaires comes to fruition. People have already tried to kill sama and burn his house down. Wait until armed humvees are driving around data centers. It’s coming.
So when we talk of people doing labor for money, we are assuming they can only own their body and receive money from that?
you may not like the fact the fat capital owner may not be lifting a finger, but they certaintly aren't getting a free lunch.
Such is the burden America must face, unfortunately. If we do nothing then Iran builds more and more missiles and a nuclear bomb and then they close the Strait and there’s nothing we can do about it. Then we get asked “why did America let this happen?”. Same with Ukraine. Sure let’s but out of other people’s business… only to get asked why we are abandoning Europe or whatever.
Secondarily, it’s plenty acceptable all the time. In the case of Iran I think it’s justifiable simply on the merits of them providing help to Russia in its unacceptable invasion of Ukraine. Never mind the strategic concerns I’ve mentioned, that Iran murdered over 30,000 of its own citizens, and spreads conflict and devastation throughout the region via proxy groups and other methods. Take out Iran and we are pretty much left with peaceful countries remaining.
And with one you need to train a guy for 25 years and with the other you need plan mode for a few minutes and then it runs 24/7.
The political class answers, in a way, to the population. The American population is extremely sensitive to the price they get at the gas station (because of the complete lack of alternatives in driving in most places, and the average car having bad fuel economy). If by election time the prices are the same, the ruling party will get punished. And the ruling party doesn't want that.
The only thing capital owners risk is losing it and becoming a worker.
So I don't think it's a free lunch, it's more risk-for-lunch than labor-for-lunch. Maybe you could argue laborers are still risking their body or something, but I think the point might stand.
I’m a backend developer so I know what it takes to build a half decent reporting system. Writing all those queries, slice and dice charts and what not takes real time and effort. All that has been outsourced to Claude Code. I now focus on ensuring that the system is sound architecturally and that useful reports are being surfaced.
My experience so far is that it's harder and slower for me to understand the genAI code than to write it myself.
Skipping thorough comprehension seems to be the popular choice in my workplace, but it's not one I can justify.
I guess just like any algorithm it’s easier to verify a solution than come up with one.
Have you read the code the AI produced? Do you understand all of it? Is it bloated? Would you be proud to say you wrote it?
I don't care how fast you created something. You didn't create it, the AI did, and you have no control over it, the AI does.
It's clear HN is a bastion of salesmen who happen to have "engineer" in their work title. But the mentality towards actual engineering makes it clear they are primarily salesmen.
That is absurd, these are tools only my own team use. Why would I not care whether I had them in a month or two, or fur many of these tools quite possibly never because we don’t have the spare capacity for how long it would take without AI?
But what I find fascinating is how the groupthink mechanism alters the subjective reality of people.
Lies or fantasy becomes reality if the entire group believes it and people truly believe the collectively accepted things to be real.
It just makes me think about consciousness overall or the lack of it, because all these things are mainly governed by subconscious mechanisms in the brain.
We are not the same when it comes to levels of consciousness and if the group mechanism demands less of it, people have no conscious choice about it
Of course nothing is black and white
Do they think out loud : "Now I should shut up because x"
Or is it an instinct they have after looking at others?
The more you can trace reasoning the more conscious, but the moment there is something created implicitly like an emotion or instinct then it's initiated by an automated subconscious response.
A large percentage of communication is non-verbal (emitted and processed subconsciously) so eye contact, micro expressions, gestures and body language play a large part in group communication.
but if you ask somebody after they exited the groupthink state they will not say they did it out of fear.
They often say: "it just happened"
Why were you behaving like that?
"We just did"
Inability to explain reasoning points to subconscious mechanisms.
It's deeply built into humans to groupthink.
I proposed how. New harness techniques and new training data/techniques, so the harness gets better and the LLM can be trained to work better with the harness. There's no reason to believe we're out of momentum for improvement in that direction.
However, they also make mistakes like humans, I don't think a better harness or better training will fix that, because fundamentally, they cannot read your mind, if you put in an ambiguous prompt.
I like to compare the process of turning inexact text to formal language to an error-correcting code. If you haven't made too much mistakes or have been precise in the specification, it will self-correct and do what you want. But if your input is too ambiguous, it will never do exactly what you want, but something close to it. And people (who are using AI) are still learning where is the boundary and how to tell.
The companies building these models are training them to react to typical expectations. If you have some special need, you will always have to tell the model, otherwise it will not know your exact context. And the harnesses have many tools for that or try to do that automatically already.
> Vietnam - unnecessary war, but we won the peace
> Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. *Too bad the rest of the world didn’t help.* Now we’re seeing a massive regression in women’s rights there.
> At its peak between 2010 and 2012, ISAF had 400 military bases throughout Afghanistan (compared to 300 for the ANSF) and roughly 130,000 troops.[7] Forty-two countries contributed troops to ISAF, including all 30 members of NATO.
Are you unfamiliar with the term? In the case of Vietnam we “lost” the war, yet today we have pretty strong and good relations with Vietnam. Hence we won the peace.
> Why are you lying about this?
I have a different perspective, but that doesn’t mean I’m lying.
Of course many countries contributed in various ways to Afghanistan, and as a former member of US military I have incredible respect for our friends and allies and still do today. But at the end of the day the vast majority of the manpower, cost, and equipment was American and the country could not be won solely on military power alone and needed much more support diplomatically, politically, economically, and in terms of aid.
The other problem with your argument is if you claim that Afghanistan was an American failure it contradicts your assertion and instead everyone failed, except that the US contributed the most. You can’t have it both ways.
> Korea - we stopped the North Koreans from taking over the entire peninsula. It’s China and Russia’s fault that the hell hole we know as North Korea exists today.
The regime still existed, and wasn't prevented by that restriction from nuke/missile development like you are so worried about in Iran. "It's other countries fault" isn't an excuse here, it's something that should be taken into consideration more generally in advance.
> Vietnam - unnecessary war, but we won the peace.
But no regime change accomplished with the war itself, yes?
> Desert Storm - stopped Saddam and kicked his thugs out of Iraq.
I think you mean "kicked his thugs out of Kuwait". And let's keep that in mind: a defensive operation worked well.
> Serbia and Bosnia - NATO campaign. I’m personally a little unsure if the results were good or not but I understand we collectively stopped a genocide.
I don't really think this qualifies as "regime change" vs intervention campaign in a "traditional" existing conflict?
> Afghanistan - we tried our best and made some mistakes along the way. Eventually got Bin Laden though. Too bad the rest of the world didn’t help. Now we’re seeing a massive regression in women’s rights there.
"Got Bin Laden" isn't a regime change, and now obviously the regime is not good. What was the rest of the world supposed to do to make it better? Occupy every square mile of the country with soldiers for a couple generations?
And then this one:
> Iraq - probably not worth the money, but Iraq went from a brutal dictatorship under Saddam to a much more stable and peaceful country with a Parliament.
There's no face of a dictator like Saddam anymore but I think "stable and peaceful" oversells it. But yeah, this is the most direct not-yet-imploded regime change in the area on the list.
Notably left off your list regime-change-wise here is Iran in the 50s. That one seems to have backfired. (And that's a great example of why Venezuela, Afghanistan, this-iteration of Iran, even Iraq all are still open-books with potential unforeseen consequences left to come.) The biggest direct threat to date from the Middle East to the US itself hasn't been from nation states, it's been terror groups that have festered post-intervention attempts.
The calculus for this attack on Iran assumes that they were going to escalate imminently in a new, more direct, way and that it would directly threaten the US itself; both of these seem a bit far-fetched after decades of the status quo. It's also an area where the US seems to not have much credibility because there was that whole less-than-a-year-ago "we knocked back the nuclear program" post-bombing claim.
And in particular:
> we aren’t going to let Iran obtain a nuclear weapon or build up such a missile and drone stockpile that they could then threaten and attack their Gulf neighbors and implement restrictions maritime trade, which they were likely to do
seems like that actually did happen, and maritime trade is already impacted? Seems a bit silly to say "the US must act to prevent the very thing that the action will provoke."
No it’s not silly. It’s called a preemptive action. It’s a very well understood concept. In the case of Iran it’s very straight forward. We could do nothing and then in a few years they just say hey the Strait is now closed, pay us, and then there isn’t anything anyone can do about it. We can disagree on the likelihood but I think it’s dishonest, as many pro-IRGC folks like to do, to suggest that it wasn’t a possibility, certainly a strong one, that Iran was moving in that direction.
Why is it that Iran, after all the US has tried to do (US because nobody else has any ability to do anything) that they need special treatment and to hold the world hostage else they get to develop nuclear weapons? I don’t think Iran or more countries in general having nuclear weapons is a good thing. Do you?
> You listed 9 things, 2 are far too recent to evaluate, and of the remaining 7 these 5 are regime-change failures (or simply not-regime-change-attempts):
Sure, what list of regime change operations do you want to use? Happy to discuss any of them. But at the same time you can’t simultaneously criticize American action here as being ineffective and then also say for other operations that “You listed 9 things, 2 are far too recent to evaluate”.
> The biggest direct threat to date from the Middle East to the US itself hasn't been from nation states, it's been terror groups that have festered post-intervention attempts.
Currently sponsored by Iran. Why don’t they just stop?
Is it lost on you that nobody in America gives the slightest shit about Iran except that they keep funding terrorists and killing people, selling drones and helping Russia murder Ukrainians, killing 30,000+ of their own people who were peacefully protesting, and constantly trying to build a nuclear weapon? If they just stop doing these things, which are unique to Iran, mind you, then none of this needs to happen.
> Notably left off your list regime-change-wise here is Iran in the 50s. That one seems to have backfired. (And that's a great example of why Venezuela, Afghanistan, this-iteration of Iran, even Iraq all are still open-books with potential unforeseen consequences left to come.)
Not a great point because, well, the world is always changing.
> The regime still existed, and wasn't prevented by that restriction from nuke/missile development like you are so worried about in Iran.
And the world is worse off for it. Millions of North Koreans are living in one of the most brutal and inhumane dictatorships to ever exist. Them obtaining nuclear weapons isn’t a model to follow.
> "It's other countries fault" isn't an excuse here, it's something that should be taken into consideration more generally in advance.
It’s not an excuse it’s just the fact of the matter. Communist governments in China and Russia are responsible for North Korea. We should prevent more such countries from coming in to existence if we can.
Alternatively, I’m fine being an isolationist. It’s a lot cheaper and everyone else can just worry about all this stuff instead. There is no in between. You get the US involvement and the good that it does, or you get isolationism. You don’t ever get “America only takes international actions that I agree with”. Impossible standard. Which do you want? I’m happy to lift sanctions on Russia and Iran and North Korea and everyone else, withdraw the US military, and leave everyone else to fend for themselves militarily unless we have an interest we want to pursue. It’s a valid enough strategy.
Because you're thinking like a salesman. What difference does a month make for a supportive tool without financial incentive? Why can't you justify a month of development without the idea of corporate breathing down you neck?
And the equivalent for software. It’s usable, intuitive, responsive, stats up and running, and doesn’t leak my private data.
Then the only "experts" (not even close, just a guy with a form and some technical training) are the building inspectors who come at the end to verify if some stuff is done up to code.
Other than the original architect who draw the plans that got used for many buildings and the electrical engineer that cleared the electrical, no experts were involved. This is basically how the whole city and most of the country was built.
There's no expert mason or painter or whatever involved. Just a dude that can hold a paint roller. That's the same as going from a craftsman programmer to some dude with claude. Individual quality goes down, but more importantly price goes down way more and so many more people get access to much better quality than having nothing.
You paint the economic model as a false dichotomy, and the main point of my posting was that it is not a false dichotomy. It is not either have a job (and be exploited by someone else) or be helpless and rely on government handouts.
For example, what if people who got laid off from companies were given significant stock in the company, so that they might partake in the potential savings and gains from replacing the workers with AI or other tools?
The whole conversation seemed to be about the economic model, so I'm not sure how it is a distraction, a boogeyman, or inconsequential.
You have described less than 0.1% of the US population, not to mention the rest of the world.
I get it, you have an idea in your head and you're struggling to see past it. Read Brave New World.
Fair, my one example on layoffs may not land with you.
But do you want us to just sink into the helplessness of us all being screwed or do you want to try to find solutions that might allow us to feel some sense of agency and hope?