You can see from this megathread, currently on the front page, that HN is by no means anti-AI:

Ask HN: What was your "oh shit" moment with GenAI? - https://qqrl.tk/item?id=48406174.

Sometimes it just takes the right initial condition (e.g. title) to bring out one side or other.

As for why the community is divided, there's always a temptation to come up with HN-specific explanations, but society as a whole is divided about AI. Surely that is the only explanation one needs. As I've been saying for years, HN can't be immune from macro trends: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

I can speak from myself as an example (although n=1): I am incredibly open to machine learning and the advances it brings. On the other hand I am extremely conscious of the fact that the current LLMs do often write bad code, which becomes especially obvious once projects go much beyond "private toy" size. For me personally the consequence is that I try to make my projects even more modular, and the modules even more clearly delineated. With proper guidance, current LLMs work mostly fine when working on isolated modules. That doesn't mean they don't sometimes fail even there, but they also on rare occasions come up with surprisingly clever solutions when you let them loose on a code base, as long as the problem you want them to fix is mostly isolated in a couple of modules.

So long story short, you can be all for LLMs and still be conscious of their shortcomings, and that just vibe coding applications you intend to let loose on unsuspecting customers is probably a bad idea, and possibly outright immoral. We have already seen more than enough examples of vibe coded applications dumping sensitive user data into the lap of anyone who is inclined to pick up a stick and prod them a little bit.

Fixing my furnace: https://qqrl.tk/item?id=48417845

New software for a retro keyboard: https://qqrl.tk/item?id=48418158

Customizing my camper van: https://qqrl.tk/item?id=48417379

Porting my astronomy app from an old Nokia phone: https://qqrl.tk/item?id=48419242

Fixing my kid’s science fair project: https://qqrl.tk/item?id=48419364

Unborking the family printer: https://qqrl.tk/item?id=48419480

Learning to draw anatomy (!): https://qqrl.tk/item?id=48418716

Lowering my electrical bill: https://qqrl.tk/item?id=48417949

Making classic guitar pedals programmable: https://qqrl.tk/item?id=48418006

Avocado armchair guy victory lap: https://qqrl.tk/item?id=48417658 (<-- oops, wrong: https://qqrl.tk/item?id=48418274)

Putting an overlay on enemies in a video game: https://qqrl.tk/item?id=48420635

It just goes on and on. I was a little nervous when I saw that post originally, but it's amazing what happens when a title is somehow just right.

Jokes aside, thanks for your selection. I had read some, but missed others until your comment.

If it matters, I think there's some people that hasn't decided yet what tribe (pro-AI/anti-AI) they belong to. There's probably dozens of us!

There is a really important question that is been lost between the anti and pro AI camps which is really answering what AI is good at and what AI is bad at, and what is the root cause of the weaknesses. Is it intrinsic to the models that LLM's use, or the way thy have been trained. In this knowledge is where the gold mine is for the next start up.

For example AI is very good at answering well defined questions, but suffers from premature closure. It will not know if it has all the information to answer the question. So whilst AI will score better than a doctor or a lawyer on a domain question it will not necessarily gather all the evidence needed to answer the question properly. Knowing this whilst using a LLM is a super power.

There is also a large gap Usability issue in that often the LLM does not really know the humans context, in other words a context collapse. It does not know if you specilised in your domain or just asking for fun.

We should be exploring and debating these gaps.

I think some of this pro/anti AI discussion is really a proxy for something else though. There is another unstated, societal disagreement about personal responsibility and the behaviors of the AI tool users.

It isn't entirely new, as people have always been blaming abstractions which lack agency (society, bureaucracy, "the machine", "the process", "the game", etc.) to conduct themselves in an ethically or logically flawed manner and then shirk responsibility. But, I think it is accelerating dramatically with the way AI agent usage is being adopted. I don't see how this can possibly continue to be normalized without leading to a catastrophic outcome.

Right now, AI tool usage is being applied in ways that would have been considered misconduct, negligence, or fraud if the actors were doing the same thing via traditional outsourcing. People who have a contractual and ethical responsibility to apply analysis, judgement, and oversight are rapidly turning into dumb pipes who just relay content. They essentially phone it in, trying to take credit for apparently moving KPIs "up and to the right". They pretend to themselves and others that they are reviewers and still in control, but when things go wrong they expect forgiveness and for others to lean in and clean up their rapidly spreading mess.

In software circles, many of us are appalled by this slop that is poisoning the well for our existing organizations. It seems like a massive, toxic externality. To us, people aiming their AI agents into our existing collaborations are pretty much flipping a switch to "roll coal", or worse.

My next project was a 2d game with random terrain, physics, sound, music, multiple levels, a day/night cycle with transitions high score tracking... (not uploaded anywhere, but it works, and I refined it a good bit.). That was more like 8 hours and maybe a 100 prompts.

Here are a few screenshots:

https://imgur.com/a/vhUXBu3

One thing that I have found to make a pretty big difference is using both the latest models and higher thinking levels. Opus 4.8 with thinking on Extra or even Max is genuinely mind blowing. The thing I hadn't really appreciated, having a sort of naive impression formed mainly from using free early versions of stuff like ChatGPT and Stable Diffusion was sort of that "Type a big ass prompt and it craps out a result" experience. But Claude is really great at refining from feedback, and it's way more flexible and responsive than I would have ever expected. I can do something like take a screenshot of a small portion of the running app or website or whatever and just say "This button needs to be bigger" or "make this red" or something like that, or even sometimes just "fix this", and Claude both correctly identifies what I'm talking about, and actually does the thing.

here I've found it really, incredibly game changing is my health. I have a pretty, to put it mildly, complex medical profile at this point. I haven't worked in over a year and pretty much every sign is pointing towards permanent disability at this point. Tons of symptoms, long med list, and I live in a smaller town with not great access to care. I'm also autistic and have not the greatest verbal communication, especially under stress or time pressure. I dumped all my info at it, in bits and bobs over several days (Side note... it's memory is pretty limited, but it will quite happily right out everything it knows from a session into a markdown file it can later re-read. I've found it very good for things like screening for drug interactions, or talking through and logging symptoms (and it can log those into human readable markdown files too). Biggest win (other than having unlimited time and interactions) is that it thinks across specilaties, versus the "real world" where the gastro only wants to deal with gastro stuff, neurology only wants to do neuro.

I certainly don't (and wouldn't) use it as a replacement for a doctor, but as an adjunct it's phenomenal. For instance, it flagged a possible drug interaction with a symptom I was having, and then offered to draft a portal message to my GP about it. I have poor executive function so lowering the friction from "type up a message and send it" to "copy and paste" is actually a pretty big deal. Turns something (I probably won't do) later into something I will do now.

It wouldn't surprise me if my very direct, literal, autistic communication style is particularly well suited to interacting with AI. I actually find talking to it rather refreshing as, while of course it's not perfect, it tends to actually respond to what I say rather than the all the assumed subtext NTs tend to expect/react to.

The AI discussion on HN is exhilarated by the fact that it can have a tangible impact on people's lives on this forum. You add to this the possibility of a minority extracting an unfathomable amount of wealth from the hype train and we lose all hope for a moderate discussion.

My own views on this are rather boring. After having tried various models, I've reached the conclusion that it adds minor benefits to my workflows, but I don't have to lose sleep from Claude reaching singularity anytime soon..

I did see your thread earlier today and I admit was pleasantly surprised. Maybe HN is turning over a new leaf? I hope so. I honestly considered switching to X it was getting so bad :P

Was it universally obvious? Hindaight is 20/20 There were many block-chain startups funded, and even FAANG got caught up in the hype. FWIW, I was a crypto sceptic, but I had many arguments with believers online and in my social circles. Side note: a crypto enthusiast colleague bought a house off their crypto gains, it may be a grift, but a small number of crypto-believwrs got really wealthy, and you're not going to convince them.

Yes. Crypto was never productive.

But nice that your buddy financed a house with other people's dumb money.

In fact as the act of paying itself has become more restricted, it's often also a good way to make illegal payments for completely legal goods and services.

I know others also do this - though often they are kind enough to auto-fold.

I think this would be a very useful feature to add to HN itself. I nearly emailed dang a few weeks ago to suggest it myself rather than roll my own browser extension to do it, though maybe it's my own responsibility to roll my own software too.

The Gearspace forums (vBulletin based?) have an "Ignore User" feature that helps make that forum vastly more tolerable.

The interesting question is, if it's so consistent, how can it go unnoticed for a long time (as you've reported) and/or get perceived as one-sided ("HN is so anti-A!") when in fact it is almost always two-sided ("HN users are divided on A")?

There's a clear answer to this: what you notice depends on how you feel. If you like A, or (more precisely) dislike anti-A, you are far more likely to notice anti-A posts. Not only that, but they will make a stronger impression on you than the median post—even the median pro-A post! [2]

These two factors—frequency of impression and impact of impression—combine to create a strong picture of the site as anti-A—so strong that people commonly use universals like "always" and "never" and "absolutely" when describing it. In reality, HN is a statistical cloud of datapoints and your pre-existing feelings are what determines which datapoints you notice (i.e. frequency) and how strongly you weight them (i.e. impact). [3]

This is why people with strongly opposing views (A vs. B) feel the same about how biased HN is, just in opposite directions! i.e. with the A team convinced there's a strong anti-A bias and the B team equally convinced there's a strong anti-B bias. It's simply (<-- that word again) that their feelings cause them to notice quite different subsets of the available datapoints. Abstract out the directional bit (pro- or anti-A), and their comments become isomorphic.

Unfortunately for us, HN is more afflicted by this phenomenon than other sites because we have no mechanism for users to arrange themselves into silos, i.e. equivalence classes of users with similar views and tastes, [editing - bear with me...]

[1] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

[2] Lots of past explanation here if anyone wants it: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que....

[3] I don't mean "you" personally, of course—everyone does it! It's a double whammy of https://en.wikipedia.org/wiki/Negativity_bias and https://en.wikipedia.org/wiki/Clustering_illusion, sometimes described in this way: https://en.wikipedia.org/wiki/Hostile_media_effect.

If LLMs were truly able to replace me, I'd be disappointed, sure - I've spent 30 years developing mastery of a craft, it's sad to see it go. But I'd resign myself and move on.

But that's not what makes me mad.

I get angry because I simply don't believe it is true. I have a reasonable math and tech background to where I grok how this stuff works at a fundamental level, and I'm utterly unconvinced that it is performing any sort of reasoning.

Call it a stochastic parrot, a token extrusion machine, whatever, but these things are not thinking or reasoning.

That doesn't mean they aren't useful- they clearly are very useful for many tasks.

My anger comes from the global attempt to replace things that require human reasoning with LLMs.

There's this push to use this stuff way past the point of "helpful accelerator" to "why do we need programmers/doctors/lawyers/etc..."

I think it's incredibly dangerous.

So while the tool is useful, I don't think we've figured out how to use it appropriately. For all the short term appearance of productivity boost it provides (whether this is real in a total-cost sense is still an active question), I think the risks to skill development and quality outweigh those benefits in many cases, and are being overlooked.

More seriously, I think this is a true reflection of a cultural phenomena. All discussions have become more polarized. There is a more of a generational divide in perception and discussion. I would also say there is a loss of nuance.

To complicate this even further there is a real diversity of experiences depending on many factors.

I mean we had flame wars on USENET but somehow it feels to me that most discourse even on controversial topics was civil. When we had tabs vs. spaces flamewars (or whatever the fun topic of the day was) everyone knew they were in a flame war (and often acknowledged that). Or maybe I'm just being nostalgic/biased.

I see the anti-AI sentiments in my work place. I think people are genuinely worried/concerned and don't know how this is going to change our world or even where we are exactly. This is also spilling into adjacent areas where people have strong emotional responses to (the rich, the economy, job market, politics, environment etc.).

The youth are facing an enormous employment crisis. Many have found themselves completely unemployable through no fault of their own.

And then AI leaders go around to commencement speeches to rub it in.

There's no loss of nuance, the situation has just escalated a lot.

That you fail to understand why those students took such great offense to what was said at those speeches doesn't make it "anti-AI bias".

Those students reacted like that, and I used it as an example, because it's very emblematic of how tech companies and leading figures act.

https://en.wikipedia.org/wiki/National_Security_Commission_o...

Pretending he's some AI nobody is a bit goofy.

Forums like this, reddit, X, readers of news sites etc tend to be filled with people that don’t have much going on in their lives, have a lot of free time to comment, are less likely to exploit the benefits of AI, and more likely to have simpler skills sets that are replaceable with AI.

Talking to people in real world, I would say the overwhelming majority are excited by AI and interesting in using it more rather than less.

Do those people not deserve to be able to live and survive or are they all just replaceable?

I’m happy that my friend who works in plastics manufacturing can move his monstrosity of an Excel spreadsheet to something more predictable and maintainable. I’m deeply annoyed by my coworker who’s trying to put a chatbot in our UI.

But also, the algorithms push enragement equals engagement and that favors pushing content to the product (us) that enrages the product to drive up their engagement numbers so they click on more ads.

Meanwhile, the medical applications of AI alone are astounding. But that doesn't get people mad so it doesn't get promoted as near as much as the latest clueless word salad from a rich dude. Election season is going be to very interesting this year IMO.

https://erictopol.substack.com/p/the-paradox-of-medical-ai-i...

You might have seen some comments by me receiving votes lately that some might classify as anti-AI. I'm not for banning it, I use it at work and at home, I learn about it.

Here a few positions I hold, for example:

- There is a fundamental deviation between what we should be seeing if we were surrounded by 100x enabled engineers and reality. We're not seeing previously untackable, complete open source projects pop up everywhere like someone coding an open-source, iphone-compatible OS in a year, or companies providing 10x more. Just POCs and small apps. LLMs have been around enough that this is pointing towards inflated claims of success, even if they are actually useful, which I'm not denying.

- LLMs provide users with a strong psychological reward (making mental workload disappear). They do so only sometimes, in a chance-based outcome. Anyone with a passing interest in psychology should realize how similar that is to the mechanics of gambling, and thus how risky it is that a user misjudges when it is reasonable to use them. Mind that I'm not saying that the tool isn't worth it, just pointing at a source of major deviation between perceived and actual outcomes that few people consider.

- There are a lot of signals that humans rely on that are broken by LLMs. "Well formatted text -> text written with careful consideration" no longer works. "Large document -> significant effort" does not hold. "Good grammar -> educated speaker" is broken as well. "decent code practices -> the PR is safeish to approve" no longer true. Some of these barriers being broken can be enablers for people, but on the whole this is going to disrupt society in fundamental and unpredictable ways.

- I think the industry is drawing unreasonable and dangerous conclusions from the advent of AI. As some commenters pointed out, if code generation is now cheap we should be seeing engineers freed to deal with non coding tasks like automated QA, user research, architecture or design, and being more able to handle bug resolution for example. We are instead seeing a push for _creating code faster_, and proposing ignoring tasks like review and quality control in pursue of speed, which is fundamentally inconsistent with speed being less of a problem. To use a flawed analogy, if your car is now 10x as fast you should be putting way more attention to how you steer, rather than asking everyone to go pedal to the metal.

- LLMs products have the potential to be extremely user hostile if enshittified. We could have probabilistic insertion of promoted material. We could have subtle political steering of people. We could have a model's performance reduced without much SLA recourse. We are not tackling those issues before they appear when it is obvious that they will appeare, and society will pay the price.

If you read with attention you'll see that no point of mine is arguing against AI usage. I don't want to bury my head in the sand and pretend LLM's don't exist or are useless. I don't want to ban them. I'm just not willing to fully allign with marketing speech and turn my brain off.

Tbf I think this is probably the way most people see it at the moment from my discussions with others.

The static comes from people who have essentially staked their entire reputation on AI one way or another.

I expect the people in here to be domain experts, understand simple concepts like closed loop water cooling, deterministic vs non-deterministic systems, maybe some basic concept of how a GPU and vector math works and most notably the exponential pace that it’s becoming both more capable and more efficient.

Unfortunately, like OP that’s not the case and it’s the same talking points I could read in my local paper. Then everyone’s talking points change in unison like they are waiting on the latest instructions from headquarters.

1. Comments should be thoughtful even if not coming from a place of expertise

2. Better comments have something useful to share behind the passion

3. "Me too" comments are usually not as interesting to read and rarely add to the discussion

I have personally been both praised and attacked for making detailed, reasoned comments. It's more about the mood and attitude of the reader(s) that determines which way it goes.

AI is a complicated issue because it is creating change very quickly--as many predicted it would 20-30 years ago--and that change is still accelerating.

In your words, the change is exponential--and this may indeed be demonstrated by the performance data over the past several years. It's hard to contemplate or predict when that change will plateau, but we definitely aren't there yet.

The ultimate impact on the world society is likely to be profound. Whether you like it or hate it, it is happening. Those who lose a job to AI may find that their mother is saved by a medicine or doctor aided by AI. It's complicated.

Perhaps there are ways to legislate compromises into its use or expansion in some parts of the world--but it is likely a technology that has at least as much positive potential for humanity as it does negative--so legislation is going to have to address the good and the bad and no country is an island unto itself.

Thanks for the opportunity to comment.

"Exponential" is very clearly not true.

  "Content about AI and LLMs are considered off-topic with the sole exclusion of deeply technical content about implementation."

Typically there's a lot of acknowledgement that problems are coming rapidly, if only in the form of amateurs flooding the domain, but there's also an assumption that their domain knowledge is going to matter, in terms of staying viable in the market. This is far from a safe assumption.

Even if you assume you are ONLY needing to sell products or services to humans, also assuming that humans will continue to thrive and spend money, you're assuming people will be able to identify superior products you assume you can produce and market, and that they won't be misled by false advertising, at scale, generated by other AI to optimize its effectiveness.

If you instead assume the domain experts are going to need to sell to AIs (either as owners of wealth and power, or as the agents of the humans we're assuming will still thrive and spend money) you're making a hell of a big assumption that the agents will be trustworthy market participants with perfect information able to evaluate stuff in the best traditions of market capitalism. Humans don't manage that, even when they're a lot smarter. If this assumption fails, all the money goes to whatever exploits the AI agents most effectively, also at scale. At that stage there is no use being a domain expert in anything but hacking people's AI agents to trick or puppet the agents to do your bidding. Anything else is wasted effort.

Sometimes I also see pushback along the lines of programmers criticizing the quality of the AI coding itself. This is gonna be domain-dependent and it's fair to counter it through developing less fragile languages, but we don't know that'll work as an answer. There's a lot of handwaving.

I'm pretty sure people's experience of AI, as a rule, is the bad, damaging forms, where it's burning stupid amounts of energy to make everything worse while openly promising to take away everyone's ability to work and replacing it with the need to pay the AI owners a sort of extra tax just to be able to exist and think. The HN crowd is WILDLY pro-AI compared to the general population.

It's not going to look any better in future for the general population. What I've described leads to 'AI' increasingly producing shockingly bad outcomes for people in general, through simple market dynamics. It's going to be way more profitable to produce the bad outcomes.

Edit: scratch that - I was going to link you to https://qqrl.tk/item?id=46018271 but it turns out you were the user I was replying to there! I don't suppose repeating it would help.

I could never, as an individual read, let alone synthesize and make decisions with, the amount of information on the internet. The LLM takes that free and open information and feeds me back novel information based on that free information. It gives me ideas, opinions, and hard data based on that information.

It's the most powerful information synthesizing tool in existence. I don't find the argument that "it's built on free information and sold to you" fair or plausible at all.

It's like saying you're free to make your own bottled water. Technically true, but in reality not.

I think AI is a convenient foil to get people whipped up and out to vote, but I know HN is not the forum for that. The technical data clearly says that closed-loop water coolers don't use that much water and energy use is a function of a counties energy infrastructure choices not the existence of demand.

But instead we're going straight to destruction of planet as the exact verbiage, which seems way out of whack.

[1]: https://www.wri.org/insights/4-charts-explain-greenhouse-gas...

Maybe in 2023, but what about now?

We could triple the data centers since 2023 and run them all on coal or natural gas and then maybe they’d even show up as a significant slice on these pie charts.

Our bubbles have blinded us to the scale of the real problem.

I'm assuming it would be under the Energy emissions category, but I didn't find anything particular around data centers or "technology" or "internet" or something like that.

Would it fall under "Electricity and heat"? Or just general "Buildings"? or "Commercial buildings"? Or am I way off base?

Only accessible via proprietary ISPs that require a subscription, actively monitor and censor (pirate sites). And managed by ICANN which is based in America (and though nonprofit, certainly influenced by money and government).

Meanwhile, local models package a large part of the past internet, can be stored in your computer and accessed by the most ignorant (but literate) laymen.

Guy who just retired his use of “stochastic parrot” because he found something even more bizarre and pretentious to say.

Deepseek v4 flash is by any means comparable to SOTA from 6 months ago. It's more than good enough for AI-assisted coding and there are no reasons to believe that one year from now or so, they won't be even better and faster.

It’s my personal opinion and it looks extremely incurious analysis of what’s going on. Even if a person doesn’t like AI, I would expect a curious person to have more deep opinions. “Non deterministic database” clearly tells me this.

There’s not a single coherent critique but just throwing some polemic to see what sticks.

Anti-AI sentiment absolutely and correctly has a "USA bad" steak.

because it's true

> Users don’t care whether the code was written by AI or by hand, or which framework you used. They care that the product works.

How can you guarantee that it works though? You can verify, but it would be at the same speed as before the AI, or even slower.

> By then, enough real-world feedback would have surfaced to identify the major issues, and tools like Claude Code would make it possible to fix and ship version 2.0 at an incredible pace.

By then you have a blackbox of a codebase which is unmaintainable, or in a worst case scenario you end up losing your data or get hacked or both.

No, it’s not just one vendor.

- One crowd is using to research algorithms, libraries, write boilerplate code, write test harnesses, introspect and integrate with APIs, do hands-off refactoring, and automating what would otherwise be boring tasks. They still think about architecture, best practices, understanding things in detail and the general shape of the solution is in their hands.

- Another crowd is curating prompts, setting up autonomous agents, creating tooling and guardrails around it, anything else but getting actually involved in how the sausage is made. They are working on meta tasks around the problem, in the hope the solution will write itself.

These two crowds are currently living in very different worlds, and getting very different results. We'll see what survives soon.

Because there's a third crowd: everyone else/the general public that are standing up vibe coded websites and don't give a hoot how things work in the background or know as long as money is coming in. There are people that are using AI and thinking less and less causing their brains over the long term to become more inelastic.

We're in for a very, very painful future that will have mixed results. On one hand, you can boostrap things a lot quicker with less mental effort and it helps get up to speed without having to know some complex things (e.g. deep knowledge in coding). This can help us innovate on basic things faster, probably.

On the other ... people aren't going to learn. If something breaks in that state where they don't know how something works, what, we're just going to ask another AI to fix it? I don't know how I feel or think about that. On a long enough timeline, there are people that won't know how any of this was designed in the first place.

That's the world we actually live in. And that's what will survive despite crowd 1 and 2 that you mentioned above.

These vibed systems will not have security built in. They will increasingly handle user information, PII, credentials, etc.

We're heading straight onto a very profitable era for scammers and other cyber criminals.

He wants my tech expertise, his code is spaghetti, he is making all the mistakes, he is experiencing AI psychosis, his AI makes md files warning him that its all going to burn him which he forwards to me lackadaisically without reading

But can he sale? Yes

Its tempting for me to proselytize that he isnt using feature branches or project tickets or even deploying with committed code

But I bite my tongue and tell him to focus on the MVP since he wants to prompt Claude Code for 48 hour sessions without there being any indication of how other devs could contribute

Because he has clients that wants what he described, and because he has no capital I get a huge cut of that

I’m fine with that, I’ll clean up the project very quickly

It could be okay if it wasn't for the fact that they have a high esteem of themselves and don't learn shit.

The first POC they vibecoded and managed to sell was a pile of trash that we couldn't realistically deploy as it.

So we spent two weeks to make it something decent enough to have the minimum confidence of the thing being reliable and safe enough to reach staging. Two weeks during they told us daily how we were slowing everything down.

After that we spent an hour explaining them how making something works on their computer, without tests, without thinking about edge cases... was not the same thing as deploying it and releasing it to actual users.

We agreed on, next time, asking us for an estimate on how much it would take to move the POC to something that could be released, before signing on any engagement with a customer.

Well, last week they came with a new deal they just signed on a completely new POC. Customer was expecting it for yesterday. To make it work, we have to setup a VPN between our infra and customer infra. Their internal process make it impossible to have this under a month.

Now, my guy and the customer, are mad at me because I can't deliver.

And the first POC? Customer wants new features. My guy don't want to deal with it because it's not their job.

I wasn't involved, but I heard last year they tried to vibedeploy, provisioning an AWS account in their own name with their own credit card. I let you imagine what happened and why they haven't retried this since.

…reads MRIs and video to detect cancer

…analyze genomics for early target discovery

…assisting surgeons

…folding proteins

And the list goes on in other fields as well. Just hoping the recent AI counterculture doesn’t stigmatize other uses of AI.

Am I a fan of Claude code? Not particularly, but I have used it on occasion. And I’ll never understand someone using an LLM to write anything (especially a comment on a site like HN) intended for consumption by other people. Not because I think it’s subpar, but because the point - IMO - is to make human connections, learn, teach, and debate. That’s hard (impossible?) to do if you’re just typing a 30 second prompt and then copy/pasting the output.

For me personally I am vaguely indifferent to programmers using LLMs to make more shitty code. My worry is the second and third order effects

For work currently, as an SRE, I'm being asked to maintain and look after slop as if its properly built and instrumented. Our platform has clear rules and conventions, and AI isn't following those.

For the wider world, I fucking hate that image/video generation is evaporating what is "real". For memes sure its great, but for bad actors it gives a brilliant way to say "its AI wasn't me" and then the debate moves away from "did person do bad thing" to "is it wrong to say that things are AI?"

I also worry about the debasement of value of human work. Looking at history, say of the weavers, it didn't work out to well for them when the powered loom came along.

They eventually moved on to other things, because that was the only option. And the world is better with the power loom. It's scary but we still have to embrace that eventually pretty much all valuable labour will be automated, and by then our society and economy needs to have been restructured for supporting humans providing 0 economic value.

Yes, but then whole swathes of the English countryside (and then the Indian countryside) was plunged into destitution for generations and it took rebellions, massacres and revolutions to get something like comfortable living.

I'm not speaking from personal experience, this is what friends are doing at their startups

But I am not surprised at all, because the building blocks of major applications are all out there as boilerplate code - heck half the time AWS has the example you need for you, assuming you know what you want to stitch together and why

If you know the major AWS tool chains and how and why to use them and how to design a product in microservices, then theoretically Claude has no idea what the whole shebang is up to but happily writes all the parts

Show the receipts. Where are the mobile apps, the photoshop replacements, the video and audio editors, the games and game engines that took a decade to make in the past that have shipped since Claude code came along?

> By then, enough real-world feedback would have surfaced to identify the major issues, and tools like Claude Code would make it possible to fix and ship version 2.0 at an incredible pace.

Again where are the receipts?

My experience with coding agents is that they’re perfectly good at generating a v0.1 that just about passes the sniff test. It does the first 90%, but the second 90% always takes longer than the first 90%. That second 90% is what coding agents are terriblle at, and are what make actually good products.

Even if you hired an actual programmer, it'd take a massive amount of time to build a Photoshop clone.

Of course, at the end Photoshop is lines of code and it could be output as is, end to end. One problem is that users aren't generally giving very precise design documents which would narrow the way to interpret them into code in precisely one way. Or that a design document at any level of precision, other than code, couldn't be interpreted in multiple ways when it comes to a specific implementation.

LLMs also take a relatively long time to output acceptable code, often taking tens of minutes before giving you a small diff. The larger the codebase, the longer it usually takes to start producing code, even over an hour.

And yet it’s not.

> LLMs also take a relatively long time to output acceptable code, often taking tens of minutes before giving you a small diff. The larger the codebase, the longer it usually takes to start producing code, even over an hour.

The problem is that they don’t generate acceptable code, they generate code that needs to be edited to be acceptable. That has always been the slow part of engineering. Waiting an hour for a bugfix even if it cost $75 in tokens would be cheaper than hiring an engineer but only if it worked. And it’s a bit like hiring a snake oil salesman - it passes the sniff test but it’s only when you’re drowning in the fact that your ai now takes 4 hours to fix the same bugs, and it introduces new bugs _and_ you don’t have anyone who can reduce that complexity that you see the reality. For a lot of us, that is immediately clear from first glance at the output of Claude and codex and the likes.

That was my point as well. That it hasn't been output, even though it could be done by a talented solo developer given enough time, and that current LLMs definitely aren't able to do so.

> The problem is that they don’t generate acceptable code, they generate code that needs to be edited to be acceptable.

You've never had an LLM output a one line bugfix that is correct to the point where you don't have to edit it?

To make things more concrete, here's an example from the creator of Redis on how he utilizes LLMs in programming: https://antirez.com/news/164

I have. I’ve also had IDEs and static analysers do the same thing. I can also take my car out of gear and have it roll down a hill but that doesn’t mean it can run without fuel. Only a sith deals in absolutes, and in the general cases LLMs don’t generate acceptable code.

If you are a graphic designer you are not going to make your own Photoshop. Even if you could ROI is not there.

Graphics designers of course are bad example because everyone will just generate images directly from LLMs.

But restaurant owner for example could build his own website with menu - heck even with just slapping html without LLM making a decent website was easy but these people didn’t have time for that.

I work in insurtech, wet dream of all big companies dealing with insurance was customer self service so they were building those interactive forms - but no customer wants to do the filling, they don’t care they don’t have time they are busy running their own business and they want to call or meet with someone who knows what needs to be filled in those forms. Chat with AI is not fixing that because business owner will have to spend his time answering all these questions that were in the form but only now it will be chatbot.

If it was just a toy with no shot at making something real people would go "oh cool have fun with that" and move on with their life. Instead we see pretty emotionally charged posts.

It's certainly currently an edge if you know what to tell the mystery box of magic in precise terms.

I don't think this distinction is going to endure though - every level of "it can't do it" has fallen and generally faster & more decisively than predicted. We started with it printing hello world, to autocomplete where you still needed to be able to know what the line should do, to autocompleting functions, to writing entire units, to working out architecture tradeoffs, to doing research planning architecture execution and testing all autonomously. That trajectory plus people retreating to nebulous "I'm adding taste" tells me this is going to sail straight past "tool in toolbelt" territory at Mach 10.

Everyone has their own perspective but to me "show me the receipt" at a specific point in time is a completely wrong lens for a tech that shows clear signs of exponential improvement (i.e. https://metr.org/ ).

> every level of "it can't do it" has fallen and generally faster & more decisively than predicted

I disagree. The agent + harness model was a huge leap and really moved the bar. The tools became genuinely useful for coding very quickly.

> Everyone has their own perspective but to me "show me the receipt" at a specific point in time is a completely wrong lens for a tech that shows clear signs of exponential improvement

At some point, the exponential improvements have to show results or it’s just a Ponzi scheme.

That's why I'm saying this whole look at one point in time logic isn't useful here. Depending on where you set the cutoff you get diametrically opposed answers.

>Ponzi scheme

The IPO & bubble financial shenanigans are only loosely linked to the technological advancement. Tech genie is out of the bottle, people are intrigued and people with ability to tinker on this are spread globally. Even if the entirety of western tech & financial sphere disappeared tomorrow tech progress here would wobble and slow not stop.

Even the one global nexus where progress could have been killed globally - Taiwan - is looking like it'll de-risk shortly between CXMT and SMIC's rapid progress.

In my mind the base case assumption here has to be that the trend (that has been remarkably consistent) continues until proven otherwise. Stack enough improvements on top of each other and instead of a useful script you shall have your photoshop. Maybe...

I think vibe coded photoshop is what’s being talked about from Anthropic, OpenAI as the end goal - Dario is on record saying that AI will replace engineers and Sam Altman has said “ we will never ever write code by hand again. It doesn't make any sense to do so”. The cursor founder has said that he ships 10x what his other engineers ship. I want to know where people _genuinely_ think the cutoff is, because there’s a lot of talk about where it’s not, and that’s gmoving the goalposts.

> The IPO & bubble financial shenanigans are only loosely linked to the technological advancement.

Except they’re not. Someone is paying for this compute power, and energy.

> In my mind the base case assumption here has to be that the trend (that has been remarkably consistent)

Making wild promises, and insane promises about capability and then doing the same thing 3 months later when a new model releases? Isn’t it convenient that both OpenAI and Anthropic have models that are “too powerful” to release. How responsible of them.

At the same time; Anthropic, OpenAI and Copilot have all changed to usage based to billing recently for enterprises as they’ve been been undercharging by 10/100/1000x in many cases. Enterprises are limiting costs (uber limiting spend to $1500/mo this week).

If these tools were really game changing and integer productivity multipliers why aren’t major engineering organisations spending all their hiring grown on these tools and getting ahead of their competitors? Because they’re “not quite ready” just like they weren’t 6 months ago, and they still won’t be in 6 months.

However, it's launched this enormous tidal wave of mediocrity that emboldens the dumbest people to do the dumbest shit and make it my problem. I just had to yell at one of the IT guys for trying to hook up our Duo to Claude, and I'm still mad about it lol.

>trying to hook up our Duo to Claude

ngl that is hilarious

For code in general, the various meanings of "I am {insert number here} times as productive" on Figure 9 page 36: https://www.nber.org/system/files/working_papers/w35275/w352...

Same document, Figure 12 page 41 shows a significant spike in iOS apps but also the users per app is way down (which you should expect, given this makes it possible for low-user-count apps to be sensible business propositions).

How many people care to spend a year making a replacement for something that took a decade? Photoshop, despite the complaints about price and subscription model, just isn't expensive enough to justify one engineer-year to replace. Unreal and Unity are free for a lot of people using them, and likewise are not worth the cost of replacing for those who do end up paying (because the teams using them know how to use them and don't want to be retrained).

For this reason, you should be looking at things which would have taken a year of human time but now take a month, or faster, so less Photoshop 27.7 (today) and more back when it was still called ImagePro (1988).

For games, I've seen games like the following take a month or more to get good enough to be interesting, and yet the following took me two prompts, the second of which was the single word "continue" (and only needed that because this was on the free tier and I used too many tokens); I didn't bother to look at the code, I don't care about the code, making the app itself was as easy as simply finding an app like this on the Apple App Store even though such an app was in one of the top-10 lists: https://github.com/BenWheatley/Piano-Trainer

Is this game "as good as" the one on the App Store? Who cares. Any random person who wants their own app can now get their own custom version doing the specific things they care about, which doesn't need to simultaneously support all the use cases of all the other people who would buy the app on the App Store.

From what I read on Hacker News comments, the same is happening with video editing, where it's not "Make an iMovie clone" (why would you, iMovie is free), but rather every time you need one specific thing, you ask your LLM of choice for a solution, and it gives you a shell script which calls ffmpeg with the right arguments.

HN always have had a sizable anti-tech crowd (I don't want to say luddite because it's borderline pejorative). If you see the technology from close and you understand the human impacts of it then there is a reason some would rather stay clear from it. I know some FAANG engineers who doesn’t allow their kids to have smartphones or use social media even though they are themselves working at those companies. Why do you think that is? And you don’t even have to be a FAANG employee to see the social and human impacts of modern technology. AI is the same, in fact not even the same because it’s even worse and it will be only worse.

It's frequently said that technology is ethically neutral, and whether it's used for good or bad ends depends on how it is applied.

What you call the anti-tech crowd is simply the crowd that takes their ethical responsibilities seriously.

There are other potential points of view that could be adopted instead of tech neutrality. Some tech could be seen as inherently good, in which case there very little concern about how much of it is used. Some tech could be seen as inherently bad, meaning it should be avoided at all costs.

Anyone being honest about AI can see that although it has some positive uses, the potential for misuse is enormous. Therefore, if you're going to use it at all, you should think carefully about how to apply it. To people that have fully bought into the hype this caution appears like negativity instead of rationality.

We've seen many applications of AI lately that aren't particularly sustainable, in several aspects.

You think the real world has nothing better to do than test your shitty code?

You will need a lot more to make yourself my enemy, but this is the divisor between us... not that you like to use Claude and I don't.

I think it depends a lot on where your interest in (self) development lies.

My main motivator has always been to understand how things work, and myself being able to create as elegant solutions as my technical role models (in the range from colleagues and mentors to the elders of our field), hopefully even pushing it further. Having the LLM just create the product robs me of that, or at least of the most rewarding parts of that. And that's why I don't like to use it.

Different people are driven by different things, I don't think either trumps the other in the objective sense, we're just wired differently.

For me working through the programming part is the understanding and solving. Programming languages are pretty beautiful and encourage different ways of thinking. Hopefully we can understand it and contribute.

Which things, specifically? I got started programming in order to control scientific instruments and analyze the data I collected. I care about the systems I'm studying. I don't really care much about the software I'm programming. As OP said it's a means to an end.

I think you're right that people on HN are generally more curious but it doesn't have to be curiosity about every single element of software. We don't write assembly code anymore either, half of software is about making software easier and faster to write.

Low level systems programming mostly. Embedded systems, *nix userland programs, API and library design, sometimes including writing assembly although in very small fractions.

These days, however, my time is spent managing agents. I have lost the joy of craftsmanship. I don't spend my day in emacs anymore.

But I am learning to enjoy it. Maybe because I have always had a utilitarian streak, and I actually care for the ends, so husbanding incredibly efficient means is thrilling. I am actually having fun.

This is important to understand. I have been coding since I was 11 when I got my first C64, and it is a genuine passion for me, but I also love working with LLM tooling.

One of the biggest things for me is that after decades of sitting in front of a computer I have chronic back and wrist pain that makes it impossible to do the long deep focus sessions that were normal when I was younger. Using AI tooling to handle all of the procedural tasks (running tests, debugging, managing git, etc) dramatically reduces the physical strain of programming, and allows for a much healthier workflow, with regular short breaks.

Not sure if it's important or not, but for the sake of OP's discussion I note that your value is not necessarily tied to "speed of execution".

But, even if I had generational wealth behind me to be able to leverage the AI to my advantage, I still see a lot of cons in the way cheap content generation worsens the world around me: facilitating fraud, political shilling, disrupting online conversations (now everyone just sends bot summaries to each other). In a way, I feel a similar change that from the "pre-facebook" Internet to the "pre-chatgpt" Internet that happened in the early 10s.

Also, programmers will be least negatively affected by AI. Humans will need to be in the loop in the forseable future, and programmers are a good candidate for those kinds of positions.

But more generally, I'll never understand this attitude about jobs. As if your job is this thing that you own that someone might take away from you. To me, my job is is something useful that I do in exchange for money. If I cease to be useful then it's fine if I lose my job. I'll find somewhere else to work, somewhere I can be useful. It might be paid worse of lower status but, to me, being useful is the whole point.

However I am increasingly annoyed at how everything has to be framed as a conversation about AI, how every tech-adjacent company has to brand itself as AI-first, and most of all, how overblown predictions are about an LLM being conscious, etc.

In short – it’s a useful technology reshaping tons of industries, but the hype is grating.

I have spent the last 3 months away from family, I caught up with my brother & his wife and they also got back from an interesting vacation recently. I tried to get information about their vacation but at best got 2 sentences that it was enjoyable. But they spent more than 24 hours(sleep over to see the nieces) ear bashing me about AI.

I truly don’t care that people find this stuff exciting, just leave me out of it and tell it’s AI content upfront and we’ll get along swimmingly.

Obviously the answer is $$$ and the fact that this admin's economic policy has further encouraged the market to go all-in on AI as it's the only thing that's trending in the black for the economy right now. I don't think you'll find many people on HN who won't readily admit that even if they're anti-AI, LLMs are genuinely amazing pieces of software that can be transformative and useful in many different environments, and it's mindblowing how they work. The issue comes from the very harmful way it's currently being commercialized and marketed.

I also find takes from the anti-LLM to be exceedingly dumb at times. Oh this text has this and that, it must have been written by LLM and thus is not worth even considering.

I'm personally amazed by what "A.I." is actually capable of, but I have a fairly solid understanding of what's going on "under the hood" of it, and therefore have somewhat realistic expectations of it. Then I see folks go overhyping it's capabilities because they've drunk themselves stupid on the lies they've been told about what it is and what it's capable of (and it's simply not capable of what the liars at the top of the A.I. corporations are telling everyone). Just try to temper their enthusiasm with a bit of reality and you're instantly "anti-AI" or "doomer" or some other just completely wrong characterization. At this point I'm convinced that for a lotta folks, A.I. is just another literal cult just like politics these days, or crypto-coins not that long ago... Drink that kool-aid, I guess... ~shrug~

I also don't think that many of the so-called "anti-AI" folks are so much against AI itself, as they're against the unethical ways that certain folks "at the top" are using it to do massive harm in an attempt to try to satisfy their bottomless greed and lust for power, and against the ways that some other folks are using it to basically escape the need to think at all, even when their job requires actual thinking.

That and Jenson screwing those of us who made him over the last decade.

It'll be better once the fraudsters are in jail and once we're able have boxes with ~1TB ram running off of our solar in the garage.

Ask HN: Why is Hacker News so anti-crypto? : https://qqrl.tk/item?id=31302494 (Do note that the post is flagged and there might be some good moderation reasons for that)

This is the reason that most of us at HN might dislike overhype. I have seen a lot of these crypto users move from crypto hype to AI hype.

Every few years, people forget the last shiny thing and move to the next and think why is X crowd not invested in Y? They must be anti-Y!

Oh speaking of crypto, bitcoin has tanked so bad, its almost at an all time low at 60k$ sinking to levels of october 2024: https://www.cnbc.com/2026/06/05/bitcoin-dismal-week-price-be...

Trying to “correct the hype” just looks like clowning in hindsight.

It’s like people in 1990s were trying to correct the internets hype: oh you know it won’t change anything and the tech bros want to create hype out of nothing!

So it’s not neutral to be anti hype for AI. It is just wrong.

Which is undeniably true. I am not "anti-AI", in fact, it helps me immensely in my current job, but in my experience, using these tools still requires quite a lot of involvement. Otherwise, updating existing or adding new functionality becomes increasingly difficult as the system grows. The funniest thing is that when you start to lose touch with the internals of the system you are building, you cannot even give the AI proper context to pinpoint the problem or guide it to make specific changes, which results it a lot of wasted tokens, wrong assumptions and mountains of sloppy code.

I see arguments saying "what does it matter, since you're not going to be touching that code anyway?"

Well, what you said about not being able to give it context is one aspect. Another one is that what the LLM is writing is still software. The more brittle and complex that software gets, the harder it is for the LLM to maintain it, since you get either spaghetti code or a house of cards where you can't move one bit of the system without breaking stuff on unrelated parts of it.

Oh, but the LLM can fix it, as long as you have some formal verification of the functionality! Sure, but it compounds.

All of this is absolutely fine for some projects, but for most enterprise and commercial software you need more rigour or you'll see yourself with a long, expensive and risky migration in the near future.

A Quinnipiac poll showed 80% of Americans are "very" or "somewhat" concerned about artificial intelligence, with only 35% feeling excited about it

https://poll.qu.edu/poll-release?releaseid=3955

Gallup found that 71% of Americans oppose the construction of AI data centers in their local communities.

https://news.gallup.com/poll/709772/americans-oppose-data-ce...

A Fox News Poll indicated that 80% of voters believe protecting the public's interests and enacting regulations should be prioritized over unchecked technological innovation.

https://www.foxnews.com/politics/fox-news-poll-voters-see-ai...

And Pew Research found that the majority of Americans are "more concerned than excited" about AI, with that number increasing over the years

https://www.pewresearch.org/short-reads/2026/03/12/key-findi...

I would also suggest that if you believe your two links are "detached from reality", you may be struggling with your own bias. They're both perfectly reasonable takes that you are totally reasonable to disagree with. Try to come down from that feeling and realize that disagreeing does not necessitate that the person you are disagreeing with is insane.

"I listen to both kinds of music, country and western."

https://hn.algolia.com/?q=ai

As for your argument, there's no such thing as elegance. Code "elegance" is mainly maintainability (and, to a smaller degree, some other aspects like security, performance, etc.). The importance of maintainability greatly varies between projects, industries and individual subjective viewpoints, resulting in the diversity of attitudes to AI-assisted coding. That, of course, assumes that AI cannot match humans in maintainability. Which seems to be the case to me right now. But it also seems that the gap is closing, not as much through AI writing "better" code, but mainly through it being increasingly capable of maintaining "bad" code.

That said, I agree with dang’s read. This site is big enough that both camps are decently represented (expect “mine”, of course), but anyone sees only what they want to see. The boosters see only doomers, and viceversa.

Other than every boardroom on earth you mean? ;-)

This reminds me of Anthropic's post where they say they ship 8x as much code as they used to.

And I stopped to consider how many times I've used an app and thought, "You know what this needs? More code!"

Bug? More code. Unexpected behavior - read the docs? Couldn't find anything. Let's try another 1000 lines of workarounds. Still doesn't work? Write another 1000 lines to monkey-patch behavior. It sort of works now.

The actual solution is removing those 2000 lines and passing the correct argument on line 25 which is clearly documented. Most humans would never do that because we're too lazy but it's so easy to generate slop at an exponential rate and blow up the LOC metrics.

With LLM coding I already have seen agent pointing out easier solutions because agent is not scared of or tired by reading existing code. Whereas most of developers want to write „their code” not read someone’s else’s code.

This team eschewed libraries and shared code. Copy/paste everywhere.

Every defect had to fixed in 100+ mini-applications. It was a telecom MMI product.

- the cloud was invented and we were told CTOs would be able to just point and click and make infrastructure and apps! What did we actually get? Another layer of abstraction to debug through. Does it have is perks? Yes. Does it have it's own problems? Yes. Is it more expensive than setting up bare metal and having a solid team? Well that depends on what you're doing and the economics of it and the team.

- then document storages came along like and got wildly popular like mongo and people were calling it the end of SQL! And no more complexity or relational nonsense. Everything is JSON and life is great. What actually happened? These companies realized over time their data was getting trashed, adding things and fixing bugs became complex in pure docstore systems. So the initial v1 was easy and looked beautiful but only 4 years in you have a production db with orphan data that's twice as big as it should be. New features take forever to see a clear path in adding it to the model because it's no longer as intuitive to get performance for a feature.

Anyway. I see AI taking both of these roads at the same time. In 5 years I believe the code will be a giant pile of unfixable mess for most vibe coded things. I also don't see it getting rid of programmers but just adding another layer of abstraction to the mix that yes is helpful, but only if you already know what you're doing, much like what came of the clouds.

Really depends on what you are shipping, what your users expect and what your personal preference is. I do not want to go 10x on products that need high performance / high reliability, is deployed at large scale where its not easy to undo. But for other stuff, sure why not. The problem is everyone just puts everything in same basket. Either way, AI is useful but not to the same extent people claim it to be.

Happen to be a startup that isn’t mission critical to someone’s health and well being? Great, now you can use AI and be as dirty as you would like.

Are you working with dangerous chemicals that are ingested by others, or systems that control hunks of metal flying through the sky with hundreds on board? Maybe we should stay clean in those environments until we make AI itself clean.

As a front-end guy, if I owned a project I would have the API AI-assisted and UI AI-driven.

It is like replacing people at the supermarket with self checkouts and expext they still feel fulfilled on their job, replenishing products from the warehouse.

Additionally only optimistics cannot see their job is in jeopardy.

If you deploy 10x faster, than me as business owner need less of you for the same amount of work.

No, the need for work doesn't grow exponentially every year, there is a physical limit to distribute among all people offering delivery capabilities.

Finally its environment impact destroys all the progress that was made in the last years, and brings computers prices back to the 1980's.

An important consideration here is that velocity is not zero sum. If you are delivering in weeks what used to take months you are creating an entirely new realm of what is possible to do with software within a corporation.

In the real world, I have never worked for a company that doesn't have a huge backlog (either tracked or in engineers heads) of work that would never be done because it wasn't economic under the old model. This tends to apply to the internal work of engineers (developer tooling, infrastructure, tech debt, etc) more than anything else. 10X faster doesn't necessarily mean shipping 10X product code. You can use that productivity boost to accelerate prototyping, ship betas faster, move the iteration loop faster, all while shipping higher quality code with less tech debt and having the time to continuously improve the engineering side of things that the business never sees.

If you fulfill your delivery contract in half the time, great for me, you now need track down another customer.

Or put in another way, an agency now only needs a third of previous team sizes to deliver the same amount of work.

The other two thirds might be lucky to have another project assigned, or get to seat on the bench, and depending on the world region (offshoring shops) get their salary halved, before being fired if seating too long on the bench.

The amount of customers willing to buy a specific product is limited.

Similar to an artist who enjoys drawing or painting, would they use an LLM? No, because they like doing that craft.

Would a programmer who loves programming use it to create marketing materials? Absolutely.

I want a solid, proud, well-engineered bridge, goddammit!

1. https://en.wikipedia.org/wiki/Tacoma_Narrows_Bridge_(1940)

I totally get why there's so much hype for AI.

I don’t think these are bad guys or bad engineers, it’s concerning to me though. Engineers should be getting sharper in their analysis over time not weaker. When someone tells me they haven’t even looked at a few lines of code they submitted it’s shocking and a sign of sloppy thinking. It’s rude too because is expecting me to pick up their slack.

I’m sure the AI companies are in love with the idea that people are growing dependent on their product for things they could easily do themselves. That’s a great business.

I just had to deal with this, they never pushed back on my PR comments, just copy pasted everything I said back into Claude. Its just second hand vibe coding at that point, might as well fire the middle man…

His defense was always "everyone uses AI, including you" and I'm like yes i do use it for code but never communications, and my code is always 10x better than the untested slop I was constantly asked to review.

This is a guy with 30 years engineering experience, reduced to submitting untested and unreviewed slop code of a quality drastically worse than the least-experienced juniors in the company.

That phenomenon on a global scale is concerning to think about. That people are using these things outside of tech to get medical advice or as therapist replacements is even more concerning.

So there is a wide range of judgement, and more importantly, a diverse set of worldviews. These are beliefs that form the foundations of cognition and perception. In the general population there are a massive number of people who do not understand technology and/or do not really appreciate it at a deep level. This includes a significant percentage of startup and engineering people unfortunately.

This isn't really related to AI because it relates to manually coded things just as much, but on this point specifically this is only true for your very early I-gave-it-to-a-bunch-of-interested-people-to-try customers. It's much less true for your first paying customers, especially if the 'major issues' make their pain worse (e.g. data loss, time wasted, etc). You lose those ones for good, or until there's a critical mass of social proof to tell them the early problems are solved.

'I can dash out an early prototype with AI and then fix it later' is a dangerous mindset. If you're working in a small market with a limited number of customers you might piss off enough people that you won't be able to recover. There still has to be some level of quality. But it is a balance.

>> I’ll probably make a lot of enemies by saying this, but do people realize that code is just a means to an end?

The answer is that, yes, most people do understand that. Some people like writing code regardless of whether they realise the extent to which that code is useful to others or not. Some people write code just as a means to an end and couldn't are less how that code is produced. There is, from what I've seen, a general expectation that the people who care about code are better at writing it but my experience is also that they just aren't. Some people who are "passionate about prorgramming" are horrible coders, some who are lukewarm or don't care at all are great coders.

I honestly don't know how AI comes into all that. HN is certainly not anti-AI. Just the other day a post made the first page with a title like "HN front page without the AI" but I can't find it now. There's as much AI stories submitted as anyting you could consider anti-AI.

Many kinds of software cannot be yeeted 10x faster with AI. Someone has to sit down and understand what the right thing to do is, first.

It also matters how many users you expect to be able to reach. If you're Facebook you can afford to use the first 10,000 users as unpaid QA. If you're an indie shop that's barely getting downloads you really want to make a positive impression on your initial users or you're toast anyway.

https://htmx.org/essays/code-is-cheap/#understanding-is-expe...

It is more of a reaction to misrepresentation and falsehood, which AI and its rhetoric seems to have generated a lot of.

> Let’s face it: by the time I manually ship version 1.0 of a product, the AI-assisted version could have been deployed 10x faster. By then, enough real-world feedback would have surfaced to identify the major issues, and tools like Claude Code would make it possible to fix and ship version 2.0 at an incredible pace.

It’s takes like this that remove the nuance completely and ignore so many facets of the debate. That being said, let’s assume this is true because I think vibecoding a CRUD app does make this realistic on the face of it. When I say vibecoding I mean prompting and dropping, not reading the code.

You do your adversarial reviews with multiple agents, you have your UX agent look over it, your security agent etc. Under the hood there are architectural issues. The code is probably passable, but rough.

You release, customers start using it for their business that they depend on for income. Issues start cropping up, you burn more and more tokens to fix the issues as they come up. Expedience starts sacrificing quality even still, architecture (if there was any) starts being violated and it degrades more and more.

I consider myself a professional, I would never want to end up in a situation like this for mission crititcal products. So, what do I do? I read the output, I make sure I understand it. Why? I care about my customers and secondarily I’m the one with the pager when something breaks down.

Now, for some fun hobby project to track my hobby paints for Warhammer… who cares? I agree. I have used Claude for such projects and not really cared. But your statement does not hold up in the enterprise world with mission critical software.

> At some point, execution speed starts to matter more than the elegance of the code.

This is reductive. You’re assuming people’s concern is “elegance”. It isn’t solely elegance. It’s domain understanding. It’s quality over all. It’s being a professional.

Writing the code was never the slow down for large scale enterprise products.

If you have an application that real people use in everyday work and depend on stuff not moving under their feet. Execution speed is not something you aim for because you have to adjust to speed of users adopting changes.

As a startup owner of course you can’t really care about those people using your software because you have to pivot as quickly as possible to an investment that pays the most and boring every day app is not going to be a unicorn.

There is another option at the end of the spectrum. You aim at posthuman world where humans are not required and your software doesn’t have to bother with earning money or users that are slow or have emotions.

I have decided to leave what has been my workplace for over 15 years - mainly to do other types of work. Why? I stopped thinking in my current job as a system architect and dev. AI output is better or on par with my thinking, and I lost all feeling of achievement in my daily work.

I still want to use my brain, so I will find a job where I can continue to do that.

For anything something else will use, this is a real problem you can’t simply wave away.

> AI “writes bad code,” “introduces bugs,” “creates technical debt”

Bad code is hard to maintain, for the AI as well. While all code eventually becomes technical debt, the throw-away nature of AI code, and the sheer volume it creates, tends to turn it to technical debt more quickly. If code is “cheap”/“easy”, and the AI is bad at maintenance, why not do a full re-write for every update?

Bugs are bad for users and harder to find when you don’t have a deep understanding of the code. Logic bugs are the worst of these, because the AI and linter won’t necessarily find them. Some logic bugs can cause a lot of real world issues before they are reported and found. If doing a full re-write for updates, because the AI doesn’t care, each run is an opportunity for new bugs to get injected into the code.

If I’m expected to understand and answer for the code when there are issues, I need to be able to read and understand it, not just deploy quickly.

https://halecraft.org/software-engineering-is-the-new-manufa...

People have reasonable concerns about the ethical, political, economic dimensions before we even get to the technical capabilities.

Even within the narrower question of the technical utility, I think there are a lot of factors which differentiate people's different experiences which are largely unacknowledged and lead to people talking past each other and failing to understand how others have such different experiences and opinions.

The sentiment that "users only care if it works" for example implies that all considerations beyond "does the feature work today" are developers self serving their aesthetics, but overlooks many other concerns which _do_ impact users at a later point.

I wrote about just this division of experience and the polarisation which manifests on hacker news just last week as it happens https://www.julianhaeger.com/posts/Disparate-Results-with-AI...

Good or bad, I believe the genie is out of the bottle, and we should do the best we can using and mitigating AI. But I don’t blame or disagree with anyone who’s critical.

I'm working on a game, and I've been fussing over the code quality. And yeah, having code that isn't awful is important for various reasons. But with a game, it got me thinking, the code is literally the only part of the game the player doesn't experience.

The time I'm spending on the code, I could be spending on the art, the game design, the music, the story...

But my natural tendency is to hyper-focus on the only part of the game nobody will ever see. I thought that was interesting.

(That being said the codebase is ass and I do need to clean it up!)

Humans are trained for easy wins, not thinking about long term consequences and assuming risks will not play out. It's the lethal trifecta of emboldening our worst characteristics.

Not only that the majority of problems that we have with software engineering are self-inflicted and everyone has forgotten that they don't have to be. All this does is allow us to operate the pile of shit we built over the last 25 years with somewhat less efficiency than we did 25 years ago.

The customer does indeed care that the product works. But the engineers should care what they build and with what. And they don't any more. The status quo is using a statistical model to assemble a pile of trash.

Go back 30 years and I single-handedly built a full custom ERP system for a company in 3 months without an LLM in sight, with no internet connection and thus without pulling a single dependency off the internet.

Add the me-too culture over the top "we have to have an AI proposition" and it's a gold rush but the gold is muck.

Unlike what many other comments here seem to suggest, HN seems much more pro-AI than what I see in real life amongst developers - at least where I live.

And I do think many users would care more than we might think, but unlike art etc. it is often more difficult to tell.

I use claude to write a design, review the design, turn that into an implementation plan, spend 2-3 turns reviewing that, but still when that is turned into code it misses things or creates helpers that's not actually used or... It creates massive files and unless I explicitly tell it to it never refactors them. It often just silences errors and warnings instead of actually fixing the problem.

It saves a lot of time, and I'm building things I couldn't have on my own. But it makes a lot of mistakes, it's far far from one shots which the hype keep going on and on about. It's tricky to put firm limits on what it does. A lot of the mistakes I catch because I've spent 15 years without an agent and sometimes it's just "hm, this smells weird" and I begin digging. I worry about the next generation.

For me the mental framing of "It's all hallucinations, some of those hallucinations are useful" is helpful to keep frustration in check as I ask it to review the same implementation plan for the 4th time and it turns up different issues because the input was slightly different, or review the output code and see allow(dead_code) despite my claude.md forbidding it.

It hates following project conventions, loves mocking so much out of tests that it fails to test anything at all, and yeah constantly leaving dead code around.

And yet it's still very useful. It's just nowhere close to as good as it's hyped, and yet there are professional developers who are using it as though it is.

Then I want to shout at it "Is the work done? No it isn't so yes of course continue, are you stupid?", but then I remember it's basically a big matrix and for the 58th time type up "Yes, ultrathink and continue"

A junior developer would learn, claude doesn't. I've tried adding this to CLAUDE.md but it doesn't help.

This is very much not settled, and very much depending on your market. Selling games to gen-z? Yeah, they are going to care a lot.

Do you feel this way about apps that gather information about you? "It says it has no tracking cookies.." Or apps that sell your email address? What if I claimed my product was vegetarian?

Like, wtf kind of attitude is "just lie about it".

We _know_ LLMs can't be _that_ good as they are promoted.

I've spent the last 6 months creating a production grade app from scratch with Claude where I wrote no single line of code. I've reviewed code and it was looking good, almost completely following my templates, workflows, skills.

Now I've started to make minor manual updates and I'm horrified. Claude has no idea why there were those templates and instructions in place. It followed them blindly without grasping their spirit. The end result is like a very junior dev copy-pasting answers from Stack Overflow into the codebase. No consistency, chaotic application of different conventions, duplicated code, ghost code (does nothing), and perhaps more as I'm digging in.

The pros: The code works, all tests pass (43% code / 57% tests, 1:1.3 ratio), the UI looks good with visible glitches

The cons: I'll have to rewrite most of the code on the long run, make it fit, easy to maintain.

The verdict: I wouldn't started this project alone. Claude get me through to v0.1.0 / MVP where I've focused solely on the product: technologies, architecture, functionality, and usability. Now it's easier to refactor all for v0.2.0 manually without Claude.

So this might be our gut feeling: we know it's something good, but not as good as the stakeholders might promote. We know it helps in some ways but it's a nightmare in other ways.

We are not anti-AI but rather pragmatic: Not that AI enthusiasts we are expected to be.

I didn’t understand this part. You said you reviewed the code and it was looking good, so how did the cruft creep in? Were you reviewing every diff, or taking an occasional sample?

It suggests to me that you don't see really any of the potential rewards for excellence. It's almost exactly the same thing as saying "there's nothing left to invent." I've watched software change the world SO. MANY. TIMES. during my short-so-far life that I must call such a proposition as the death of creativity bull fucking shit. Using AI makes you less likely to create any LASTING contribution to the world, even as it makes you look very busy.

If you want to be the best, you do the fucking work and learn from it. There Is. No. Other. Way. There never will be.

I also don't consider LLM's to be AI. I put it in the same category as PageRank.

> AI-assisted version could have been deployed 10x faster. By then, enough real-world feedback would have surfaced to identify the major issues

You want to ship major bugs to your users, let them find them, report them and fix them afterwards. You passively assume this is a good way to build software without even really questioning it.

Aside from some people just not liking this in principle, there are a lot of contexts where bugs cause actual harm and cost actual money. In some cases, "people dying" and "go to jail for it" type harm.

If you don't own quality, why should I pay? You're just a middleman at that point.