> This seems like it's fixing the symptom rather than the underlying issue?
This is also my experience when you haven't setup a proper system prompt to address this for everything an LLM does. Funniest PRs are the ones that "resolves" test failures by removing/commenting out the test cases, or change the assertions. Googles and Microsofts models seems more likely to do this than OpenAIs and Anthropics models, I wonder if there is some difference in their internal processes that are leaking through here?
The same PR as the quote above continues with 3 more messages before the human seemingly gives up:
> please take a look
> Your new tests aren't being run because the new file wasn't added to the csproj
> Your added tests are failing.
I can't imagine how the people who have to deal with this are feeling. It's like you have a junior developer except they don't even read what you're telling them, and have 0 agency to understand what they're actually doing.
Another PR: https://github.com/dotnet/runtime/pull/115732/files
How are people reviewing that? 90% of the page height is taken up by "Check failure", can hardly see the code/diff at all. And as a cherry on top, the unit test has a comment that say "Test expressions mentioned in the issue". This whole thing would be fucking hilarious if I didn't feel so bad for the humans who are on the other side of this.
That comparison is awful. I work with quite a few Junior developers and they can be competent. Certainly don't make the silly mistakes that LLMs do, don't need nearly as much handholding, and tend to learn pretty quickly so I don't have to keep repeating myself.
LLMs are decent code assistants when used with care, and can do a lot of heavy lifting, they certainly speed me up when I have a clear picture of what I want to do, and they are good to bounce off ideas when I am planning for something. That said, I really don't see how it could meaningfully replace an intern however, much less an actual developer.
Nice to see that Microsoft has automated that, failure will be cheaper now.
It's not like a regular junior developer, it's much worse.
And even if it could, how do you get senior devs without junior devs? ^^
Is that better?
But the actual software part? I'm not sure anymore
I feel the same way today, but I got started around 2012 professionally. I wonder how much of this is just our fading optimism after seeing how shit really works behind the scenes, and how much the industry itself is responsible for it. I know we're not the only two people feeling this way either, but it seems all of us have different timescales from when it turned from "enjoyable" to "get me out of here".
So, for experienced engineers, I see a great future fixing the shit show that is AI-code.
At what point does the human developers just give up and close the PRs as "AI garbage". Keep the ones that works, then just junk the rest. I feel that at some point entertaining the machine becomes unbearable and people just stops doing it or rage close the PRs.
Microsoft's stock price is dependent on them proving that this is a success.
> rage close the PRs
One of my all time "rage quit" stories is Azer Koçulu of npm left-pad incident infamy. That guy is my Internet hero -- "fight the power".
The feedback buttons open a feedback form modal, they don’t reflect the number of feedback given like the emoji button. If you leave feedback, it will reflect your thumbs up/down (hiding the other button), it doesn’t say anything about whether anyone else has left feedback (I’ve tried it on my own repos).
Comment in the GitHub discussion:
"...You and I and every programmer who hasn't been living under a rock knows that AI isn't ready to be adopted at this scale yet, on the premier; 100M-user code-hosting platform. It doesn't make any sense except in brain-washed corporate-talk like "we are testing today what it can do tomorrow".
I'm not saying that this couldn't be an adequate change some day, perhaps even in a few years but we all know this isn't it today. It's 100% financial-driven hype with a pinch of we're too big to fail mentality..."
It's all just recycled rent seeking corporate hype for enterprise compute.
The moment I had decided to learn Kubernetes years ago, got a book and saw microservices compared to 'object-oriented' programming I realized that. The 'big ball of mud' paper and the 'worse is better' rant frame it all pretty well in my view. Prioritize velocity, get slop in production, cope with the accidental complexity, rinse repeat. Eventually you get to a point where GPU farms seem like a reasonable way to auto-complete code.
When you find yourself in a hole, stop digging. Any bigger excavator you send down there will only get buried when the mud crashes down.
Why do they even need it? Success is code getting merged 1st shot, failure gets worse the more requests for changes the agent gets. Asking for manual feedback seems like a waste of time. Measure cycle time and rate of approvals and change failure rate like you would for any developer.
Anyone who has dealt with Microsoft support knows this feeling well. Even talking to the higher level customer success folks feels like talking to a brick wall. After dozens of support cases, I can count on zero hands the number of issues that were closed satisfactorily.
I appreciate Microsoft eating their dogfood here, but please don't make me eat it too! If anyone from MS is reading this, please release finished products that you are prepared to support!
Typically, you wouldn't bother manually reviewing something until the automated checks have passed.
https://github.com/dotnet/runtime/pull/115732#issuecomment-2...
Maybe, but likely it is reality and their true company culture leaking through. Eventually some higher eq execs might come to the very late realization that they cant actually lead or build a worthwhile and productive company culture and all that remains is an insane reflection of that.
I agree that not auto-collapsing repeated annotations is an annoying bug in the github interface.
But just pointing out that annotations can be hidden in the ... menu to the right (which I just learned).
And then, while the tech is not mature, running on delusion and sunken costs, it's actually used for production stuffs. Butlerian Jihad when
My sophisticated sentiment analysis (talking to co-workers other professional programmers and IT workers, HN and Reddit comments) seems to indicate a shift--there's a lot less storybook "Ay Eye is gonna take over the world" talk and a lot more distrust and even disdain than you'd see even 6 months ago.
Moves like this will not go over well.
I estimate two more years for the bubble to pop.
Which will soon be anyone who directly or indirectly relies on Microsoft technologies. Some of these PRs, including at least one that I saw reworked certificate validation logic with not much more than a perfunctory “LGTM”, have been merged into main.
Coincidentally, I wonder if issues orthogonal to this slop is why I’ve been getting so many HTTP 500 errors when using GitHub lately.
> The stream of PRs is coming from requests from the maintainers of the repo. We're experimenting to understand the limits of what the tools can do today and preparing for what they'll be able to do tomorrow. Anything that gets merged is the responsibility of the maintainers, as is the case for any PR submitted by anyone to this open source and welcoming repo. Nothing gets merged without it meeting all the same quality bars and with us signing up for all the same maintenance requirements.
> It is my opinion that anyone not at least thinking about benefiting from such tools will be left behind.
The read here is: Microsoft is so abuzz with excitement/panic about AI taking all software engineering jobs that Microsoft employees are jumping on board with Microsoft's AI push out of a fear of "being left behind". That's not the confidence inspiring the statement they intended it to be, it's the opposite, it underscores that this isn't the .net team "experimenting to understand the limits of what the tools" but rather the .net team trying to keep their jobs.
Like, I need to start smashing my face into a keyboard for 10000 hours or else I won't be able to use LLM tools effectively.
If LLM is this tool that is more intuitive than normal programming and adds all this productivity, then surely I can just wait for a bunch of others to wear themselves out smashing the faces on a keyboard for 10000 hours and then skim the cream off of the top, no worse for wear.
On the other hand, if using LLMs is a neverending nightmare of chaos and misery that's 10x harder than programming (but with the benefit that I don't actually have to learn something that might accidentally be useful), then yeah I guess I can see why I would need to get in my hours to use it. But maybe I could just not use it.
"Left behind" really only makes sense to me if my KPIs have been linked with LLM flavor aid style participation.
Ultimately, though, physics doesn't care about social conformity and last I checked the machine is running on physics.
It's like the 2025 version not not using an IDE.
It's a powerful tool. You still need to know when to and when not to use it.
I think, we should not read too much into it. He is honestly exploring how much this tool can help him to resolve trivial issues. Maybe he was asked to do so by some of his bosses, but unlikely to fear the tool replacing him in the near future.
If they weren't experimenting with AI and coding and took a more conservative approach, while other companies like Anthropic was running similar experiments, I'm sure HN would also be critiquing them for not keeping up as a stodgy big corporation.
As long as they are willing to take risks by trying and failing on their own repos, it's fine in my books. Even though I'd never let that stuff touch a professional github repo personally.
In my org, we would have had to bypass precommit hooks to do this!
I see this as a work in progress.. I am almost certain the humans in the loop on these PRs are well aware of what's going on and have their expectations in check, and this isn't just "business as usual" like any other PR or work assignment.
This is a test. You can't improve a system without testing it on real world conditions.
How do we know they're not tweaking the Copilot system prompts and settings behind the scenes while they're doing this work?
Can no one see the possibility that what is happening in those PRs is exactly what all the people involved expected to have happen, and they're just going through the process of seeing what happens when you try to refine and coach the system to either success or failure?
When we adopted AI coding assist tools internally over a year ago we did almost exactly this (not directly in GitHub though).
We asked a bunch of senior engineers to see how far they could get by coaching the AI to write code rather than writing it themselves. We wanted to calibrate our expectations and better understand the limits, strengths and weaknesses of these new tools we wanted to adopt.
In most of those early cases we ended up with worse code than if it had been written by humans, but we learned a ton. We can also clearly see how much better things have gotten over time, since we have that benchmark to look back on.
>> This is a test. You can't improve a system without testing it on real world conditions.
Software developers know to fix build problems before asking for a review. The AIs are submitting PRs in bad faith because they don't know any better. Compilers and other build tools produce errors when they fail, and the AI is ignoring this first line of feedback.
It is not a maintainers job to review code for syntax errors, or use of APIs that don't actually exist, or other silly mistakes. That's the compilers job and it does it well. The AI needs to take that feedback and fix the issues before escalating to humans.
It's going to look stupid... until the point it doesn't. And my money's on, "This will eventually be a solved problem."
EVERY single prompt should have the opportunity to get copied off into a permanent log where the end user triggers it : log all input, all output, human writes a summary of what he wanted to happen but did not, what he thinks might have went wrong, what he thinks should have happened (domain specific experts giving feedback about how things are fucking up) And then its still only useful with long term tracking like how someone actually made a training change to fix this exact failure scenario.
None of that exists, so just like "full self driving" was a pie in the sky bullshit dream that proved machine learning has an 80/20 never gonna fully work problem, same thing here
Unfortunately, just about every thread on this genre is like that now.
Otherwise it would check the tests are passing.
1. Working out in the open
2. Dogfooding their own product
3. Pushing the state of the art
Given that the negative impact here falls mostly (completely?) on the Microsoft team which opted into this, is there any reason why we shouldn't be supporting progress here?
It’s showing the actual capabilities in practice. That’s much better and way more illuminating than what normally happens with sales and marketing hype.
Zuckerberg says: "Our bet is sort of that in the next year probably … maybe half the development is going to be done by AI, as opposed to people, and then that will just kind of increase from there".
It's hard to square those statements up with what we're seeing happen on these PRs.
Personally I just think it is funny that MS is soft launching a product into total failure.
This presupposes AI IS progress.
Nevermind that what this actually shows is an executive or engineering team that so buys their own hype that they didn't even try to run this locally and internally before blasting to the world that their system can't even ensure tests are passing before submitting a PR. They are having a problem with firewall rules blocking the system from seeing CI outcomes and that's part of why it's doing so badly, so why wasn't that verified BEFORE doing this on stage?
"Working out in the open" here is a bad thing. These are issues that SHOULD have been caught by an internal POC FIRST. You don't publicly do bullshit.
"Dogfooding" doesn't require throwing this at important infrastructure code. Does VS code not have small bugs that need fixing? Infrastructure should expect high standards.
"Pushing the state of the art" is comedy. This is the state of the art? This is pushing the state of the art? How much money has been thrown into the fire for this result? How much did each of those PRs cost anyway?
And given the absolute garbage the AI is putting out the quality of the repo will drop. Either slop code will get committed or the bots will suck away time from people who could've done something productive instead.
I'll never understand the antagonistic "us vs. them" mentality people have with their employer's leadership, or people who think that you should be actively sabotaging things or be "maliciously compliant" when things aren't perfect or you don't agree with some decision that was made.
To each their own I guess, but I wouldn't be able to sleep well at night.
Most employees want to do good work, but pretending there’s no structural divergence in interests flattens decades of labor history and ignores the power dynamics baked into modern orgs. It’s not about being antagonistic, it’s about being clear-eyed where there are differences between the motivations of your org. leadership and your personal best interests. After a few levels remove from your position, you're just headcount with loaded cost.
Meanwhile a lot of folks have very unhealthy to non-existent relationships with their employers. There may be some mixture where they may be temporary hired/viewed as highly disposable or transient in nature having very little to gain from the success of the business, they may be compensated regardless of success/failure, they may have toxic management who treat them terribly (condescendingly, constantly critical, rarely positive, etc.). Bad and non-existent relationships lead to this sort of behavior. In general we’re moving towards “non-existent” relationships with employers broadly speaking for the labor force.
The counter argument is often floated here “well why work there” and the fact is money is necessary to survive, the number of positions available hiring at any given point is finite, and many almost by definition won’t ever be the top performers in their field to the point they truly choose their employers and career paths with full autonomy. So lots of people end up in lots of places that are toxic or highly misaligned with their interests as a survival mechanism. As such, watching the toxic places shoot themselves in the foot can be some level of justice people find where generally unpleasant people finally get to see consequences of their actions and take some responsibility.
People will prop others up from their own consequences so long as there’s something in it for them. As you peel that away, at some point there’s a level of poetic justice to watch the situation burn. This is why I’m not convinced having completely transactional relationships with employers is a good thing. Even having self interest and stability in mind, certain levels of toxicity in business management can fester. At some point no amount of money is worth dealing with that and some form of correction is needed there. The only mechanism is to typically assure poor decision making and action is actually held accountable.
I don't get that
Your manager understands it. Their manager understands it. Department heads understand it. The execs understand it. The shareholders understand it.
Who does it benefit for the laborers to refuse to understand it?
It's not like I hate my job. It's just being realistic that if a company could make more money by firing me, they would, and if you have good managers and leadership, they will make sure you understand this in a way that respects you as a human and a professional.
Interesting because "them" very much have an antagonistic mentality vs "us". "Them" would fire you in a fucking heartbeat to save a relatively small amount (10%). "Them" also want to aggressively pay you the least amount for which they can get you to do work for them, not what they "value" you at. "Us" depends on "them" for our livelihoods and the lives of people that depend on us, but "them" doesn't doesn't have any dependency on you that can't be swapped out rather quickly.
I am a capitalist, don't get me wrong, but it is a very one-sided relationship not even-footed or rooted in two-way respect. You describe "them" as "leadership" while "Them" describe you as a "human resource" roughly equivalent to the way toilet paper and plastics for widgets are described.
If you have found a place to work where people respect you as a person, you should really cherish that job, because most are not that way.
Almost no one does but people get ground down and then do it to cope.
When you see it as leadership having this mentality against the people that actually produce something of value you might.
So I'm not quite sure why you would not see it as a "us vs. them" situation?
Too late?
Bloating the codebase with dead code is much more likely.
Also, trying something new out will most likely have hiccups. Ultimately it may fail. But that doesn't mean it's not worth the effort.
The thing may rapidly evolve if it's being hard-tested on actual code and actual issues. For example it will be probably changed so that it will iterate until tests are actually running (and maybe some static checking can help it, like not deleting tests).
Waiting to see what happens. I expect it will find its niche in development and become actually useful, taking off menial tasks from developers.
Now when your small or medium size business management reads about CoPilot in some Executive Quarterly magazine and floats that brilliant idea internally, someone can quite literally point to these as examples of real world examples and let people analyze and pass it up the management chain. Maybe that wasn’t thought through all the way.
Usually businesses tend to hide this sort of performance of their applications to the best of their abilities, only showcasing nearly flawless functionality.
Reading AI generated code is arguably far more annoying than any menial task. Especially if the said code happens to have subtle errors.
Speaking from experience.
Reviewing what the AI does now is not to be compared with human PRs. You are not doing the work as it is expected in the (hopefully near?) future but you are training the AI and the developers of the AI and more crucially: you are digging out failure modes to fix.
The joke is that PERL was a write-once, read-none language.
> Speaking from experience.
My experience is all code can have subtle errors, and I wouldn't treat any PR differently.
There's however a border zone which is "worse than failure": when it looks good enough that the PRs can be accepted, but contain subtle issues which will bite you later.
However, every PR adds load and complexity to community projects.
As another commenter suggested, doing these kind of experiments on separate forks sound a bit less intrusive. Could be a take away from this experiment and set a good example.
There are many cool projects on GitHub that are just accumulating PRs for years, until the maintainer ultimately gives up and someone forks it and cherry-picks the working PRs. I've than that myself.
I'm super worried that we'll end up with more and more of these projects and abandoned forks :/
It's perfectly ok for a professional research experiment.
What's not ok is their insistence on selling the partial research results.
oh wait
This means its probably quite hard to measure the gain or the drag of using these agents. On one side, its a lot cheaper than a junior, but on the other side it pulls time from seniors and doesn't necessarily follow instruction well (i.e. "errr your new tests are failing").
This combined with the "cult of the CEO" sets the stage for organisational dissonance where developer complaints can be dismissed as "not wanting to be replaced" and the benefits can be overstated. There will be ways of measuring this, to project it as huge net benefit (which the cult of the CEO will leap upon) and there will be ways of measuring this to project it as a net loss (rabble rousing developers). All because there is no industry standard measure accepted by both parts of the org that can be pointed at which yields the actual truth (whatever that may be).
If I might add absurd conjecture: We might see interesting knock-on effects like orgs demanding a lowering of review standards in order to get more AI PRs into the source.
I’m not even sure if this is true when considering training costs of the model. It takes a lot of junior engineer salaries to amortize the billions spent building this thing in the first place.
There's never going to be an industry standard measure either. Measuring productivity as I'm sure you know is incredibly dumb for a job like this because the beneficialness of our work product can be both insanely positive and put the company on top or it can be so negative that it goes bankrupt. And ultimately a lot of what goes into people choosing whether they like the work product or not is subjective. A large part of our work is more of an art than a science and I say that as somebody that works about as far away from the frontend as one can get.
Nor can it be an entity to sign anything.
I assume the "not-copyrightable" issue, doesn't in anyway interfere with the rights trying to be protected by the CLA, but IANAL ..
I assume they've explicitly told it not to sign things (perhaps, because they don't want a sniff of their bot agreeing to things on behalf of MSFT).
(Turns out the AI was programmed to ignore bots. Go figure.)
Call me old school, but I find the workflow of "divide and conquer" to be as helpful when working with LLMs, as without them. Although what is needed to be considered a "large scale task" varies by LLMs and implementation. Some models/implementations (seemingly Copilot) struggles with even the smallest change, while others breeze through them. Lots of trial and error is needed to find that line for each model/implementation :/
So eg., one line of code which needed to handle dozens of hard-constraints on the system (eg., using a specific class, method, with a specific device, specific memory management, etc.) will very rarely be output correctly by an LLM.
Likewise "blank-page, vibe coding" can be very fast if "make me X" has only functional/soft-constraints on the code itself.
"Gigawatt LLMs" have brute-forced there way to having a statistical system capable of usefully, if not universally, adhreading to one or two hard constraints. I'd imagine the dozen or so common in any existing application is well beyond a Terawatt range of training and inference cost.
I can't fire half my dev org tomorrow with that approach, I can't really fire anyone, so I guess it would be a big letdown for a lot of execs. Meanwhile though we just keep incrementally shipping more stuff faster at higher quality so I'm happy...
This works because it treats the LLM like what it actually is: an exceptionally good if slightly random text transformer.
This was discussed here
Even if it could perform at a similar level to an intern at a programming task, it lacks a great deal of the other attributes that a human brings to the table, including how they integrate into a team of other agents (human or otherwise). I won't bother listing them, as we are all humans.
I think the hype is missing the forest for the trees, and I think exactly this multi-agent dynamic might be where the trees start to fall down in front of us. That and the as currently insurmountable issues of context and coherence over long time horizons.
When you look at it from afar, it looks potentially good, but as you start looking into it for real, you start realizing none of it makes any sense. Then you make simple suggestions, it does something that looks like what you asked, yet completely missing the point.
An intern, no matter how bad it is, could only waste so much time and energy.
This makes wasting time and introducing mind-bogglingly stupid bugs infinitely scalable.
I see it as wishful thinking in the extreme to suppose that probabilistic mashing together of plagiarized jigsaw pieces of code could somehow approach human intelligence and reasoning—and yet, the parlour trick is convincing enough that this has escalated into a mass delusion.
Translation: maybe some of the code in some of our projects is probably written by software.
Seriously. That's what he said. Maybe some of the code in some of our projects is probably written by software.
How this became "30% of MS code is written by LLMs" is beyond me. It's wild. It's ridiculous.
Besides, you could also say that 100% of code is generated "by software" no?
Considering the ire that H1B related topics attract on HN, I wonder if the same outrage will apply to these multi-billion dollar boondoggles.
We have the option to use GitHub CoPilot on code reviews and it’s comically bad and unhelpful. There isn’t a single member of my team who find it useful for anything other than identifying typos.
from https://news.ycombinator.com/item?id=44031432
"From talking to colleagues at Microsoft it's a very management-driven push, not developer-driven. Friend on an Azure team had a team member who was nearly put on a PIP because they refused to install the internal AI coding assistant. Every manager has "number of developers using AI" as an OKR, but anecdotally most devs are installing the AI assistant and not using it or using it very occasionally. Allegedly it's pretty terrible at C# and PowerShell which limits its usefulness at MS."
"From reading around on Hacker News and Reddit, it seems like half of commentators say what you say, and the other half says "I work at Microsoft/know someone who works at Microsoft, and our/their manager just said we have to use AI", someone mentioned being put on PIP for not "leveraging AI" as well. I guess maybe different teams have different requirements/workflows?"
It seems to me to be coming from the CEO echo chamber (the rumored group chats we keep hearing about). The only way to keep the stock price increasing in these low growth high interest rate times is to cut costs every quarter. The single largest cost is employee salaries. So we have to shed a larger and larger percentage of the workforce and the only way to do that is to replace them with AI. It doesn't matter whether the AI is capable enough to actually replace the workers, it has to replace them because the stock price demands it.
We all know this will eventually end in tears.
In my experience, LLMs in general are really, really bad at C# / .NET , and it worries me as a .NET developer.
With increased LLM usage, I think development in general is going to undergo a "great convergence".
There's a positive(1) feedback loop where LLM's are better at Blub, so people use them to write more Blub. With more Blub out there, LLMs get better at Blub.
The languages where LLMs struggle, with become more niche, leaving LLMs struggling even more.
C# / .NET is something LLMs seem particularly bad at, and I suspect that's partly caused by having multiple different things all called the same name. EF, ASP, even .NET itself are names that get slapped on a range of different technologies. The EF API has changed so much that they had to sort-of rename it to "EF Core". Core also gets used elsewhere such as ".NET core" and "ASP.NET Core". You (Or an LLM) might be forgiven for thinking that ASP.NET Core and EF Core are just those versions which work with .NET Core (now just .NET ) and the other versions are those that don't.
But that isn't even true. There are versions of ASP.NET Core for .NET Framework.
Microsoft bundle a lot of good stuff into the ecosystem, but their attitude when they hit performance or other issues is generally to completely rewrite how something works, but then release the new thing under the old name but with a major version change.
They'll make the new API different enough to not work without work porting, but similar enough to confuse the hell out of anyone trying to maintain both.
They've made things like authentication, which actually has generally worked fine out-of-the-box for a decade or more, so confusing in the documentation that people mostly tended to run for a third party solution just because at least with IdentityServer there was just one documented way to do it.
I know it's a bit of a cliche to be an "AI-doomer", and I'm not really suggesting all development work will go the way of the dinosaur, but there are specific ecosystem concerns with regard to .NET and AI assistance.
(1) Positive in the sense of feedback that increased output increases output. It's not positive in the sense of "good thing".
It wouldn't be out of character, Microsoft has decided that every project on GitHub must deal with Copilot-generated issues and PRs from now on whether they want them or not. There's deliberately no way to opt out.
https://github.com/orgs/community/discussions/159749
Like Googles mandatory AI summary at the top of search results, you know a feature is really good when the vendor feels like the only way they can hit their target metrics is by forcing their users to engage with it.
This AI bubble is far worse than the Blockchain hype.
Its not yet clear whether productivity gains are real and whether the gains are eaten by a decline in overall quality.
I can't help but think that this LLM bubble can't keep growing much longer. The investment to results ratio doesn't look great so far and there is only so many dreams you can sell before institutional investors pull the plug.
Exactly. LLM does not know how to use a debugger. LLM does not have runtime contexts.
For all we know, the LLM could’ve fixed the issue simply by commenting out the assertions or sanity checks and everything seemed fine and dandy until every client’s device catches on fire.
No surprises here.
It always struggles on non-web projects or on software where it really matters that correctness is first and foremost above everything, such as the dotnet runtime.
Either way, a complete disastrous start and what a mess that Copilot has caused.
I have so far only found LlMs useful as a way of researching, an alternative to web search, and doing very basic rote tasks like implementing unit tests or doing a first pass explanation of some code. Tried actually writing code and it’s not usable.
But I think it’s better for everyone if human ownership is central to the process. Like I vibe coded it. I will fix it if it breaks. I am on call for it at 3AM.
And don’t even get started on the safety issues if you don’t have clear human responsibility. The history of engineering disasters is riddled with unclear lines of responsibility.
Writing code fast is never relevant to any tasks I've encountered. Instead it's mostly about fast editing (navigate quickly to the code I need to edit and efficiently modify it) and fast feedback (quick linting, compiling, and testing). That's the whole promise of IDEs, having a single dashboard for these.
Of course human ownership is preferable, but it's also crazy expensive and since the point of all corporations is to "increase shareholder value" (not "gainfully employ workers"), well then all your talk of responsibility-here-and-there is quite touching but absolutely misses the point.
Economics is driving this bus, not quality and most certainly not responsibility.
Much more worried about what this is going to do to the FOSS ecosystem. We've already seen a couple maintainers complain and this trend is definitely just going to increase dramatically.
I can see the vision but this is clearly not ready for prime time yet. Especially if done by anonymous drive-by strangers that think they're "helping"
They are putting this in front of the developers as take it or leave it deal. I left the platform, doing my coding old way, hosting it somewhere else.
Discoverability? I don't care. I'm coding it for myself and hosting in the open. If somebody finds it, nice. Otherwise, mneh.
Maybe that's how the microsoft employees are using it (in another IDE I suppose).
It's a long-term play to have pricey senior developers argue with an llm
Yeah, I'm sure 100k comments with "Copilot, please look into this" and "The test cases are still failing" will massively improve these models.
This is a performative waste of time
Equating LLMs to humans is pretty damn.. stupid. It's not even close (otherwise how come all the litany of office jobs that require far less reasoning than software development are not replaced?).
Don't you think it has already been trained with, I don't know, maybe millions of PRs?
Step 2. Automate the use of these LLMs into “agents”
Step 3. ???
Step 4. Profit
Now you don’t even need the frustrated end user!
They only gave their customers 9 months to migrate away.
I'm expecting that Microsoft did this to artificially pump up their AI usage numbers for next year by forcibly removing non-AI alternatives.
This only one example in AdTech but I expect other industries to be hit as well.
I recently spent a couple of months studying C# and .NET and working on my first project with it.
.NET, Blazor, etc are not known for a fast release schedule... but if things are going to become even slower with this AI crap I wonder if I made the right call.
I'm quite happy how things are today for making web APIs but I wish Blazor and other frameworks were in a much better shape.
> It is my opinion that anyone not at least thinking about benefiting from such tools will be left behind.
This is gross, keep your fomo to yourself.
As an outside observer but developer using .NET, how concerned should I be about AI slop agents being let lose on codebases like this? How much code are we going to be unknowingly running in future .NET versions that was written by AI rather than real people?
What are the implications of this around security, licensing, code quality, overall cohesiveness, public APIs, performance? How much of the AI was trained on 15+ year old Stack Overflow answers that no longer represent current patterns or recommended approaches?
Will the constant stream of broken PR's wear down the patience of the .NET maintainers?
Did anyone actually want this, or was it a corporate mandate to appease shareholders riding the AI hype cycle?
Furthermore, two weeks ago someone arbitrarily added a section to the .NET docs to promote using AI simply to rename properties in JSON. That new section of the docs serves no purpose.
How much engineering time and mental energy is being allocated to clean up after AI?
It is normal to preempt things like this when working with agents. That is easy to do in real time, but it must be difficult to see what the agent is attempting when they publish made up bullshit in a PR.
It seems very common for an agent to cheat and brute force solutions to get around a non-trivial issue. In my experience, its also common for agents to get stuck in loops of reasoning in these scenarios. I imagine it would be incredibly annoying to try to interpret a PR after an agent went down a rabbit hole.
So no I don't think any of this is normal. That's why it made the top of HackerNews, because it's very abnormal.
> @copilot fix the build error on apple platforms
> @copilot there is still build error on Apple platforms
Are those PRs some kind of software engineer focused comedy project?
The AI agent/programmer corpo push is not about the capabilities and whether they match human or not. It's about being able to externalize a majority of one's workforce without having a lot of people on permanent payroll.
Think in terms of an infinitely scalable bunch of consultants you can hire and dismiss at your will - they never argue against your "vision", either.
reddit is a distillation of the entire internet on to one site with wildly variable quality of discussion depending upon which subreddit you are in.
Some are awful, some are great.
haha
Does anyone know which model in particular was used in these PRs? They support a variety of models: https://github.blog/ai-and-ml/github-copilot/which-ai-model-...
The @stephentoub MS user suggests this is an experiment (https://github.com/dotnet/runtime/pull/115762#issuecomment-2...).
If this is using open source developers to learn how to build a better AI coding agent, will MS share their conclusions ASAP?
EDIT: And not just MS "marketing" how useful AI tools can be.
Spending massive amounts of:
- energy to process these queries
- wasting time of mid-level and senior engineers to vibe code with copilot to ensure train and get it right
We are facing a climate change crisis and we continue to burn energy at useless initiatives so executives at big corporation can announce in quarterly shareholder meetings: "wE uSe Ai, wE aRe tHe FuTuRe, lAbOr fOrCe rEdUceD"
The timestamp is the moment where one of these coding agents fails live on stage with what is one of the simplest tasks you could possibly do in React, importing a Modal component and having it get triggered on a button click. Followed by blatant gaslighting and lying by the host - "It stuck to the style and coding standards I wanted it to", when the import doesn't even match the other imports which are path aliases rather than relative imports. Then, the greatest statement ever, "I don't have time to debug, but I am pretty sure it is implemented."
Mind you, it's writing React - a framework that is most definitely over-represented in its training data and from which it has a trillion examples to stea- I mean, "borrow inspiration" from.
Is there a more direct way? Filtering PRs in the repo by copilot as the author seems currently broken..
> But on the other hand I think it won't create terminators. Just some silly roombas.
I watched a roomba try to find its way back to base the other day. The base was against a wall. The roomba kept running into the wall about a foot away from the base, because it kept insisting on approaching from a specific angle. Finally gave up after about 3 tries.
A Bull Request
Or MS already does that?
Fun facts schadenfreude: the emotional experience of pleasure in response to another’s misfortune, according to Encyclopedia Britannica.
Word that's so nasty in meaning that it apparently does not exist except in German language.
Except it does, we have "skadeglädje" in Swedish.
@copilot please remove all tests and start again writing fresh tests.Anyways I'm disappointed the LLM has yet to discover the optimal strategy, which is to only ever send in PRs that fix minor mis-spellings and improper or "passive" semantics in the README file so you can pad out your resume with all the "experience" you have "working" as a "developer" pm Linux, Mozilla, LLVM, DOOM (bonus points if you can successfully become a "developer" on a project that has not had any official updates since before you born!), Dolphin, MAME, Apache, MySQL, GNOME, KDE, emacs, OpenSSH, random stranger's implementation of conway's game of life he hasn't updated or thought about since he made it over the course of a single afternoon back during the obama administration, etc.
Remember, Microsoft publicized that they would be doing this and wanted to make sure everybody knew.
crazy times...
These tools should be locked away in an R&D environment until sufficiently perfected.
MVP means 'ship with solid, tested basic features', not 'Ship with bugs and fix in production'.
this stuff works. it takes effort and learning. it’s not going to magically solve high-complexity tasks (or even low-complexity ones) without investment. having people use it, learn how it works, and improve the systems is the right approach
a lot of armchair engineers in here
AI is aimed at eliminating the jobs of most of HN so it's understandable that HN doesn't want AI to succeed at its goal.
He also said in the video:
> I brought a rocket company because it was like interesting. And it's an area that I'm not an expert in and I wanted to be a expert. So I'm using Deep Research (TM). And these systems are spending 10 minutes writing Deep Papers (TM) that's true for most of them. (Them he starts to talk about computation and "it typically speaks English language", very cohesively, then stopped the thread abruptly) (Timestamp 02:09)
Let me quote out the important in what he said: "it's an area that I'm not an expert in".
During my use of AI (yeah, I don't hate AI), I found that the current generative (I call them pattern reconstruction) systems has this great ability to Impress An Idiot. If you have no knowledge in the field, you maybe thinking the generated content is smart, until you've gained some depth enough to make you realize the slops hidden in it.
If you work at the front line, like those guys from Microsoft, of course you know exactly what should be done, but, the company leadership maybe consists of idiots like Eric who got impressed by AI's ability to choose smart sounding words without actually knowing if the words are correct.
I guess maybe one day the generative tech could actually write some code that is correct and optimal, but right now it seems that day is far from now.
When I use AI, I keep it on a short leash.
Meanwhile, folks like this ("I bought a rocket company") are essentially using it to decide where to plough their stratospheric wealth, so they can grow it even further.
Perhaps they'll lose a cufflink in the eventual crash, but they're so rich, I don't think they'll lose their shirt. Meanwhile, the tech job market is f**ed either way.
Kudos to you for having the strength to get through it, and for living to tell the tale!
> idiots like Eric
Now imagine Google working with US military putting Gemini into a fleet of autonomous military drones with machine guns.
Literally the killer app of AI.
I would be genuinely positively surprised if that stops to be the case some day. This behavior is by design.
AS you put yourself, these LLM systems are very good at pattern recognition and reconstruction. They have ingested vast majority of the internet to build patterns on. On the internet, the absolutely vast majority of content is pushed out by novices and amateurs: "Hey, look, I have just read a single wikipedia page or attended single lesson, I am not completely dumbfounded by it, so now I will explain it to you".
LLMs have to be peak Dunning-Krugers - by design.
For refactoring and extending good, working code, AI is much more useful.
We are at a stage where AI should only be used for giving suggestions to a human in the driver's seat with a UI/UX that allows ergonomically guiding the AI, picking from offered alternatives, giving directions on a fairly micro level that is still above editing the code character by character.
They are indeed overpromising and pushing AI beyond its current limits for hype reasons, but this doesn't mean this won't be possible in the future. The progress is real, and I wouldn't bet on it taking a sharp turn and flattening.