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Comment by impulser_ | Hacker News Reader

I'm pretty sure he's talking about companies and people outsourcing their decision making and thinking to AI and not really about using AI itself.

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.

View on HN

Correct. I use AI a ton and I'm having more fun every day than I ever did before thanks to it (on average, highs are higher, lows are lower). Your characterization is all very accurate. Thank you.

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)

I thinking that it’s quite a different experience going all Jackson Pollock with AI in your own studio on your own terms, compared to the sorry state of affairs of having 100s of Pollocks throwing paint around wildly within a corp to meet a paint quota.

I very much like this metaphor.

Earlier today:

>Amazon workers under pressure to up their AI usage are making up tasks

https://news.ycombinator.com/item?id=48148337

It's the new "counting lines of code". I think many companies are so terrified of falling behind that they're irrationally floundering, trying to appear like they're "with it".

Yup. My friend said his boss has told them basically that they HAVE TO (do all the AI things) because now ‘our competitors will use AI’ and surpass their product.

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.

> good ideas ... aren’t substantially in greater supply

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.

> People should be freed up to think and create better things,

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).

Good ideas also take resources like time, free-space to think etc... many firms dont understand this. Moreover many firms believe the C-Suite are the almighty with the gods gift of great ideas.

There is a degree to which quick experimentation helps you find the good ideas, at least for the incremental ones.

Actually, it's even more than that, right? Economically, it is pumping up/inflating the bubble some more in a perverted way, where it is not the people themselves believing some horseradish, but their employer forcing them to pump it up more. Quite insane.

Claude, please crease a routine and run it in a loop continuously. The task in the routine is “create the most complex code possible, in a random programming language, that produces the exact output “My senior leaders are pinheads,”

Counting lines of code starts to look incredibly sane compared to this, where you’re not just counting lines of code, you’re paying for another company for every line produced. There’s exactly one winner here and it’s not any of the companies using AI.

Feels like a worldwide goldrush, but not everyone has gold in those hills.

Those who burn the most money "win", I guess?

I find that odd given that another division in Amazon is no longer using AI coding tools at all. Its a big company so who knows if this is company wide or just in this one division. I expect its just in one division though.

size of org has a lot to do with the entropy

compare 100 pollocks vs 2-3

> 100s of Pollocks throwing paint around wildly within a corp to meet a paint quota

I wish I had written that.

I can't think of a single case of any AI content, be it prose or code, where I thought "I wish I had written that". With AI code, it's more like I wish I hadn't let the AI write that.

How many ways are there of sending a context dictionary to a template where you can say that there are radically superior ways?

We’re using Copilot at work to build reporting and automation tools. Nothing ground breaking, but very useful and tailored to our needs.

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.

I’m building reporting for my company and what you said mirrors my experience nearly 100%.

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.

How are you dealing with the problem of making sure the reporting queries are correct?

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 make sure to understand the query to the fullest extent. I run explain plan to make sure no nasty things like full table scans are happening.

I guess just like any algorithm it’s easier to verify a solution than come up with one.

Just wait until AI companies stop subsidizing everything and you get the ac

I run local models. They are very good now (roughly 30 billion parameters).

Nothing you wrote is connected in any way to the comment I wrote.

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.

An engineer doesn't care about how fast something is made (at least, not as a primary metric engineering). A salesman cares about how fast they can push to market.

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.

> An engineer doesn't care about how fast something is made

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?

>Why would I not care whether I had them in a month or two,

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?

What AI gives us is the ability to write code that we wish we didn't have to write. It is the killer one-off tool builder, prototyper, dep upgrader

Here's a quote from a recent chat with gpt-5.2 that I wish I had come up with: "Anyone can chase a chicken. Leaders create systems."

Quite the visualisation

Replace "paint" with "shit" and the visual image becomes even more fitting.

But then you lose the Jackson Pollock joke, which is what makes it compelling and memorable!

...or is it?

Never mind the Pollocks.

Oh bollocks.

lmao this analogy

Can we combine this with the infinite monkey theorem? If we have an infinite number of Pollocks throwing paint at an infinitely large canvas surely they are going to create any piece of art we can imagine...

This does exist, it's the Library of Babel: https://en.wikipedia.org/wiki/The_Library_of_Babel#Philosoph...

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

This is the best characterization of the collective corporate madness I've seen yet. Bravo

Hi Mitchell. Psychosis is a serious psychiatric condition that can be induced or triggered by AI. “AI psychosis” in this context is a misuse of a clinical term. Your tweet describes a disagreement on a value judgment that boils down to “move fast and break things” with high trust in AI outputs vs going all in on quality and reliability with low trust in AI. It’s an engineering tradeoff like any other.

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.

Psychosis does not require hallucinations. Delusions are sufficient.

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.

Yes. I was offering examples. Again, having a difference of opinion is not a delusion.

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.

I don't think this is all psychosis but more like extreme groupthink.

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

https://en.wikipedia.org/wiki/Folie_%C3%A0_deux

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.

I just thought that instead of psychosis it's just regular groupthink

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

Maybe the difference would be the level of absurdity that's accepted

I would add to this that there's actually a social function to "costly" beliefs, which is that they signal allegiance to the in-group.

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.

That is true, it's beneficial for social survival.

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

I'm not sure that it has to be on a consciousness levels. I think it can be explained by anxiety/fear.

Yeah, It could be fear of rejection or not fitting in.

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 think it is more about "knowing when to shut up" than about actually believing when it comes to sudden dominating group think. It is very clear in politics where a wing on some issue go silent and then suddenly appears way later.

But do these people have a logic on when to shut up?

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.

Would you prefer it be called reality distortion field? People use slang, woke scolding the internet isn't going to change that.

Having a difference of opinion can absolutely be a delusion. For example, I think you're probably not God. If you thought you were God, then we'd disagree, and you'd also be delusional.

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.

was looking for this comment. this post is highly inappropriate and very inaccurate. this should be at the top. too many people are throwing around the word psychosis without knowing what it means. if someone is truely going through psychosis you get them help!

He uses "AI psychosis" as a description of people that are overzealous on AI. He is obviously not a person that can or would diagnose mental illness.

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.

Yeah, but AI psychosis can also be used to mean the stronger thing that the parent comment refers to -- something like AI-induced psychosis, which was how I originally understood the term:

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...

I am aware of the conflict between medical and slang semantics. This doesn't change my commentary.

Well, I agree with you that the parent comment is wrong inasmuch as it suggests we can't tell from context that mitchellh is using the term to mean "a value judgment" instead of "a form of psychosis". We can tell.

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".

People would understand what he meant if he called someone awkward “autistic” too. It’s wrong to use medical terms as slang because it erases the actual meaning and disregards the lived experience of people who have been through the condition. People who have been around psychosis would come to the same conclusion. The majority of the population not having that exposure doesn’t make it right. It’s tasteless and inappropriate.

It's also harmful to overly gatekeep the term autism to the point where a lot of legitimate uses are discouraged, and it happens a lot, if you let it.

If the tweet had called his friends autistic, would that be a legitimate use?

Yes.

Using terms from domain metaphorically in another is a common and, I think, useful way of communication. While a view like yours has genuine merit, especially for a subset of the population who have experience personal or otherwise, with the medical condition, I think it's overly restrictive and counter productive to label it as outright tasteless and inappropriate.

"unable to tell what is real" is an an accurate characterization of the people he's describing imo.

I’ve had to do a ton of SQL stuff lately, which I haven’t really worked with since the late 90s. ChatGPT has been a godsend, not just for me, but for our only coworker who knows SQL well, whom I’d probably be bugging several times a day at my wits’ end.

But no one cares about those kinds of productivity gains. Just the ones that will completely replace us.

I'm the old school type who writes out a document that explains what I plan on doing in markdown even if it's generic like "a window with x and y buttons" and the logic flow and then use that to have ai write a plan with me before I send it off to execute it. This has worked super well.

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)

I'm always amazed by those comments. Why couldn't you buy a book on SQL[0], and spend a week on it? Or just go over to YouTube for a refresher?

[0]: Like https://www.oreilly.com/library/view/sql-queries-for/9780134...

When you have a general idea of what smells bad vs what's okay...why?

I'd rather get it from the LLM and review

This is fine for a moderately sized query. When your queries start taking in 8 joins and 20 fields per table because you're running queries on Presto with 5 TB of data, not only is it drastically better at writing (because it doesn't mess up the fields), you can ask it to try the query 5 different ways to help you land on the most optimal.

This is a great example of AI tech-debt and fragility.

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.

This feels wrong. 8 joins is almost certainly reporting stuff, not transactional. Contrary to what some SQL-averse devs think, 300 lines of SQL is actually more maintainable than the equivalent ~1000 lines of application code. It's also much faster. And I do think that's the real conversion, because SQL is a much higher level language than currently available application languages. It's also declarative in nature, which helps maintainance.

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.

Yes but developers (or at least web backend developers, who are the ones I interact with the most) are extremely averse to SQL and normalization.

I think that's what was meant by "reporting stuff, not transactional".

That's exactly where I would expect it to fail somewhere, changing some part of the query every time it writes one.

In my experience, Claude (at least Opus and Sonnet) is pretty good about not misremembering itself.

I think you may be describing the experience of 6-12 months ago.

I'm amazed you think that instead of using an LLM that someone will go buy a book and spend a week learning something that, judging by the fact that they last used it 30 years ago, likely won't be relevant for them soon.

It's not only that I rarely use it, it's also that it's ugly. It's Relational Cobol. It's as loveable as Oracle. The vendor specific dialects don't even agree on how to do recursive queries do they?

Unfortunately I am very good at forgetting things I resented having to learn, and SQL is definitively one of them.

So you don’t understand what you generate with ai and think that it will be a solution for a problem you can only solve using sql.

No, it's easy enough to understand the query once the AI has generated it. I have looked up how to do it many times after all.

Yes

If the AI's query pulled what I intended to pull, why should I care to understand the SQL any more than I should understand the Query Plan or the Machine Code?

As with regex, querying is about not getting what you don't want as much as it is about getting what you want. And the former of the two is much more difficult to verify.

There's nothing wrong with using SQL only when you know in advance exactly which records you wish to query.

But if you ever need to query unknown data, then probably you should learn SQL a bit deeper.

Extremely weird take.

SQL is (was?) one of my strongest skills, I enjoy it a lot, and I still reach for the LLM. It's just faster than me, and when it goes wrong (rarely) I can correct it in plain English.

Simple, because books don't earn OpenAI and Anthropic a dime.

A book on .... SQL? What is this, the 1970s?

I find SQL and data(bases) in general to be LLM’s Achilles’ heel. Databases are rarely under version control, so the training data only has one half of the knowledge.

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.

That's interesting - SQL is one of the places I find them the strongest - I think there must be an insane amount of training data out there for SQL. But mostly I'm asking them for ad hoc report queries. Nobody cares if they're bad SQL, they just want to know how many signups there were in March that didn't tick the marketing box. Sounds like you're pushing their capabilities a lot further than I am though - I just want to perform arbitarily complex queries on 3NF data.

Yeah not sure what this guy is talking about, LLMs excel with queries because the SQL language is pretty small in scope and its easy to test the output. Table structure and relationships are easy to feed to the AI.

> 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

"Nobody cares if they're bad SQL"

Laid off your DBAs I see.

Ok, ok. Nobody who matters cares if they're bad SQL ;)

Just use an LLM to make a good knowledge base for the databases. Based on schema info and production queries. An agent can use that to write queries that work.

> outsourcing their decision making and thinking to AI and not really about using AI itself

> 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.

relevant Derek Sivers article "Delegate, don't Abdicate" https://sive.rs/abdicate

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.

It’s really frustrating too because even just the plain language translation and pattern matching aspects have such incredible uses.

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”.

The worst part of AI is that the time to produce software has become entirely unpredictable. "If Claude is randomly good at this, and happens to be up today, it will take me about 3 hours. If Claude is randomly bad at this task, or has downtime, 2 weeks"

What I'm seeing is a little eternal September of support tickets about programs that fail to interface the JSON API of a customer of mine. The API is always allucinated. In the best case there are out of place attributes. Often they don't exist at all. I've seen x, y, width, height when we have only top and left. Of course no human read the documentation. Those are probably founders vibe coding a client without the technical competence of understanding the API doc on Postman. That is understandable. Unfortunately they don't even have the competence of pointing their AI to Postman in the right way. My custumer assessed that they will always find a way to do a mistake despite any mitigation from our side. What I do is replying to those tickets with line by line comments of the allucinated JSON. I never talk about AIs because I might hurt the pride of some of them and, who knows, some little mistakes could be from real junior developers. Sometimes the tickets are followed up by more puzzled ones, sometimes they fix the problem. Probably they copy and paste my reply to their bots.

> Probably they copy and paste my reply to their bots.

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've heard the same thing mentioned by a close friend building integrations. They are helping/supporting real use cases but they decided not to help vibe coder founders without an understanding of how APIs work etc. It's just too big of a gap to cover even for larger companies with strong support.

Seeing this too. Customer support tickets are all AI now. The random bolded words, the em dashes, they way where if you KNOW what is actually happening, they are slightly off or just WAY off.

If you were tapped into AI first features you'd design aliases in your api so AI hallucinated api exists for next time

Create a <domain>.tld/llms.txt or some SKILL.md files. When I encounter these tickets I just share links to these resources and the problem goes away.

That's why I made an API LLMs can call to search fastcomments APIs: https://docs.fastcomments.com/guide-llm-kit.html

Several people I know have already gone through phases like this. When you're doing it alone there is a moderating factor when their friends and family start calling them out on their behavior or weird things they say.

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.

I suspect we're going to see this in many corporate environments soon, if we aren't already

> 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 is exactly what is happening. instead of building true AI culture around thoughtful adoption of AI strengths while defending against weaknesses, they're coming up with bullshit heuristics like "every repo has a CLAUDE.md", watching private token usage dashboards, and terrorizing everyone into doing it (or lose your job).

this leads to naive AI adoption, which is the worst of both worlds (no real speedup, out sourcing thinking, ai slop PRs, skill rot).

I have a friend that is a junior in a security-oriented sys-admin/network engineer type role. They have been doing the job for only a bit over a year. No background in programming.

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!

There has never been a better time to be in incident response and adjacent fields.

From what I have seen, most corporate it security people are at a service desk level at best. They are tool runners who don't really understand what the tools spit out, they just go bug other teams about it.

I didn’t think just offloading your thinking to AI was AI psychosis.

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.

> 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

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.

> 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 the loss of that?

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.

Wow, okay. Reading a whole relationship into that sort of interaction is way less reasonable, although now that I think about it a somewhat similar thing happened to Geordi La Forge once...

Including a very awkward followup when he met the person his was based on.

It’s not just way less reasonable, it’s depressing. I feel like a new drug was released and I’m watching multiple friends succumb to it.

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.

I'm curious how to best define what AI psychosis actually is.

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.

You speak like a bot and are a brand new account. Thank you for whoever set this up to add to the problem.

Thank you for trying to help address the bot problem, but this is a false positive.

Well how did you go from a green account that said it was created 1 hour ago when I responded to one saying it was made in 2024.

@dang is this a bug?

the proof is left as an exercise for the reader

I’m not even claiming negatives against you now. You were a green account in my UI and it said it was created 1 hour ago when I made my initial comment.

The UI is now showing different information and a comment from years ago so I am genuinely curious if it’s a bug in the forum software.

How do you have so many crazy friends?

I work in software and don’t come from the upper class sending their kids into faangs for their first job at the tender age of 28.

Were kinda predisposed to mental illness as a group, not too surprised that a new source of insanity pushed a few over the edge.

People who don't come from upper class and work in software are predisposed to mental illness?

Am I reading this wrong, or can you explain?

They have healthcare and support structures

Blanket statement, I have been flamed so much for them here.

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.

If you’re trying to say that the wealthy have it just as hard as the poor I would ask you to step off a cliff under the claim that gravity doesn’t exist.

I am not, it seems you are misunderstanding.

That is correct but then the statement becomes so broad it is useless. Of course wealthy people have it easier but that is a useless statement.

Let me guess you want to abolish the capital system bla bla bla

No, I want fully automated gay space luxury communism.

I also happen to believe that capitalism is the best system to get us from our current scarcities to that sort of utopic future.

It appears you're inferring a _lot_ that was not said. I think both posters in this thread are misunderstanding eachother.

Why even say anything so thin as "wealthy have it better than poor people"

No way!

I'm going directly to the point here: those people have clearly mental issues that would and probably did already show in the past without AI as well.

Would they, though? Current AI stuff is delivering something functionally nonexistent in human history before this: absolute sycophancy, 24/7, on demand, for anyone who wants it. People joke about the wealthy becoming detached from reality because of yes-men, but this is a stage beyond even the capability of the most dedicated brown-noser.

I agree that these people had mental health issues. I think if they got to billionaire level and were surrounded by yes men they would have the same reaction.

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.

That is a possibility indeed, I agree. There are mild mental issues that might have gone under the radar before and are now magnified by the AI sycophancy. I'm no mental health expert so I can't really tell but it does make some intuitive sense.

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.

The way I put this to myself is that AI gives “correct correct answers and incorrect correct answers”.

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.

It’s simpler than that - it’s a guessing machine that has superior access to a whole load of information and capacity to process at a speed at which we humans cannot compete.

Does it make it better than us? No because ultimately the thing itself doesn’t ‘know’ right from wrong.

Better according to what standard?

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!

I used to think otherwise, but the older I get the more I think you are correct on this one.

in an inflationary monetary system you need to spin the hamster wheel faster than the money printer. all the way until it all falls apart...

Yeah, very often the issue is that some context is missing. It'll say something true, but which misses the bigger point, or leads to a suboptimal result. Or it interprets an ambiguous thing in one specific way, when the other meaning makes more sense. You have to keep your wits about you to catch these things.

It's an incredible tool but it's also very derpy sometimes, full of biases, blind spots etc.

The way I phrase this to others is: Language models produce linguistically valid sentences, not factually correct sentences.

> which is arguably more challenging than creating the solution.

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!

Aren't we ignoring the elephant in the room ?

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.

when you outsource thinking to AI, you get that magical speed up. the agent is making decisions for you, so things move at agent speed. it often makes decisions without telling you, and the final "here's the plan" output often requires you to understand the problem at great depth, which requires return to human speed, so you skim and just approve.

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.

> 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.

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.

Can concur. I would say I am doing 3 things per day now instead of 1.

I agree with you, except it isn't even good at writing code. Almost every time that you get an LLM to write a bunch of code for you, it has mistakes in it. The logic isn't right, the API calls aren't right, the syntax isn't right (!). That problem hasn't yet been fixed and it looks as though it never will be. That means that every line of code it generates, you have to review, because even if 95% of the code is correct, you need to find the 5% which isn't. But if you have to do that, it becomes slower than just writing the code yourself. As people have pointed out over and over again: typing in the code was never the part that took time. So I don't agree that LLMs are really useful for writing code.

LLMs are good at producing code that seems plausible at first glance and appears to work, but it never really does. And when trying to fix things, you discover 7 slightly different ad hoc implementations of the same thing, with their own weird edge cases and behaviors. And you likely miss 4 more. There is no intention or coherence behind any of it.

> if you just prompt the AI and believe what it tell you then you have AI psychosis

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”

I wouldn’t say they have an undefined truth value. Their source of truth is their training data. The problem is that human text is not tightly coupled to the capital T truth.

Nor is the LLM output tightly coupled to the training data. They'll "eagerly"[1] fill in the blanks wherever it sounds good.

[1] here I don't mean to imply agency, just vigor.

“Toked out” is really, really good, thank you for this

I wonder how different this is from having companies let Fortune or Inc magazine do their thinking for them.

Or random consultants.

Is "AI said it was a good idea" and worse than "we were following industry trends"?

> 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.

Though there is some overlap in software development. Like for example using heavy-weight dependencies, that try to follow the one size fits all approach, when one could use a much simpler, faster or even no dependency at all. The LLMs will readily suggest quickly adding that huge dependency, that is mentioned in beginner tutorials. Or suggest to use regex for parsing HTML.

(Real example, had this from Kimi 2.6 recently, lol.)

this author suggest its essentially the same risk https://www.poppastring.com/blog/what-we-lost-the-last-time-.... i feel its heightened because execs and leaders are absolutely salivating over the opportunity to fire thousands of humans with no regard for the cognitive debt that comes from outsourcing thinking to ai.

> companies and people outsourcing their decision making and thinking to AI

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.

It’s almost as if we haven’t learned anything from Hans the horse, Ouija boards, "facilitated communication", or the countless examples of the folly of surrounding yourself with yes men. The point about improv is spot on.

He uses AI himself, so I agree he doesn't see AI use as black/white.

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.

share the prompt!

For a start, invert - ask about the exact opposite in a separate session.

I’ll second this. Great way to recalibrate yourself, once you see it confidently assert the exact opposite statement.

https://claude.ai/settings/general (Instructions for Claude)

---

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).

We're trying to outsmart The Genie(a Jinn) now. He will deliver according to the letter of the prompt but not the spirit of it.

Just add "do what I'm intending to ask, not what I actually asked" and it'll be fine.

Works on genies too, or so I'm told by Clod.

I've found just asking it to be "critical but constructive", goes a long long way.

> Treat my claims as hypotheses, not decisions. Before agreeing with a proposed change, state the strongest case against it. [...]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.

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.

I am starting to come around to a similar sentiment. I have seen several large projects cook now for almost a year are not done. These are not trivial projects but the leads are heavily using ai at every opportunity.

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.

> 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

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’ve been talking to a lot of engineers about how they use AI in their day to day and it’s dramatically different than what you see from the hypers.

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.

I digress; this article actually has helped identify useful knowledge gaps around topics I have researched. https://drensin.medium.com/elephants-goldfish-and-the-new-go...

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.

I've been strictly using LLM's to either push stuff that I've done plenty times before and are mostly boilerplate or have zero value for writing them by hand (not even educational), and I always ENSURE that they work on stuff that are easily verifiable and proven incorrect with my existing knowledge or a few minutes of googling.

If you think you can let AI write code without double checking you have AI psychosis.

If you prefer reviewing AI-written code over writing it yourself, you just have odd preferences from my perspective (but not psychosis).

What does 'prefer' mean here?

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.

Part of the psychosis are AI usage mandates, where companies require a certain amount of LLM usage per worker. Of course these things are useful, but forcing them on workers is psychotic.

Ai gives generic answer for ideas but it's great for code. Pattern matching works for one not the other.

> 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.

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.

I think the author means that we as homosapiens cant stop talking about this new shinny hammer we just invited

>but if you just prompt the AI and believe what it tell you then you have AI psychosis.

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.

> Do you believe what teachers told you in school? Yes?

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.

There's a huge difference between a teacher giving outdated information representing what was once our (or at least their) best understanding of the world, and a chatbot that just randomly makes up things for no reason while insisting that it's all true.

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.

What is "thinking"?

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.

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