I enjoyed reading theses perspectives, they are reasoned and insightful.
I'm undecided about my stance for gen AI in code. We can't just look at the first order and immediate effects, but also at the social, architectural, power and responsibility aspects.
For another area, prose, literature, emails, I am firm in my rejection of gen AI.
I read to connect with other humans, the price of admission is spending the time.
For code, I am not as certain, nowadays I don't regularly see it as an artwork or human expression, it is a technical artifact where craftsmanship can be visible.
Will gen AI be the equivalent of a compiler and in 20 years everyone depends on their proprietary compiler/IDE company?
Can it even advance beyond patterns/approaches that we have built until then?
I have many more questions and few answers and both embracing and rejecting feels foolish.
Given how fast the Open Source models have been able to catch up their closed-source counterparts, I think at least on the model/software side this will be a non-issue. The hardware situation is a bit grimmer, especially with the recent RAM prices. Time will tell: if in 2–3 years time, we can get to a situation where a 512GB–1TB VRAM / unified memory + good fp8 rig is a few thousands and not tens of thousands of dollars, we'll probably be good.
This has already happened or happening quite fast with cloud. Where setting up own data center, or even few servers could be crime against humanity if it does not use whole Kubernetes/Devops/Observability stack.
This is my immediate concern as well. Sam said in an interview that he sees "intelligence" as a utility that companies like OpenAI would own and rent out.
The problem is the cat is already out of the bag on the technology. Anyone can go over to Huggingface, follow a cookbook [0], and build their own models from the ground up. He cannot prevent that from taking place or other organizations releasing full open weight/open training data models as well, on permissive licenses, which give individuals access to be able to modify those models as they see fit. Sam wishes he had control over that but he doesn't nor will he ever.
Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it, since the end product ("intelligence") can be swapped out with little concern over who is providing it.
> Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it
I believe this is the natural end-state for LLM based AI but the danger of these companies even briefly being worth trillions of dollars is that they are likely to start caring about (and throwing lobbying money around) AI-related intellectual property concerns that they've never shown to anyone else while building their models and I don't think it is far fetched to assume they will attempt all manner of underhanded regulatory capture in the window prior to when commoditization would otherwise occur naturally.
All three of OpenAI, Google and Anthropic have already complained about their LLMs being ripped off.
The industry and the wider world are full steam ahead with AI, but the following takes (from the article) are the ones that resonate with me. I don't use AI directly in my work for reasons similar to those expressed here[1].
For the record, I'll use it as a better web search or intro to a set of ideas or topic. But i no longer use it to generate code or solutions.
I just completely shifted my mindo n that as well. I used to think I can just ai code everything, but it just worked because I started at a good codebase that I built after a while it was the AIs codebase and neither it, nor me could really work in it, till I entangled it.
>It takes care and careful engineering to produce good results. One must work to keep the models within the flight envelope. One has to carefully structure the problem, provide the right context and guidance, and give appropriate tools and a good environment. One must think about optimizing the context window; one must be aware of its limitations.
In other words, one has to lean into the exact opposite tendencies of those which generally make people reach for AI ;)
I'm not sure there is a "normal" tendency to reach for AI. But there is certainly parallel in that, say, javascript and PHP have a reputation of being preferred by barely able people who make interesting and useful things with atrocious code.
I've seen rust codebases that would make you cry along with perfectly well architected applications written in both perl and php. You're just playing into common language silo stereotypes. A competent developer can author code in their language of choice whatever that may be. I'm not sure "reaching for AI" implies anything besides that some folk prefer that tool for their work. I personally don't have a tendency to reach for AI, but that doesn't somehow imply they or I are "lesser" because of it.
Sure, people are not perfect, but there are established common values that we don't need to convey in a prompt.
With AI, despite its usefulness, you are never sure if it understands these values. That might be somewhat embedded in the training data, but we all know these properties are much more swayable and unpredictable than those of a human.
It was never about the LLM to begin with.
If Linus Torvalds makes a contribution to the Linux kernel without actually writing the code himself but assigns it to a coding assistant, for better or worse I will 100% accept it on face value. This is because I trust his judgment (I accept that he is fallible as any other human). But if an unknown contributor does the same, even though the code produced is ultimately high quality, you would think twice before merging.
I mean, we already see this in various GitHub projects. There are open-source solutions that whitelist known contributors and it appears that GitHub might be allowing you to control this too.
Prioritizing or deferring to existing contributors happens in pretty much every human endeavor.
As you point out this of course predates the age of LLM, in many ways it's basic human tribal behavior.
This does have its own set of costs and limitations however. Judgement is hard to measure. Humans create sorting bonds that may optimize for prestige or personal ties over strict qualifications or ability. The tribe is useful, but it can also be ugly. Perhaps in a not too distant future, in some domains or projects these sorts of instincts will be rendered obsolete by projects willing to accept any contribution that satisfies enough constraints, thereby trading human judgement for the desired mix of velocity and safety. Perhaps as the agents themselves improve this tension becomes less an act of external constraint but an internal guide. And what would this be, if not a simulation of judgement itself?
You could also do it in stages, ie have a delegated agent promote people to some purgatory where there is at least some hope of human intervention to attain the same rights and privileges as pre-existing contributors, that is if said agent deems your attempt worthy enough. Or maybe to fight spam an earnest contributor will have to fork over some digital currency, to essentially pay the cost of requesting admission.
All of these scenarios are rather familiar in terms of the history of human social arrangements.
That is just to say, there is no destruction of the social contract here. Only another incremental evolution.
The problem is that it acts as an accountability sink even when it is attached.
I've had multiple coworkers over the past few months tell me obvious, verifiable untruths. Six months ago, I would have had a clear term for this: they lied to me. They told me something that wasn't true, that they could not possibly have thought was true, and they did it to manipulate me into doing what they want. I would have demanded and their manager would have agreed that they need to be given a severe talking to.
But now I can't call it a lie, both in the sense that I've been instructed not to and in the sense that it subjectively wasn't. They honestly represented what the agent told them was the truth, and they honestly thought that asking an agent to do some exploration was the best way to give me accurate information.
What's the replacement norm that will prevent people from "flooding the zone" with false AI-generated claims shaped to get people to do what they want? Even if AI detection tools worked, which I emphasize that they do not, they wouldn't have stopped the incidents that involved human-generated summaries of false AI information.
I forgot to mention why I brought up the idea of who is making the contribution rather than how (i.e., through an LLM).
Right now, the biggest issue open-source maintainers are facing is an ever-increasing supply of PRs. Before coding assistants, those PRs didn't get pushed not because they were never written (although obviously there were fewer in quantity) but because contributors were conscious of how their contributions might be perceived. In many cases, the changes never saw the light of day outside of the fork.
LLMs don't second-guess whether a change is worth submitting, and they certainly don't feel the social pressure of how their contribution might be received. The filter is completely absent.
So I don't think the question is whether machine-generated code is low quality at all, because that is hard to judge, and frankly coding assistants can certainly produce high-quality code (with guidance). The question is who made the contribution. With rising volumes, we will see an increasing amount of rejections.
By the way, we do this too internally. We have a script that deletes LLM-generated PRs automatically after some time. It is just easier and more cost-effective than reviewing the contribution. Also, PRs get rejected for the smallest of reasons.
If it doesn't pass the smell test moments after the link is opened, it get's deleted.
> LLMs don't second-guess whether a change is worth submitting, and they certainly don't feel the social pressure of how their contribution might be received. The filter is completely absent.
Of course you could have an agent on your side do this, so I take you to mean a LLM that submits a PR and is not instructed to make such a reflection will not intrinsically make it as a human would, that is as a necessary side effect of submitting in the first place (though one might be surprised).
It would be curious to have an API that perhaps attempts to validate some attestation about how the submitting LLM's contribution was derived, ie force that reflection at submission time with some reasonable guarantees of veracity even if it had yet to be considered. Perhaps some future API can enforce such a contract among the various LLMs.
You cannot say that breaking the social contract (the fabric of society, if you will) is generally a good thing, although I am sure some will find opportunities for growth.
After all, the phoenix must burn to emerge, but let's not romanticise the fire.
The title is misleading. It says in one of the first sentences:
> The comments within do not represent “the Rust project’s view” but rather the views of the individuals who made them. The Rust project does not, at present, have a coherent view or position around the usage of AI tools; this document is one step towards hopefully forming one.
So calling this "Rust Project Perspectives on AI" is not quite right.
I feel bad for people who reject LLMs on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
I strongly doubt that is going to be the case - picking up these tools is not rocket science, even if you want to be able to use them fairly effectively. In addition, there is so much churn in AI tooling these days that an early investment might not really be worth a lot in the longer run.
On the other hand, hands-on experience in programming and architecture is currently a must-have to use the tools effectively - and continuing without AI in the short term might just buy an inexperienced engineer some time to learn, and postpone skill atrophy for an experienced engineer.
Of course, who can know what the future looks like, but I doubt a "wait and see" approach is that dangerous to anyone's career.
Asking it to do something isn't exactly complicated. At the very least, it's way easier than actually coding so why would you expect people to struggle with writing? There's no skill required in using LLMs, that's kinda the point.
LLMs are very easy to pick up, the point of them for their makers is to commoditize skill and knowledge, you can't be left behind in learning to use them, AI providers don't have economic incentives to make them into anything other than appliances.
The people more at risk of being left behind are the ones that don't learn when not to trust their output.
I don't necessarily agree with the LLM moral objection, but this point of view is unconvincing. Change the topic to say, slavery, and the "I feel bad for those who reject slavery on moral grounds, they'll fall behind..." argument becomes fairly absurd.
You're essentially saying the very concept of a moral objection is to be pitied. Maybe you believe that's true but I'd say that reflects poorly on our values today.
I feel bad for people who reject Windows 11 on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
I feel bad for people who reject lying/stealing/cheating/corruption/backstabbing on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
The goal that AI-Megacorp CEOs have been pushing lately is "super intelligence" and so if that's where you truly think we are rapidly heading, what's the risk for those of us not hyper-invested in AI? This "super intelligence" (by definition) will be able to understand us both equally well, so all these "prompting skills" people claim sets them apart from people who don't use AI that much will be utterly pointless.
This is just the typical FOMO nonsense pushed by AI fans.
It's the exact same as seen with many past hypes, and every time the result is a lot more nuanced than those fans claim. It wasn't that long ago that people were claiming MongoDB was going to revolutionize the world and make relational databases obsolete, or how cryptocurrencies were going to change the world, or NFTs, and the list goes on.
I feel bad for people who accept AI. They're going to wind up just as replaced by it as I will, but it will somehow come as a surprise to them despite the writing being on the wall for ages
I imagine there will be a lot of regrets in the future from people that were early adopters that eventually got pushed out by the AI they love so much
Regret? Of what? The tech is here. You won't slow it down by not using it. People need to either adapt by moving to more and more niche areas, or become the person to be retained when the efficiency gains materialize. We still don't have the proper methodology figured out, but people are working on it.
That said, I'd agree that people who currently claim 20x speedups will indeed be replaced.
Seems like a lot of people’s problems with AI come from talking to the dumber models and having it not provide sufficient proof that it fixed a bug. Maybe instead of banning AI, projects should set a minimum smarts level. e.g. to contribute, you must use gpt-5.4-codex high or better for either writing it or code reviewing it.
I enjoyed reading theses perspectives, they are reasoned and insightful.
I'm undecided about my stance for gen AI in code. We can't just look at the first order and immediate effects, but also at the social, architectural, power and responsibility aspects.
For another area, prose, literature, emails, I am firm in my rejection of gen AI. I read to connect with other humans, the price of admission is spending the time.
For code, I am not as certain, nowadays I don't regularly see it as an artwork or human expression, it is a technical artifact where craftsmanship can be visible.
Will gen AI be the equivalent of a compiler and in 20 years everyone depends on their proprietary compiler/IDE company?
Can it even advance beyond patterns/approaches that we have built until then?
I have many more questions and few answers and both embracing and rejecting feels foolish.
I'm worried about a few big companies owning the means of production for software and tightening the screws.
Given how fast the Open Source models have been able to catch up their closed-source counterparts, I think at least on the model/software side this will be a non-issue. The hardware situation is a bit grimmer, especially with the recent RAM prices. Time will tell: if in 2–3 years time, we can get to a situation where a 512GB–1TB VRAM / unified memory + good fp8 rig is a few thousands and not tens of thousands of dollars, we'll probably be good.
This has already happened or happening quite fast with cloud. Where setting up own data center, or even few servers could be crime against humanity if it does not use whole Kubernetes/Devops/Observability stack.
This is my immediate concern as well. Sam said in an interview that he sees "intelligence" as a utility that companies like OpenAI would own and rent out.
The problem is the cat is already out of the bag on the technology. Anyone can go over to Huggingface, follow a cookbook [0], and build their own models from the ground up. He cannot prevent that from taking place or other organizations releasing full open weight/open training data models as well, on permissive licenses, which give individuals access to be able to modify those models as they see fit. Sam wishes he had control over that but he doesn't nor will he ever.
[0] https://huggingface.co/docs/transformers/index
Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it, since the end product ("intelligence") can be swapped out with little concern over who is providing it.
> Hopefully it continues to get commoditized to the point where no monopoly can get a stranglehold on it
I believe this is the natural end-state for LLM based AI but the danger of these companies even briefly being worth trillions of dollars is that they are likely to start caring about (and throwing lobbying money around) AI-related intellectual property concerns that they've never shown to anyone else while building their models and I don't think it is far fetched to assume they will attempt all manner of underhanded regulatory capture in the window prior to when commoditization would otherwise occur naturally.
All three of OpenAI, Google and Anthropic have already complained about their LLMs being ripped off.
https://www.latimes.com/business/story/2026-02-13/openai-acc...
https://cloud.google.com/blog/topics/threat-intelligence/dis...
https://fortune.com/2026/02/24/anthropic-china-deepseek-thef...
Which is a wildly hypocritical tack for them to take considering how all their models were created, but I certainly wouldn’t be surprised if they did.
The industry and the wider world are full steam ahead with AI, but the following takes (from the article) are the ones that resonate with me. I don't use AI directly in my work for reasons similar to those expressed here[1].
For the record, I'll use it as a better web search or intro to a set of ideas or topic. But i no longer use it to generate code or solutions.
1. https://nikomatsakis.github.io/rust-project-perspectives-on-...
I just completely shifted my mindo n that as well. I used to think I can just ai code everything, but it just worked because I started at a good codebase that I built after a while it was the AIs codebase and neither it, nor me could really work in it, till I entangled it.
>It takes care and careful engineering to produce good results. One must work to keep the models within the flight envelope. One has to carefully structure the problem, provide the right context and guidance, and give appropriate tools and a good environment. One must think about optimizing the context window; one must be aware of its limitations.
In other words, one has to lean into the exact opposite tendencies of those which generally make people reach for AI ;)
I'm not sure there is a "normal" tendency to reach for AI. But there is certainly parallel in that, say, javascript and PHP have a reputation of being preferred by barely able people who make interesting and useful things with atrocious code.
I've seen rust codebases that would make you cry along with perfectly well architected applications written in both perl and php. You're just playing into common language silo stereotypes. A competent developer can author code in their language of choice whatever that may be. I'm not sure "reaching for AI" implies anything besides that some folk prefer that tool for their work. I personally don't have a tendency to reach for AI, but that doesn't somehow imply they or I are "lesser" because of it.
It does to executives who sign the checks to ai usage contracts
AI ultimately breaks the social contract.
Sure, people are not perfect, but there are established common values that we don't need to convey in a prompt.
With AI, despite its usefulness, you are never sure if it understands these values. That might be somewhat embedded in the training data, but we all know these properties are much more swayable and unpredictable than those of a human.
It was never about the LLM to begin with.
If Linus Torvalds makes a contribution to the Linux kernel without actually writing the code himself but assigns it to a coding assistant, for better or worse I will 100% accept it on face value. This is because I trust his judgment (I accept that he is fallible as any other human). But if an unknown contributor does the same, even though the code produced is ultimately high quality, you would think twice before merging.
I mean, we already see this in various GitHub projects. There are open-source solutions that whitelist known contributors and it appears that GitHub might be allowing you to control this too.
https://github.com/orgs/community/discussions/185387
Prioritizing or deferring to existing contributors happens in pretty much every human endeavor.
As you point out this of course predates the age of LLM, in many ways it's basic human tribal behavior.
This does have its own set of costs and limitations however. Judgement is hard to measure. Humans create sorting bonds that may optimize for prestige or personal ties over strict qualifications or ability. The tribe is useful, but it can also be ugly. Perhaps in a not too distant future, in some domains or projects these sorts of instincts will be rendered obsolete by projects willing to accept any contribution that satisfies enough constraints, thereby trading human judgement for the desired mix of velocity and safety. Perhaps as the agents themselves improve this tension becomes less an act of external constraint but an internal guide. And what would this be, if not a simulation of judgement itself?
You could also do it in stages, ie have a delegated agent promote people to some purgatory where there is at least some hope of human intervention to attain the same rights and privileges as pre-existing contributors, that is if said agent deems your attempt worthy enough. Or maybe to fight spam an earnest contributor will have to fork over some digital currency, to essentially pay the cost of requesting admission.
All of these scenarios are rather familiar in terms of the history of human social arrangements.
That is just to say, there is no destruction of the social contract here. Only another incremental evolution.
An agent is still attached to an accountable human. If it is not, ignore it.
How do you figure out which is the case, at scale?
You don't.
The problem is that it acts as an accountability sink even when it is attached.
I've had multiple coworkers over the past few months tell me obvious, verifiable untruths. Six months ago, I would have had a clear term for this: they lied to me. They told me something that wasn't true, that they could not possibly have thought was true, and they did it to manipulate me into doing what they want. I would have demanded and their manager would have agreed that they need to be given a severe talking to.
But now I can't call it a lie, both in the sense that I've been instructed not to and in the sense that it subjectively wasn't. They honestly represented what the agent told them was the truth, and they honestly thought that asking an agent to do some exploration was the best way to give me accurate information.
What's the replacement norm that will prevent people from "flooding the zone" with false AI-generated claims shaped to get people to do what they want? Even if AI detection tools worked, which I emphasize that they do not, they wouldn't have stopped the incidents that involved human-generated summaries of false AI information.
I forgot to mention why I brought up the idea of who is making the contribution rather than how (i.e., through an LLM).
Right now, the biggest issue open-source maintainers are facing is an ever-increasing supply of PRs. Before coding assistants, those PRs didn't get pushed not because they were never written (although obviously there were fewer in quantity) but because contributors were conscious of how their contributions might be perceived. In many cases, the changes never saw the light of day outside of the fork.
LLMs don't second-guess whether a change is worth submitting, and they certainly don't feel the social pressure of how their contribution might be received. The filter is completely absent.
So I don't think the question is whether machine-generated code is low quality at all, because that is hard to judge, and frankly coding assistants can certainly produce high-quality code (with guidance). The question is who made the contribution. With rising volumes, we will see an increasing amount of rejections.
By the way, we do this too internally. We have a script that deletes LLM-generated PRs automatically after some time. It is just easier and more cost-effective than reviewing the contribution. Also, PRs get rejected for the smallest of reasons.
If it doesn't pass the smell test moments after the link is opened, it get's deleted.
> LLMs don't second-guess whether a change is worth submitting, and they certainly don't feel the social pressure of how their contribution might be received. The filter is completely absent.
Of course you could have an agent on your side do this, so I take you to mean a LLM that submits a PR and is not instructed to make such a reflection will not intrinsically make it as a human would, that is as a necessary side effect of submitting in the first place (though one might be surprised).
It would be curious to have an API that perhaps attempts to validate some attestation about how the submitting LLM's contribution was derived, ie force that reflection at submission time with some reasonable guarantees of veracity even if it had yet to be considered. Perhaps some future API can enforce such a contract among the various LLMs.
> AI ultimately breaks the social contract
Business schools teach that breaking the social contract is a disruption opportunity for growth, not a negative,
The Hacker in Hacker News refers to "growth hacking" now, not hacking code
It depends who you ask.
You cannot say that breaking the social contract (the fabric of society, if you will) is generally a good thing, although I am sure some will find opportunities for growth.
After all, the phoenix must burn to emerge, but let's not romanticise the fire.
> You cannot say that breaking the social contract (the fabric of society, if you will) is generally a good thing
I am not saying it's a good thing, just that it's a common attitude here
I suppose it didn't come through in my original post, but I was trying to be critical
Generational churn breaks social contract.
You all using Latin and believing in the old Greek gods to honor the dead?
Muricans still owning slaves from Africa?
All ways in which old social contracts were broken at one point.
We are not VHS cassettes with an obligation to play out a fuzzy memory of history.
The title is misleading. It says in one of the first sentences:
> The comments within do not represent “the Rust project’s view” but rather the views of the individuals who made them. The Rust project does not, at present, have a coherent view or position around the usage of AI tools; this document is one step towards hopefully forming one.
So calling this "Rust Project Perspectives on AI" is not quite right.
Maybe "Rust maintainers' perspectives on AI" or "Rust contributors' perspectives on AI" would be better?
Correct. This is one internal draft by someone quoting some other people's positions but not speaking for any other positions.
Not speaking for others, but Niko's writing is IMO strongly shading the wording used to describe positions that do or don't align with his own views.
I took it as meaning "perspectives of people in the Rust Project about AI."
I feel bad for people who reject LLMs on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
On the falling behind:
I strongly doubt that is going to be the case - picking up these tools is not rocket science, even if you want to be able to use them fairly effectively. In addition, there is so much churn in AI tooling these days that an early investment might not really be worth a lot in the longer run.
On the other hand, hands-on experience in programming and architecture is currently a must-have to use the tools effectively - and continuing without AI in the short term might just buy an inexperienced engineer some time to learn, and postpone skill atrophy for an experienced engineer.
Of course, who can know what the future looks like, but I doubt a "wait and see" approach is that dangerous to anyone's career.
Why would anybody who rejects them on moral grounds pick them up later? It isn't a discussion of lateness, it's a discussion of opting out.
Asking it to do something isn't exactly complicated. At the very least, it's way easier than actually coding so why would you expect people to struggle with writing? There's no skill required in using LLMs, that's kinda the point.
The point is that people who reject them on moral grounds won't be using them, irrespective of whether they are easy to use.
LLMs are very easy to pick up, the point of them for their makers is to commoditize skill and knowledge, you can't be left behind in learning to use them, AI providers don't have economic incentives to make them into anything other than appliances.
The people more at risk of being left behind are the ones that don't learn when not to trust their output.
> The people more at risk of being left behind are the ones that don't learn when not to trust their output.
Or the ones who fall out of practice writing software themselves because they've been relying on AI to do all the work.
(Or the same, but with "long-form English text" instead of "software".)
They'll get left behind in the same sense that 1980s professionals who refused to touch computers got left behind.
I don't necessarily agree with the LLM moral objection, but this point of view is unconvincing. Change the topic to say, slavery, and the "I feel bad for those who reject slavery on moral grounds, they'll fall behind..." argument becomes fairly absurd.
You're essentially saying the very concept of a moral objection is to be pitied. Maybe you believe that's true but I'd say that reflects poorly on our values today.
No, he's saying this specific moral objection is to be pitied.
When I say "I feel bad for people who feel a need to own guns", I'm not saying I feel bad for people who feel a need to lock their doors at night.
I feel bad for people who reject Windows 11 on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
https://shkspr.mobi/blog/2026/03/im-ok-being-left-behind-tha...
I feel bad for people who reject lying/stealing/cheating/corruption/backstabbing on moral grounds. They'll likely fall behind, while also having to live in a world increasingly built around something they see as immoral.
People who reject those things don't get left behind... In fact, they tend to live more successful lives and spend less time in prison.
This is total FUD.
The goal that AI-Megacorp CEOs have been pushing lately is "super intelligence" and so if that's where you truly think we are rapidly heading, what's the risk for those of us not hyper-invested in AI? This "super intelligence" (by definition) will be able to understand us both equally well, so all these "prompting skills" people claim sets them apart from people who don't use AI that much will be utterly pointless.
This is just the typical FOMO nonsense pushed by AI fans.
It's the exact same as seen with many past hypes, and every time the result is a lot more nuanced than those fans claim. It wasn't that long ago that people were claiming MongoDB was going to revolutionize the world and make relational databases obsolete, or how cryptocurrencies were going to change the world, or NFTs, and the list goes on.
> They'll likely fall behind
So far this doesn't seem to be the case, despite it being repeated endlessly over the last few years.
>while also having to live in a world increasingly built around something they see as immoral
Should people just decide that things they think are immoral are actually fine and get over it? Doesnt really seem coherent...
> So far this doesn't seem to be the case, despite it being repeated endlessly over the last few years.
For most professional roles today, using LLMs is a must. It's probably as important as using Google, if not more.
> Should people just decide that things they think are immoral are actually fine and get over it? Doesnt really seem coherent...
No, hence why I feel bad for them.
When the moral perspective isn't that sound and isn't that important, yeah, they usually do. Everyone gets tired of complaining.
Are the people who aren’t born or haven’t even entered a workforce also falling behind?
Yeah that's why you go to school, learn, get trained etc..
I feel bad for people who accept AI. They're going to wind up just as replaced by it as I will, but it will somehow come as a surprise to them despite the writing being on the wall for ages
I imagine there will be a lot of regrets in the future from people that were early adopters that eventually got pushed out by the AI they love so much
Regret? Of what? The tech is here. You won't slow it down by not using it. People need to either adapt by moving to more and more niche areas, or become the person to be retained when the efficiency gains materialize. We still don't have the proper methodology figured out, but people are working on it.
That said, I'd agree that people who currently claim 20x speedups will indeed be replaced.
> You won't slow it down by not using it.
Then why is it forced into everywhere and everyone and everything?
Because they don't want you to realize that you have the power to reject garbage then have the government punish them for creating such waste.
If enough people refuse to use it then we can absolutely slow it down
So I'm doing that. Even if I don't expect to "win" in the end, I'm doing what I think is right
Maybe one day I'll be vindicated
At the very least I can look my kids in the eye when they're working age that I didn't happily help bring in their bleak futures.
There must be plenty of people who "accept" it in a fatalistic manner, where the final result will not be a surprise.
Anything that uses the phrase "diverse perspectives" is not worth reading.
Seems like a lot of people’s problems with AI come from talking to the dumber models and having it not provide sufficient proof that it fixed a bug. Maybe instead of banning AI, projects should set a minimum smarts level. e.g. to contribute, you must use gpt-5.4-codex high or better for either writing it or code reviewing it.
doesn’t matter if you use the best model
I use Opus 4.6 almost exclusively and it still generates nonsense if I don’t guide it.