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.
Humans are vital for non-craftsmanship reasons. Human curiosity and the ability to grok the big picture was vital in detecting the XZ backdoor attempt. If there is an wholesale AI-takeover, I don't think such attacks would have been detected 5 years in the future.
AI will make future attacks much easier for several reasons: changes ostensibly by multiple personas but actually controled by the same entity. Maintainers who are open to AI-assisted contributions will accept drive-by contributions, and will likely have less time to review each contribution in depth, and will have a narrower context than the attacker on each PR.
AI-generated code fucks with trust and reputation: I trust the code I generate [1] with or without AI, I trust AI-generated code by others far less than their manually generated code. I'm not aure what the repercussions are yet.
1. I am biased and likely over-optimistic about the security and number of bugs.
Just make sure that you isolate whatever is generated so that if you ever decide that copyright means something to you after all that you don't end up with a worthless codebase.
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-...
In other words, one has to lean into the exact opposite tendencies of those which generally make people reach for AI ;)
Of course it's possible, (computers are very fast in this century!), it's just that the kind of people who prioritize that, don't tend to use those languages!
(There's lunatics like me who take pride in shipping eight kilobyte browser games. But not many, I suspect ;)
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.
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.
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.
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.
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.
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
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 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.
I don't know what most people are doing in their day to day with AI but this is the closest to reality I have seen thus far. I have seen posts on here about how they have 4 agents making 50kloc a day or something and I can't reliably get a complete spec to output 50 lines of commit worthy code. Emphasis on reliable and commit worthy. I won't go into pros and cons, but I just don't see how everyone is even operating like this, especially with a team of people and any semblance of legacy code. Note, by legacy I do not mean old bad code, I mean pre existing code from various contributors.
For research on crates/integrations, I see some benefits, but sometimes I think it is because search engines have been enshittified and inundated with the top 100 results of nearly all queries being AI slop. 10 out of 10 times I would rather ping a person. Lately I have been assuming most pro-ai articles are written by LLMs or advertising campaigns and ignore it. It's working well so far. Still a top performer on my team...
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.
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.
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.
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".)
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...
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.
https://shkspr.mobi/blog/2026/03/im-ok-being-left-behind-tha...
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.
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.
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
That said, I'd agree that people who currently claim 20x speedups will indeed be replaced.
> 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 use Opus 4.6 almost exclusively and it still generates nonsense if I don’t guide it.
