Vibe coding kills open source

by kgwgk • 6 months ago

330 285 6 months ago

ktallett• 6 months ago

I think vibe coding would greatly struggle with large open source projects unless your planning was exceptional and your comments on optimal coding style was exceptional, however...... For those small open source tools that many of us use daily and find invaluable, I actually think vibe coding is ideal for that. It can make a functional version quickly and you can iterate and improve it, and feel no loss for making it free to use.

I was very sceptical but I will admit I think vibe coding has a place in society, just what it is yet is still to be determined. It can't help most for sure but it can help some in some situations.

Cthulhu_4• 6 months ago

For those small open source tools that many of us use daily and find invaluable, I actually think vibe coding is ideal for that.

If they don't exist, AND the author is comitted to maintaining them instead of just putting it online, sure. But one issue I see is that a lot of these tools you describe already exist, so creating another one (using code assist tools or otherwise) just adds noise IMO.

The better choice is to research and plan (as you say in your first sentence) before comitting resources. The barrier to "NIH" is lowered through code assistants, which risks reducing collaboration in open source land in favor of "I'll just write my own".

Granted, "I'll write my own" has always felt like it has a lower barrier to entry than "I'm going to search for this tool and learn to use it".

cess11• 6 months ago

The authors try to study the effect of people not engaging directly with OSS projects because they substitute for this with a gang of chatbots, and draw the conclusion that this lack of contact with actual people means they'll be less likely to help finance OSS development.

data-ottawa• 6 months ago

There are three or four projects I've always wanted to do, but were frontloaded with a lot of complexity and drudgery.

Maybe the best feature of vibe coding is that it makes the regret factor of poor early choices much lower. Its kind of magic to go "you know what, I was wrong, let's try this approach instead" and not having to spend huge amounts of time fixing things or rewriting 80% of the project.

It's made it a lot more fun to try building big projects on my own, where I would go into decision paralysis or prematurely optimize and never start the meat or learning of the core project.

Its also been nice to have agents review my projects for major issues, so I feel more confident sharing them.

fc417fc8022• 6 months ago

go into decision paralysis or prematurely optimize

Setting out to implement a feature only to immediately get bogged down in details that I could probably get away with glossing over. LLMs short circuit that by just spitting something out immediately. Of course it's of questionable quality, but once you get something working you can always come back and improve it.

hayd• 6 months ago

I think one of the things that will need to be embraced is carefully curating .md context files to give the prompts better/shared direction to contributors. Things like any new feature or fix should include a test case (in the right place), functions should re-use existing library code wherever possible, function signatures should never change in a backwards-incompatible way, any code changes should pass the linter, etc etc. And ideally ensure the agent writes code that's going to be to the maintainer's "taste".

I haven't worked out how to do this for my own projects.

Once you've set it up it's not too hard to imagine an AI giving an initial PR assessment... to discard the worst AI slop, offer some stylistic feedback, or suggest performance concerns.

Sharlin• 6 months ago

No problem! Just give the agents the ability to autonomously report issues, submit patches, and engage with library authors. Surely nothing can go wrong.

tosh• 6 months ago

generative ai increases ambition, lowers barriers

more open source, better open source

perhaps also more forking (not only absolute but also relative)

contribution dynamics are also changing

I'm fairly optimistic that generative ai is good for open source and the commons

what I'm also seeing is open source projects that had not so great ergonomics or user interfaces in general are now getting better thanks to generative ai

this might be the most directly noticeable change for users of niche open source

avaer4• 6 months ago

What do you think of the paper's research claims that the returns for maintainers are reduced and sharing is decreasing?

positron263• 6 months ago

Without real finance model innovation, what returns?

lukan3• 6 months ago

"Vibe coding raises productivity by lowering the cost of using and building on existing code, but it also weakens the user engagement through which many maintainers earn returns."

I think the title is clickbait.

The conclusion is:

"Vibe coding represents a fundamental shift in how software is produced and consumed. The productivity gains are real and large. But so is the threat to the open source ecosystem that underpins modern software infrastructure. The model shows that these gains and threats are not independent: the same technology that lowers costs also erodes the engagement that sustains voluntary contribution."

The dangers I see rather in projects drowning in LLM slop PR's, instead of less engagement.

And the benefits of LLMs to open source in lowering the cost to revive and maintain (abandoned) projects.

wolfi1• 6 months ago

do you have experience in reviving an abandoned project? which way did you go? what would be a sensible approach?

lukan3• 6 months ago

I am currently in the process of finding out.

LLM's did help with quickly researching dependencies unknown to me and investigating build errors, but ideally I want to set it up in a way, that the agent can work on its own, change -> try to build -> test it. Once that works half automated, I call it success.

earino• 6 months ago

Two of the authors are engaging on bluesky regarding the "clickbaityness" of the paper:

https://bsky.app/profile/gaborbekes.bsky.social/post/3md4rga...

(Note, I receive a thanks in the paper.)

korenmiklos3• 6 months ago

author here. indeed, a more preceise title could be

given everything we know about OSS incentives from prior studies and how easy it is to load an OSS library with your AI agent, the demand-reducing effect of vibe coding is larger than the productivity-increasing effect

but that would be a mouthful

positron263• 6 months ago

What even is "engagement" here? Seems like abstract harm that rationalizes whatever emotion the reader already feels.

jorvi• 6 months ago

The productivity gains are real and large

This is also just untrue. There is a study showing that the productivity gain is -20%, developers (and especially managers) just assume it is +25%. And when they are told about this they still feel they are +20% faster. It's the dev equivalent of mounting a cool-looking spoiler to your car.

There are productivity gains, but they're in the fuzzy tasks like generating documentation and breaking up a project into bite-sized tasks. Or finding the right regex or combination of command line flags, and that last one I would triple verify if it was anything difficult to reverse.

tomaytotomato4• 6 months ago

I have been trying to use Claude code to help improve my opensource Java NLP location library.

However trying to get it to do anything other than optimise code or fix small issues it struggles. It struggles with high level abstract issues.

For example I currently have an issue with ambiguity collisions e.g.

Input: "California"

Output: "California, Missouri"

California is a state but also city in Missouri - https://github.com/tomaytotomato/location4j/issues/44

I asked Claude several times to resolve this ambiguity and it suggested various prioritisation strategies etc. however the resulting changes broke other functionality in my library.

In the end I am redesigning my library from scratch with minimal AI input. Why? because I started the project without the help of AI a few years back, I designed it to solve a problem but that problem and nuanced programming decisions seem to not be respected by LLMs (LLMs dont care about the story, they just care about the current state of the code)

Cthulhu_4• 6 months ago

I started the project in my brain and it has many flaws and nuances which I think LLMs are struggling to respect.

The project, or your brain? I think this is what a lot of LLM coders run into - they have a lot of intrinsic knowledge that is difficult or takes a lot of time and effort to put into words and describe. Vibes, if you will, like "I can't explain it but this code looks wrong"

tomaytotomato4• 6 months ago

I updated my original comment to explain my reasoning a bit more clearly.

Essentially I ask an LLM to look at a project and it just sees the current state of the codebase, it doesn't see the iterations and hacks and refactors and reverts.

It also doesn't see the first functionality I wrote for it at v1.

This could indeed be solved by giving the LLM a git log and telling it a story, but that might not solve my issue?

nevi-me• 6 months ago

I've been a skeptic, but now that I'm getting into using LLMs, I'm finding being very descriptive and laying down my thoughts, preferences, assumptions, etc, to help greatly.

I suppose a year ago we were talking about prompt engineers, so it's partly about being good at describing problems.

cpursley• 6 months ago

Yes, a lot of coders are terrible at documentation (both doc files and code docs) as well as good test coverage. Software should not need to live in ones head after written, it should be well architected and self-documenting - and when it is, both humans and LLMs navigate it pretty well (when augmented with good context management, helper mcps, etc).

skybrian2• 6 months ago

I find that asking it to write a design doc first and reviewing that (both you and the bot can do reviews) gets better results.

faxmeyourcode2• 6 months ago

LLMs dont care about the story, they just care about the current state of the code

You have to tell it about the backstory. It does not know unless you write about it somewhere and give it as input to the model.

krona2• 6 months ago

The commit history of that repo is pretty detailed at first glance.

px43• 6 months ago

it struggles

It does not struggle, you struggle. It is a tool you are using, and it is doing exactly what you're telling it to do. Tools take time to learn, and that's fine. Blaming the tools is counterproductive.

If the code is well documented, at a high level and with inline comments, and if your instructions are clear, it'll figure it out. If it makes a mistake, it's up to you to figure out where the communication broke down and figure out how to communicate more clearly and consistently.

zeroCalories2• 6 months ago

Not all tools are right for all jobs. My spoon struggles to perform open heart surgery.

whateveracct• 6 months ago

This sounds like coding with plaintext with extra steps.

smrq• 6 months ago

"My Toyota Corolla struggles to drive up icy hills." "It doesn't struggle, you struggle." ???

It's fine to critique your own tools and their strengths and weaknesses. Claiming that any and all failures of AI are an operator skill issue is counterproductive.

vrighter2• 6 months ago

A tool is something I can tightly control. A thing that may or may not work today, and if it does, might stop working tomorrow when the model gets updated without any notification to anyone, the output of which I have to very carefully scrutinize anyway, is not a tool. It's a toy.

epolanski• 6 months ago

One major part of successful LLM-assisted coding is to not focus on code vomiting but scaffolding.

Document, document, document: your architecture, best practices, preferences (both about code and how you want to work with the LLM and how do you expect it to behave it).

It is time consuming, but it's the only way you can get it to assist you semi-successfully.

Also try to understand that LLM's biggest power for a developer is not in authoring code as much as assistance into understanding it, connecting dots across features, etc.

If your expectation is to launch it in a project and tell it "do X, do Y" without the very much needed scaffolding you'll very quickly start losing the plot and increasing the mess. Sure, it may complete tasks here and there, but at the price of increasing complexity from which it is difficult for both you and it to dig out.

Most AI naysayers can't be bothered with the huge amount of work required to setup a project to be llm-friendly, they fail, and blame the tool.

Even after the scaffolding, the best thing to do, at least for the projects you care (essentially anything that's not a prototype for quickly validating an idea) you should keep reading and following it line by line, and keep updating your scaffolding and documentation as you see it commit the same mistakes over and over. And part of scaffolding requires also to put the source code of your main dependencies. I have a _vendor directory with git subtrees for major dependencies. LLMs can check the code of the dependencies, the tests, and figure out what they are doing wrong much quicker.

Last but not least, LLMs work better with certain patterns, such as TDD. So instead of "implement X", it's better to "I need to implement X, but before we do so, let's setup a way for testing and tracking our progress against". You can build an inspector for a virtual machine, you can setup e2es or other tests, or just dump line by line logs in some file. There's many approaches depending on the use case.

In any case, getting real help for LLMs for authoring code (editing, patching, writing new features) is highly dependent on having good context, good setup (tests, making it write a plan for business requirements and one for implementation) and following and improving all these aspects as you progress.

tomaytotomato4• 6 months ago

I agree to an extent

My project is quite well documented and I created a Prompt a while back along with some mermaid diagrams

https://github.com/tomaytotomato/location4j/tree/master/docs

I can't remember the exact prompt I gave to the LLM but I gave it a Github issue ticket and description.

After several iterations it fixed the issue, but my unit tests failed in other areas. I decided to abort it because I think my opinionated code was clashing with the LLM's solution.

The LLM's solution would probably be more technically correct, but because I don't do l33tcode or memorise how to implement Trie or BST my code does it my way. Maybe I just need to force the LLM to do it my way and ignore the other solutions?

softwaredoug• 6 months ago

Sounds a lot like model training and I’ve treated this sort of programming with AI exactly like that importantly making sure I have a test/train split

Make sure there’s a holdout the agent can’t see that it’s measured against. (And make sure it doesn’t cheat)

https://softwaredoug.com/blog/2026/01/17/ai-coding-needs-tes...

krona2• 6 months ago

If Claude read the entire commit history, wouldn't that allow it to make choices less incongruent with the direction of the project and general way of things?

eichin• 6 months ago

Trying not to turn this into "falsehoods developers believe about geographic names", but having done natural-language geocoding at scale (MetaCarta 2002-2010, acquired by Nokia) the most valuable thing was a growing set of tagged training data - because we were actually building the models out of that, but also because it would detect regressions; I suspect you needed something similar to "keep the LLMs in line", but you also need it for any more artisinal development approach too. (I'm a little surprised you even have a single-value-return search() function, issue#44 is just the tip of the iceberg - https://londonist.com/london/features/places-named-london-th... is a pretty good hint that a range of answers with probabilities attached is a minimum starting point...)

tomaytotomato4• 6 months ago

Thanks for this - its interesting how I have come to this conclusion as well.

My reworked approach is to return a list of results with a probability or certainty score.

In the situation of someone searching for London, I need to add some sort of priority for London, UK.

My dataset is sourced from an opensource JSON file which I am now pre-processing and identifying all collisions on it.

There are so many collisions!

Could I pick your brains and you could critique my approach? Thanks

antirez2• 6 months ago

I believe we will see a new huge wave of useful open source software. However don't expect the development model to stay the same. I was finally able to resurrect a few projects of mine, and many more will come. One incredible thing was the ability to easily merge what was worth merging from forks, for instance. The new OSS will be driven not much by the amount of code you can produce, but from the idea of software you have, how the software should look like, behave, what it should do to be useful. Today design is more important than coding.

avaer4• 6 months ago

We need a new git. (could be built on the current git)

One incredible thing was the ability to easily merge what was worth merging from forks, for instance

I agree, this is amazing, and really reduces the wasted effort. But it only works if you know what exists and where.

forgotpwd16• 6 months ago

Jujutsu?

mg74• 6 months ago

More we need a new GitHub.

wasmainiac• 6 months ago

That sounds a little extreem, why not just a new auto merge feature?

koakuma-chan5• 6 months ago

I don't trust software that has .claude in its GitHub repo.

echelon4• 6 months ago

You won't have to ignore this stuff for long. Pretty soon it'll be mandatory to keep up.

I've been a senior engineer doing large scale active-active, five nines distributed systems that process billions of dollars of transactions daily. These are well thought out systems with 20+ folks on design document reviews.

Not all of the work falls into that category, though. There's so much plumbing and maintenance and wiring of new features and requirements.

On that stuff, I'm getting ten times the amount of work done with AI than I was before. I could replace the juniors on my team with just myself if I needed to and still get all of our combined work done.

Engineers using AI are going to replace anyone not using AI.

In fact, now is the time to start a startup and "fire" all of these incumbent SaaS companies. You can make reasonable progress quickly and duplicate much of what many companies do without much effort.

If you haven't tried this stuff, you need to. I'm not kidding. You will easily 10x your productivity.

I'm not saying don't review your own code. Please do.

But Claude emits reasonable Rust and Java and C++. It's not just for JavaScript toys anymore.

- - - - - - - - - - - -

Edit:

Holy hell HN, downvoted to -4 in record time. Y'all don't like what's happening, but it's really happening.

I'm not lying about this.

I provided my background so you'd understand the context of my claims. I have a solid background in tech.

The same thing that happened to illustration and art is happening here, to us and to our career. And these models are quite usable for production code.

I can point Claude to a Rust HTTP handler and say, "using this example [file path], write a new endpoint that handles video file uploads, extracts the metadata, creates a thumbnail, uploads them to the cloud storage, and creates the relevant database records."

And it does it in a minute.

I review the code. It's as if I had written it. Maybe a change here or there.

Real production Rust code, 100 - 500 LOC, one shotted in one minute. It even installs the routes and understands the HTTP framework DSL. It even codegens Swagger API documentation and somehow understands the proc macro DSL that takes Rust five minutes to compile.

This tech is wizardry. It's the sci fi stuff we dreamed of as kids.

I don't get the sour opinions. The only thing to fear is big tech monopolozation.

I suppose the other thing to worry about is what's going to happen to our cushy $400k salaries. But if you make yourself useful, I think it'll work out just fine.

Perhaps more than fine if you're able to leverage this to get ahead and fire your employer. You might not need your employer anymore. If you can do sales and wear many hats, you'll do exceedingly well.

I'm not saying non-engineers will be able to do this. I'm saying engineers are well positioned to leverage this.

m000• 6 months ago

The real question is how much of the new wave of vibe-coded software will be able to graduate from pet project to community-maintained project.

It feels that vibe coding may exacerbate fragmentation (10 different vibe-coded packages for the same thing) and abandonment (made it in a weekend and left it to rot) for open source software.

antirez2• 6 months ago

I believe the process of accumulation of knowledge / fixes / interesting ideas will be still valid, so there will be a tons of small projects doing things that you can replicate and throw away, but the foundational libraries / tools will be still collaborative. But I don't agree with the idea of fragmentation, AI is very good at merging stuff from different branches, even when they diverged significantly.

cheema332• 6 months ago

I am a huge proponent of using AI tools for software development. But until I see a vibe coded replacement for the Linux kernel, PostgreSQL, gcc, git or Chromium, I am just going to disagree with this premise. If I am on a system without Python installed, I don't see Claude saying, oh, you don't need to download it, I'll write the Python interpreter for you.

Quarrel• 6 months ago

I am a huge proponent of using AI tools for software development. But until I see a vibe coded replacement for the Linux kernel, PostgreSQL, gcc, git or Chromium, I am just going to disagree with this premise.

Did you read it?

It isn't saying that LLMs will replace major open source software components. It said that the "reward" for providing, maintaining and helping curate these OSS pieces; which is the ecosystem they exist in, just disappears if there is no community around it, just an LLM ingesting open source code and spitting out a solution good or bad.

We've already seen curl buckle under the pressure, as their community minded, good conscious effort to give back to security reports, collapsed under the weight of slop.

This is largely about extending that thesis to the entire ecosystem. No GH issues, no PRs, no interaction. No kudos on HN, no stars on github, no "cheers mate" as you pass them at a conference after they give a great talk.

Where did you get that you needed to see a Linux kernel developed from AI tools, before you think the article's authors have a point?

volkercraig2• 6 months ago

This is largely about extending that thesis to the entire ecosystem. No GH issues, no PRs, no interaction. No kudos on HN, no stars on github, no "cheers mate" as you pass them at a conference after they give a great talk.

Oh... so nothing's gonna change for me then...

cheema332• 6 months ago

Where did you get that you needed to see a Linux kernel developed from AI tools..

It is in the title: "Vibe coding kills open source"

Clickbait titles beget clickbait responses.

dizhn• 6 months ago

I don't really read papers and haven't read this one either but that summary.

In vibe coding, an AI agent builds software by selecting and assembling open-source software (OSS),

Are they talking about indirectly due to prior training of the model? No agent I use is selecting and assembling open source software. That's more of an integration type of job not software development. Are they talking about packages and libraries? If yes, that's exactly how most people use those too.

I mean like this:

often without users directly reading documentation, reporting bugs, or otherwise engaging with maintainers.

and then,

Vibe coding raises productivity by lowering the cost of using and building on existing code, but it also weakens the user engagement through which many maintainers earn returns.

Maintainers who earn "returns" must be such a small niche as to be insignificant. Or do they mean things like github stars?

When OSS is monetized only through direct user engagement, greater adoption of vibe coding lowers entry and sharing, reduces the availability and quality of OSS, and reduces welfare despite higher productivity.

Now the hypothesis is exactly the opposite. Do agents not "select and assamble" OSS anymore? And what does this have to do with how OSS is "monetized"?

Sustaining OSS at its current scale under widespread vibe coding requires major changes in how maintainers are paid.

Sustaining OSS insofar as maintainers do it for a living requries major changes. Period. I don't see how vibe coding which makes all of this easier and cheaper is changing that equation. Quality is a different matter altogether and can still be achieved.

I am seeing a bunch of disjointed claims taken as truth that I frankly do not agree with in the first place.

What would the result of such a study even explain?

korenmiklos3• 6 months ago

Author here. By "returns" we mean any reward the developer is aiming for, whether money, recognition, world fame, future jobs, helping fellow developers. Sorry, econ jargon.

AI agents can select and load the appropriate packages and libraries without the user even knowing the name of the library, let alone that of the developer. This reduces the visibility of developers among users, who are now less likely to give a star, sponsor, offer a job, recommend the library to others etc.

Even as a business user, say an agency building websites, I could have been a fedn of certain js frameworks, hosting meetups, buying swags, sponsoring development. I am less likely to do that if I have no idea what framework is powering the websites I build.

Our argument is that rewards fall faster with vibe coding than productivity increases. OSS developers lose motivation, they stop maintaining existing libraries, don't bother sharing new ones (even if they keep writing a lot of code for themselves).

WarmWash2• 6 months ago

Small bespoke personalized on the spot apps are the future with LLMs.

The future will absolutely not be "How things are today + LLMs"

The paradigm now for software is "build a tool shed/garage/barn/warehouse full of as much capability for as many uses possible" but when LLMs can build you a custom(!) hammer or saw in a few minutes, why go to the shed?

skybrian2• 6 months ago

Maybe true for some apps, but I suspect we will still have a vibrant ecosystem of package managers and open source libraries and coding agents will know how to use them.

marginalia_nu2• 6 months ago

What would be the point of that? If LLMs ever actually become competent, surely they can just implement what they need.

reactordev2• 6 months ago

Why need a tool at all when the LLM can just build the house? What is a hammer? What is a keyboard? What’s a “Drivers License”?

draxil• 6 months ago

I think that's an optimistic interpretation of how good LLMs are?

But I think the reality is: LLMs democratise access to coding. In a way this decreases the market for complete solutions, but massively increases the audience for building blocks.

ipaddr6• 6 months ago

That you get no credit for open sourcing. Why would creators spend time anymore?

croes3• 6 months ago

LLMs democratise access to coding

Vibe coders don't code, they let code. So LLMs democratise access to coders.

blibble4• 6 months ago

LLMs democratise access to coding

by making the world dependent on 3, fascist adjacent, US tech companies?

candiddevmike• 6 months ago

Because whatever you use a LLM to build will inevitably need more features added or some kind of maintenance performed. And now you're spending $200+/mo on LLM subscriptions that give you a half-assed implementation that will eventually collapse under its own weight, vs just buying a solution that actually works and you don't have to worry about it.

technofiend• 6 months ago

... and you don't have to worry about it.

Not to be argumentative, but I have a concern that whomever I buy my solution from will have vibe coded it instead. I guess that means my support contract entitles me to hassling them about it, but I'm starting to worry it's just LLMs and vibe coded apps all the way down.

anticorporate2• 6 months ago

I think you're missing the enormous value in apps being standardized and opinionated. Standardized means that in addition to documentation, the whole internet is available to help you. Opinionated means as a user of an app in a new domain, you don't have to make a million decisions about how something should work to just get started.

Sure, there will be more personalized apps for those who have a lot of expertise in a domain and gain value from building something that supports their specific workflow. For the vast majority of the population, and the vast majority of use cases, this will not happen. I'm not about to give up the decades of experience I've gained with my tools for something I vibe coded in a weekend.

iknowSFR• 6 months ago

Then you’re going to be left behind. I’m going to be left behind.

Every problem or concern you raise will adapt to the next world because those things are valuable. These concerns are temporary, not permanent.

Bishonen88• 6 months ago

Expertise won't be needed (it already isn't). One can create copies of apps with vague descriptions referencing those big apps:

"Create a copy of xyz. It needs to look and behave similarly. I want these features ... And on top of that ...". Millions decisions not needed. A handful of vague descriptions of what one wants is all it takes today. I think claude and co. can even take in screenshots.

Documentation won't be needed either IMO. Since humans won't write nor read the code. They will simply ask LLM's if they have a question.

I totally am giving up my experience with various paid SaaS this year, which I was paying for last years. Not only am I able to add the features that I was wishing for those tools to have (and would have never made it into the real app because they're niche requests), but am saving money at the same time.

And the above is just whats happening today. Claude Code is younger than 1 year old. Looking forward to come back to this thread in a year and swallow my words... but I'm afraid I won't have to.

tracker110• 6 months ago

I've seen plenty of "standardized" (ie, "Enterprise" applications)... I'd just assume a bespoke hammer that's simple and easy to understand over a complex beast of HammerFactoryFactory to deliver you a builder of custom hammer builders so you get the JobHammer you need as part of the IoC loader platform that is then controlled through a 1.2gb service orchestrator that breaks at 11am every third Tuesday for an hour. When all you need to do is post up a "Help Wanted" poster on a piece of wood.

digiown2• 6 months ago

The apps/use cases for which such standardized and opinions tools can exist for, economically, mostly already exist IMO. Vibe coded tools fill an enormous space of semi-unique problems that only affect a small amount of people. For example various scripts to automate tasks imposed by a boss. The best balance is probably to use LLMs to use the standardized tools for you when available, so that things remain mostly scrutable.

As the saying goes, 80% of users only use 20% of the features of your program, but they are different 20% parts. When the user vibecode the program instead, only their specific 20% needs to be implemented.

seniorThrowaway5• 6 months ago

AI's / LLM's have already been trained on best practices for most domains. I've recently faced this decision and I went the LLM custom app path, because the software I needed was a simple internal business type app. There is open source and COTS software packages available for this kind of thing, but they tend to be massive suites trying to solve a bunch of things I don't need and also a minefield of licensing, freemium feature gating, and subject to future abandonment or rug pulls into much higher costs. Something that has happened many times. Long story short, I decided it was less work to build the exact tool I need to solve my "right now" problem, architected for future additions. I do think this is the future.

theshrike793• 6 months ago

SAP is THE MOST standardised "app" in the world.

It's so standard that the usual paradigm is that your company will adapt itself to the way SAP works, not the other way around. Massive gigantic corporations have tried to adapt SAP and failed. IIRC Lidl had a very expensive high-profile failure in this.

Being standardised isn't always a good thing.

InMice• 6 months ago

I like this take. "How things are today + LLM" is in some ways the best we can approximate because one is all we know and other side is the future unfolding before our eyes. One of the coolest things about vibe coding I find is starting with a base like django then using vibe coding to build models and templates exactly how one wants for a UIUX. Basically maybe we still need humans for the guts and low level stuff but that provides a base for fast, easy personalized customization.

I had a job where in short we had a lot of pain points with software that we had no resources permitted to fix them. With a mix past experience, googling I started writing some internal web based tools to fix these gaps. Everyone was happy. This is where I see vibe coding being really helpful in the higher level stuff like higher level scripting and web based tools. Just my opinion based on my experience.

pier25• 6 months ago

I don't think apps where people spend a lot of time are equivalent to small tools. You can vibe code a calculator but you probably spend most of your time on much more complex software.

groundzeros20153• 6 months ago

A calculator that uses doubles for everything I guess.

squigz• 6 months ago

Because going to the shed to get a work-tested tool is still faster than waiting on an LLM and hoping it meets every use-case you're likely to run into with that tool.

Whatever it is, the future will also certainly not be what it was a couple decades ago - that is, every one inventing their own solution to solved problems, resulting in a mess of tools with no standardization. There is a reason libraries/frameworks/etc exist.

jerf• 6 months ago

"why go to the shed"

A good question but there's a good answer: Debugged and tested code.

And by that, I mean the FULL spectrum of debugging and testing. Not just unit tests, not even just integration tests, but, is there a user that found this useful? At all? How many users? How many use cases? How hard has it been subjected to the blows of the real world?

As AI makes some of the other issues less important, the ones that remain become more important. It is completely impossible to ask an LLM to produce a code base that has been used by millions of people for five years. Such things will still have value.

The idea that the near-future is an AI powered wonderland of everyone getting custom bespoke code that does exactly what they want and everything is peachy is overlooking this problem. Even a (weakly) superhuman AI can't necessarily anticipate what the real world may do to a code base. Even if I can get an AI to make a bespoke photo editor, someone else's AI photo editor that has seen millions of person-years of usage is going to have advantages over my custom one that was just born.

Of course not all code is like this. There is a lot of low-consequence, one-off code, with all the properties we're familiar with on that front, like, there are no security issues because only I will run this, bugs are of no consequence because it's only ever going to be run across this exact data set that never exposes them (e.g., the vast, vast array of bash scripts that will technically do something wrong with spaces in filenames but ran just fine because there weren't any). LLMs are great for that and unquestionably will get better.

However there will still be great value in software that has been tested from top to bottom, for suitability, for solving the problem, not just raw basic unit tests but for surviving contact with the real world for millions/billions/trillions of hours. In fact the value of this may even go up in a world suddenly oversupplied with the little stuff. You can get a custom hammer but you can't get a custom hammer that has been tested in the fire of extensive real-world use, by definition.

otikik• 6 months ago

when LLMs can build you an custom(!) hammer or saw in a few minutes, why go to the shed?

Because I thought I needed a hammer for nails (employee payroll) but then I realized I also need it to screw (sales), soldering (inventory management) and cleanup (taxes).

Oh and don't forget that next month the density of iron can lower up to 50%.

freedomben• 6 months ago

Screw sales! I've definitely felt that way more than a few times :-D

Good points. It does feel like that happens quite often

palmotea• 6 months ago

The paradigm now for software is "build a tool shed/garage/barn/warehouse full of as much capability for as many uses possible" but when LLMs can build you an custom(!) hammer or saw in a few minutes, why go to the shed?

1) Your specific analogy is kinda missing something important: I don't want my tools working differently every time I use them, also it's work to use LLMs. A hammer is kind of a too-simple example, but going with it anyway: when I need a hammer, I don't want my "LLM" generating a plastic one, then having to iterate for 30 minutes to get it right. It takes me far less than 30 minutes to go to my shed. A better example is would be a UI, even if it was perfect, do you want all the buttons and menus to be different every time you use the tool? Because you generate a new one each time instead of "going to the shed"?

2) Then there's the question, can an LLM actually build, or does it just regurgitate? A hammer is an extremely we'll understood tool, that's been refined over centuries, so I think an LLM could do a pretty good job with one. There are lots of examples, but that also means the designs the LLM is referencing are probably better than the LLM's output. And then for things not like that, more unique, can the LLM even do it at all or with a reasonable amount of effort?

I think there's a modern phenomenon where making things "easier" actually results in worse outcomes, a degraded typical state vs. the previous status quo, because it turns what was once a necessity into a question of personal discipline. And it turns out when you remove necessity, a lot of people have a real hard time doing the best thing on discipline alone. LLMs might just enable more of those degenerate outcomes: everyone's using "custom" LLM generated tools all the time, but they all actually suck and are worse than if we just put that effort into designing the tools manually.

tracker110• 6 months ago

I started picturing AI generating tools like it does images of people... I mean, of course every other hammer will have an extra head off to the side, or split into 3 handles.

Seriously though, you can tell AI what libraries and conventions you want to follow... that's been a lot of what I've done with it recently... I've been relatively pleased with the results.

I've said several times that it's not perfect, but it is an overall force multiplier. It's much like working disconnected with an overseas dev team, but you get turn around in minutes instead of the next morning in your email. The better instructions/specs you give, the better the results. On my best day, I got about 3 weeks of what would take me alone done, after about 3 hours of planning/designing and another 2-3 hours of iteration with Claude Code. On my worst day, it was frustrating and it would have been about the same amount of time doing it myself. On average, I'd say I get close to 5 days of work done in 5-6 hours of AI assisted coding. Purely anecdotally.

That said, I usually have a technical mind for how I want the solution structured as well as features and how those features work... often it clashes with the AI approach and sometimes it swims nicely. I'll also say that not all AI coding is the same or even close in terms of usefulness.

exe34• 6 months ago

along that line of thinking, I've been wondering if there are better building blocks. right now we're asking llms to use the bricks designed for the human hand building a cathedral - what do the bricks look like when we want AI to build many sheds for specific use? functional programming? would the database ideas of data storage like the longhorn vapourware make a come back?

Ravus• 6 months ago

I do not think that this is likely to be a successful model.

When (not if) software breaks in production, you need to be able to debug it effectively. Knowing that external libraries do their base job is really helpful in reducing the search space and in reducing the blast radius of patches.

Note that this is not AI-specific. More generally, in-house implementations of software that is not your core business brings costs that are not limited to that of writing said implementation.

rglover2• 6 months ago

Would you trust your hand next to a saw made by an LLM?

tracker110• 6 months ago

Maybe. Were the designs reviewed by qualified engineers and gone trough rigorous QA cycles before getting placed in front of me?

II2II• 6 months ago

when LLMs can build you an custom(!) hammer or saw in a few minutes, why go to the shed?

Because software developers typically understand how to implement a solution to problem better than the client. If they don't have enough details to implement a solution, they will ask the client for details. If the developer decides to use an LLM to implement a solution, they have the ability to assess the end product.

The problem is software developers cost money. A developer using an LLM may reduce the cost of development, but it is doubtful that the reduction in cost will be sufficient to justify personalized applications in many cases. Most of the cases where it would justify the cost would likely be in domains where custom software is in common use anyhow.

Sure, you will see a few people using LLMs to develop personalized software for themselves. Yet these will be people who understand how to specify the problem they are trying to solve clearly, will have the patience to handle the quirks and bugs in the software they create, and may even enjoy the process. You may even have a few small and medium sized businesses hiring developers who use LLMs to create custom software. But I don't think you're going to see the wholesale adoption of personalized software.

And that only considers the ability of people to specify the problem they are trying to solve. There are other considerations, such as interoperability. We live in a networked world after all, and interoperability was important even before everything was networked.

aspenmartin2• 6 months ago

Because software developers typically understand how to implement a solution to problem better than the client. If they don't have enough details to implement a solution, they will ask the client for details. If the developer decides to use an LLM to implement a solution, they have the ability to assess the end product.

Why do you think agents can’t do that? They can’t do this really well today but if the distance we went in 2025 stays similar it’ll be like a year before this starts getting decent and then like another 1 year before it’s excellent.

Sure, you will see a few people using LLMs to develop personalized software for themselves. Yet these will be people who understand how to specify the problem they are trying to solve clearly, will have the patience to handle the quirks and bugs in the software they create

Only humans can do this?

pianopatrick• 6 months ago

If they don't have enough details to implement a solution, they will ask the client for details.

but LLMs are chat bots. Surely eventually someone will set up an LLM based coding system that can ask architecture and design questions before starting to code.

wasmitnetzen• 6 months ago

Because I will probably ask the AI for a rock instead of a bespoke hammer. If I even know what a nail is.

I very much like to use the years of debugging and innovation others spent on that very same problem that I'm having.

groundzeros20153• 6 months ago

Because it can’t really do that for any tools that matter.

pjmlp• 6 months ago

Exactly, think StarTrek replicator.

rurp• 6 months ago

The vast majority of users make zero changes to the default settings of an app or device, even for software they use all the time and where some simple builtin adjustments would significantly improve their experience.

I simply can't imagine a world where these same people all decide they constantly want to learn a completely unique UX for whatever piece of software they want to use.

ryandrake2• 6 months ago

All the people may not, but a decently skilled software engineer armed with an LLM, who doesn't have a lot of free time might be now be motivated to do it, whereas before it was like, "This thing is going to take months to replace, do I really want to write my own?"

7e• 6 months ago

The LLM will know how the user operates, their proclivities and brain structure, and will design UX perfectly suited to them, like a bespoke glove. They won't have to learn anything, it will be like a butler.

WarmWash2• 6 months ago

Your missing the forest for the trees here.

Users will not fumble with the complex web of nested settings that engineers wet dream about.

But they will tell the LLM "I'd really like it if the tool bar only had the hammer and saw tools", and it will be done.

I cannot see software going in any other direction than a blank front end that users prompt LLMs to run scripts on top of.

Picture MS Word where the GUI is just a page and a sidebar for telling an LLM what you want it to do. And if it's not possible, the LLM could even write extensions and plugins that make it possible.

Software is going to completely change.

ryandrake2• 6 months ago

The more I experiment with quickly coding up little projects with LLMs the more I am convinced of this. There is that saying: 90% of your customers use 10% of your software's features, but they each use a different 10%. Well, the ability to quickly vibe up a small bespoke app that does that 10% AND NOTHING ELSE is here now, and it kind of solves that problem. We don't need to put up with DoEverythingBloatWare (even open source DoEverything) when you can just have the bits and pieces you actually want/need.

Also, you don't have to fear breaking updates--you know for sure that the software's UI will not just change out from under you because some designer had to pad their portfolio. Or that you're not going to lose a critical feature because the developer decided to refactor and leave it out.

I'm currently going through and looking at some of the bigger, bloated, crashing slow-moving software I use and working on replacements.

FeloniousHam• 6 months ago

I can speak to this directly: I've customized a few extensions I use with VSCode, (nearly) completely having the AI generate/iterate over my feature request until it works. I don't have the time to learn the details (or different languages) of the various projects, but I get huge benefit from the improvements.

- PRO Deployer

- MS Typescript

- Typescript-Go

- a bespoke internal extension to automate a lot of housekeeping when developing against tickets (git checks, branch creation, stash when switching, automatically connecting and updating ticket system)

jayd16• 6 months ago

Why use a battle tested, secure, library that you know solves your problem when you can burden your project with custom code you need to maintain?

seniorThrowaway5• 6 months ago

While quality libraries do exist, let's not pretend that most people are validating and testing the libraries they pull in, that abandoned / unmaintained libraries aren't widely used, and that managing the dependency hell caused by libraries is free.

LtWorf• 6 months ago

Nah the AI will maintain it!

jvanderbot• 6 months ago

From what - OS libraires only? Assembly?

The danger is not "Nobody uses OSS".

The danger is "building software becomes exponentially more difficult without a commons to build from".

panta• 6 months ago

StanLLM-generated hammer: "Dear valued customer, our automated systems have flagged activity on your StanLLM account that appears to be non-compliant with our Acceptable Use Policy. As a precautionary measure your account has been suspended. If you believe this suspension is in error, feel free to contact our customer support at /dev/null^H^H^H^H^H^H^H^H^Hsupport@..."

onraglanroad• 6 months ago

That's what you get for using proprietary software instead of the GNU version: StaLLMan

matkoniecz5• 6 months ago

when LLMs can build you a custom(!) hammer or saw in a few minutes, why go to the shed?

once such LLMs exist, this question may be worth considering

they do NOT exist at this moment

YesBox• 6 months ago

Hehe, you created quite the dog pile. Here's my woof:

IMO you only need to look at the 30+ year history of Linux to see how wrong this prediction is. There will be a small group of people who do as you say, but the other 95% will happily pay for someone else to take care of their problem. Convenience is the supreme king of the American market.

dimitri-vs4• 6 months ago

This assumes an educated, passionate and patient user that 99% of people are not. They wont ask for a hammer - they will ask for a rock tied to a stick and get pissed off when it doesn't work like a hammer. They will ask for paint that doesn't drip. They will ask for electrical sockets they can install in their bathtub.

parliament32• 6 months ago

"Why hire a website designer when you could just drag and drop in WordPress?"

And many businesses do, and it works, until it doesn't. I agree with you; that's the future I'm seeing for ad-hoc LLM apps.

GoatInGrey• 6 months ago

My personal theory is that as the excitement for LLMs normalizes, we'll land on something evolutionary rather than revolutionary. Prompt programming will take over what used to be quick/amateur micro programs (this includes userspace "developers"). Skilled developers will operate on a spectrum: all manual code at one extreme, and at the other extreme, manually defining just the essential patterns that prompt programming can reasonably build upon.

I do not suspect that we will stay in an individualized programs Tower of Babel situation, if we ever enter it in the first place.

It's anyone's guess as to what we end up settling on, of course. This is just a guess of mine.

jcarrano• 6 months ago

The 3d-printer of software: get a custom part quickly and cheaply, even if not suitable for mass production.

seniorThrowaway5• 6 months ago

I think this is a great analogy

MSFT_Edging• 6 months ago

This is only a realistic expectation for the single person who needs that hammer.

Otherwise we'll all individually be burning power via GPUs to reinvent the wheel thousands of times.

Also, look at the level of effort to maintain any bespoke machine. Assembly lines with interchangeable parts were a big deal for a reason. That follows with software via standard libraries and APIs. If you reinvent your software wheel every time, we'll all have careers trying to fix the deluge of slop that has been generated.

eikenberry• 6 months ago

Bespoke personalized apps have been around forever in the form of shell scripts. LLMs will expand that capability to a lot more people but won’t change the basic dynamics. Just like shell scripts, LLMs will need lower level building blocks to work with. The main difference will be that the LLM ecosystem will include some libraries as well. Though, I believe, most of those libraries haven’t been written yet.

MagicMoonlight• 6 months ago

You could already pay Indians to make you software if you wanted poorly made software. Poorly making it with AI isn’t that big an improvement.

You go to the shed because you know the hammer has undergone extensive testing and won’t immediately be hacked, costing you hundreds of millions.

theshrike793• 6 months ago

It is.

Getting poor software made by Indians is a cycle that takes months.

With AI you get the first poor version within hours. Then you can iterate. In a week of hourly iteration you'll most likely have something usable.

The Indians are still having meetings about when to have meetings and you can see from the logs they haven't accessed any of the documentation you gave them for the issue. Billing is on point though.

estimator7292• 6 months ago

LLMs have been a godsend for throwaway software. I wouldn't want to count the number of hours I've spent hand rolling an application that exists for one purpose for about two weeks and then to the digital graveyard.

Now that LLMs can do it while I make coffee, I can do more useful things with my time like writing business code and posting on HN.

Beyond that, meh.

nektro• 6 months ago

the money's gonna run out and LLMs will disappear overnight

troutpanda• 6 months ago

Finally a world where everyone uses different hammers and no one can work on anything unless you can ask the hammer-oracle to reverse engineer the other people's hammers and nails

xacky• 6 months ago

This is also the general threat to books and encyclopedias. Grok for all its point of view flaws still generated a full encyclopedia in two months that Wikipedia by humans took 25 years and Britannica over three centuries. The only remaining issue is when we can finally trust AI to be correct more than expert humans and be aligned with human moral consensus.

p0nce• 6 months ago

It is effective but once cost of creating something is down, then you have less reason to collaborate and depend on each other vs asking your own LLM to build your own bubble. When paired with new-found cognitive laziness and lack of motivation when you then use no AI it's not sure of the second order effects.

pixl972• 6 months ago

then you have less reason to collaborate and depend on each other vs asking your own LLM to build your own bubble

What's interesting in reading comments like this is reading the same type of message across a bunch of different fields and aspects of life.

"When continents move, not only the weather changes"

If GenAI keeps increasing it's abilities and doesn't bankrupt a number of companies first, I think it's going to make a lot of people bubbles that encompass their entire lives. It's not difficult to imagine little pockets of hyperreality were some peoples lives are only feed by generated content and their existence starts to behave more like a video game than having any grounding in the physical. It's going to be interesting what the fractured remains of society look like in that future.

nicoburns2• 6 months ago

Something I've noticed is that AI code generation makes it easier/faster to generate code while shifting more work of the work of keeping code correct and maintainable to the code review stage. That can be highly problematic for open source projects that are typically already bottlenecked by maintainer review bandwidth.

It can be mitigated by PR submitters doing a review and edit pass prior to submitting a PR. But a lot of submitters don't currently do this, and in my experience the average quality of PRs generated by AI is definitely significantly lower than those not generated by AI.

echelon4• 6 months ago

The maintainers can now do all the work themselves.

With the time they save using AI, they can get much more work done. So much that having other engineers learn the codebase is probably not worth it anymore.

Large scale software systems can be maintained by one or two folks now.

Edit: I'm not going to get rate limited replying to everyone, so I'll just link another comment:

https://news.ycombinator.com/item?id=46765785

shafyy• 6 months ago

Not sure if you're being sarcastic or not?

wooderson_iv• 6 months ago

Do you have anecdotes or evidence of this or is it speculative?

j16sdiz• 6 months ago

Those are the most mentally exhausting task. Are you sure putting this burden on single person is good?

tracker110• 6 months ago

No, because proper QA/QC will be the bottleneck.... AI is ill-suited to test for fit/use. I built an ANSi terminal with AI assist (rust/wasm/canvas)... it literally took longer to get the scrollback feature working with keyboard and mousewheel interactions than it took to get the basic rendering correct. And there are still a few bugs in it.

In the end, you should not just skip QA/QC and fitness testing. Many things can fit a technical spec and still be absolutely horrible. With AI assisted developmnet, imo it's that much more important to get the UX right. I don't want 10x the apps if they're all half-implemented garbage that look like garbage are hard to use and just painful to install, maintain and use.

Library creation still has a place here... and so far, getting AI code assistants to actually understand and use a given library that may be less popular has been at the very least, interresting.

matkoniecz5• 6 months ago

So much that having other engineers learn the codebase is probably not worth it anymore.
Large scale software systems can be maintained by one or two folks now.

No, LLMs are not so powerful yet.

erelong• 6 months ago

Yeah, it should change things but also free up other energies to work on things

trey-jones2• 6 months ago

To me, an old guy, I would rather have LLM doing (assisting with) the code review than the actual code production. Is that stupid?

groundzeros20153• 6 months ago

This makes sense to me.

I need to make decisions about how things are implemented. Even if it can pick “a way” that’s not necessarily going to be a coherent design that I want.

In contrast for review I already made the choices and now it’s just providing feedback. More information I can choose to follow or ignore.

electroly2• 6 months ago

LLMs are great at reviewing. This is not stupid at all if it's what you want; you can still derive benefit from LLMs this way. I like to have them review at the design level where I write a spec document, and the LLM reviews and advises. I don't like having the LLM actually write the document, even though they are capable of it. I do like them writing the code, but I totally get it; it's no different than me and the spec documents.

Leynos• 6 months ago

Take a look at CodeRabbit and Sourcery if you want to give that a go.

pgroves• 6 months ago

I was expecting this to be the point of the article when I saw the title. Popular projects appear to be drowning in PRs that are almost certainly AI generated. OpencodeCli has 1200 open at the moment[1]. Aider, which is sort of abandoned has 200 [2]. AFAIK, both projects are mostly one maintainer.

[1] https://github.com/anomalyco/opencode/pulls [2] https://github.com/Aider-AI/aider/pulls

matkoniecz5• 6 months ago

Even not-so popular niche projects are getting LLM spam. Curiously, at least where Ia m active most comes from account with India-related usernames.

Some are opening PRs, some are posting comments in issues that repeat what was said already, just in more words.

gyanchawdhary• 6 months ago

interesting as an econ thought experiment .. but it assumes OSS revenue comes from direct developr engagement .. In practice .. most successful OSS is funded by enterprises .. cloud vendors .. or consulting engagements .. where broader adoption, including AI mediated usage, often increases demand of said OSS project

neko-kai2• 6 months ago

On the contrary, I hope vibe coding revives Linux desktop into a truly usable platform.

e.g. Vibe coding defeats GNOME developers' main argument for endlessly deleting features and degrading user experience - that features are ostensibly "hard to maintain".

Well, LLMs are rapidly reducing development costs to 0.

The bottleneck for UI development is now testing, and here desktop Linux has advantage - Linux users have been trained like Pavlov's dogs to test and write detailed upstream bug reports, something Windows and macOS users just don't do.

croes3• 6 months ago

You don't think the current prices of LLMs will stay?

At some point the investors want to see profit.

Cthulhu_4• 6 months ago

Is the maintenance due to code or due to people / politics / etc? LLMs won't change that.

Also it's a formal system and process, "vibe" coding is anything but. Call me curmudgeony (?) but I don't think "vibe coding" should be a phrase used to describe LLM assisted software engineering in large / critical systems.

rvz• 6 months ago

On the contrary, I hope vibe coding revives Linux desktop into a truly usable platform.

Oh sweet summer child.

Well, LLMs are rapidly reducing development costs to 0.

And maintainance costs along with technical debt rapidly goes up.

ipaddr6• 6 months ago

For me spending time on my open source projects doesn't make sense anymore.

People (the community and employers) previously were impressed because of the amount of work required. Now that respect is gone as people can't automatically tell on the surface if this is a low effort vibe code or something else.

Community engagement has dropped. Stars aren't being given out as freely. People aren't actively reading your code like they use to.

For projects done before llms you can still link effort and signal but for anything started now.. everyone assumes it's llm created. No one want to read that code and not in the same way you would read other humans. Fewer will download the project.

Many of the reasons why I wrote open source is gone. And knowing the biggest/only engagement will come from llms copying your work giving you no credit.. what's the point?

Cthulhu_4• 6 months ago

But effort / amount of work shouldn't be a deciding factor - I think anyone can churn out code if they choose to. But it's the type and quality of it.

Nobody cares if you wrote 5000 LOC, what they care about is what it does, how it does it, how fast and how good it does it, and none of those qualifiers are about volume.

9dev2• 6 months ago

Eh, I don't believe that. Smartphones have amazing cameras, and we still have photographers. There are CNC saws and mills that will ship you your perfectly realised CAD prints, yet there are still carpenters and a vibrant community of people making their own furniture. These examples go on and on.

Without any kind of offence implied: As maintainer of a few open source projects, I'm happy if it stops being an employability optimisation vector. Many of the people who don't code for fun but to get hired by FAANG aren't really bringing joy to others anyway.

If we end up with a small web of enthusiasts who write software for solving challenges, connecting intellectually with likeminded people, and altruism—then I'm fine with that. Let companies pay for writing software! Reduce the giant dependency chains! Have less infrastructure dedicated to distributing all that open source code!

What will remain after that is the actual open source code true to the idea.

em-bee2• 6 months ago

exactly this. FOSS was always driven by those who could code and did so driven by their own intrinsic motivation. those people won't disappear. there may be less people because some are more driven by quick results and while in the past they had to code to get there, now they don't, which means they won't discover the joy of coding.

but for others coding will become an art and craft like woodworking or other hobbies that require mastery.

ipaddr6• 6 months ago

Photographers use cameras so increasing cameras makes more photographers.

CNC saws use to take pencil draws as input and now they can handle files. People always made handmade furniture while CNCs existed.

Open source projects around a need will continue. Things like youtube downloader fills a need. But many projects were showing off what you as a developer can write to impress a community. Those are dead. Projects that showcased new coding styles or ways to do things are dead.

Faang open source employment was never a thing. Faang filtered by leetcode, referrals, clout and h1 visas.

contravariant• 6 months ago

I'm never quite sure what to think of papers that have a conclusion and then build a mathematical model to support it.

tonyedgecombe• 6 months ago

Science starts with hypothesis and predictions.

pixl972• 6 months ago

Yes, but it's easy, and incorrect, to start with an answer and build your work backwards rather than proving your hypothesis with evidence.

marginalia_nu2• 6 months ago

When OSS is monetized only through direct user engagement, greater adoption of vibe coding lowers entry and sharing, reduces the availability and quality of OSS, and reduces welfare despite higher productivity. Sustaining OSS at its current scale under widespread vibe coding requires major changes in how maintainers are paid.

I can't think of even a single example of OSS being monetized through direct user engagement. The bulk of it just isn't monetized at all, and what is monetized (beyond like a tip jar situation where you get some coffee money every once in a while) is primarily sponsored by enterprise users, support license sales, or through grants, or something like that. A few projects like Krita sell binaries on the steam store.

dfox• 6 months ago

There is this kind of webdev-adjacent niche where the model of using documentation (or even intentionally sub-par documentation) as a marketing funnel for consulting and/or "Pro" versions is a thing. These projects are somewhat vocal about vibe coding killing their business models. If these projects really create any meaningful value is another question.

nprateem• 6 months ago

Terraform, ansible, countless others. No community=no enterprise version, no awareness

WorldMaker• 6 months ago

what is monetized (beyond like a tip jar situation where you get some coffee money every once in a while) is primarily sponsored by enterprise users, support license sales, or through grants, or something like that

All of those examples are the "direct user engagement" in question. No one tips a tip jar that they don't see. Enterprise users don't sponsor projects or buy licenses when they don't know they are using projects they should sponsor or buy a better license.

If an LLM is automating your `npm install` you probably don't see the funding requests. Are you running `npm fund` in your spare time?

If an LLM is automating your need to lookup library documentation you probably don't see that the library's own documentation has a Ko-Fi link or GitHub Sponsors request. Would you check library websites and GitHub repos on your own for such things without the need to read their documentation?

BoredPositron• 6 months ago

I have written so many small scripts and apps that do exactly what I want. The general purpose OSS projects are always a compromise. I believe if LLMs mature some more years we will see a decline in these general purpose projects and will see a rise in personal apps. I dont think its something to worry about.

tinyhouse• 6 months ago

There's a balance between coding by hand and vibe coding that is important. The less you understand the code, the more boring maintaining the software becomes. It's OK for throw away code, but not for serious open source projects. Use it as a powerful tool rather than your replacement.

rtp4me2• 6 months ago

I wonder how many OSS projects are using AI to actively squash bugs so their projects are more rock-solid than before. Also, seems to me if your project underwent a full AI standardized code-quality check (using 2 or 3 AI models), it would be considered the "standard" from which other projects could use. For example, if you needed a particular piece of code for your own project, the AI tooling could suggest leveraging an existing gold-standard project.

sailfast• 6 months ago

It _might_ kill open source. It might lower revenue opportunities according to this abstract. Bit of a click-bait paper title.

OrvalWintermute• 6 months ago

maybe we just need License-Aware Vibe Coding that can link back to code snippet provenance similar to SBOMs?

bluejay2387• 6 months ago

Does it seem to anyone else that author's have created a definition for 'vibe coding' that is specifically designed to justify their paper? Also that their premise is based on the assumption that developers will be irresponsible about the use of these tools ("often without users directly reading documentation, reporting bugs, or otherwise engaging with maintainers") so that it would actually be people killing open source not 'Vibe Coding'? Just a guess on my part, but once developers learn to use these tools and we get over the newness I think this will be great for open source. With these tools open source projects can compete with an army of corporate developers while alleviating some of the pressure on overworked under-rewarded maintainers.

korenmiklos3• 6 months ago

Author here. We have the productvity-increasing effect of AI coding agents in the model (you're right, we're using "vibe coding" as a catch-all here). Our claim is that rewards to OSS developers (visibility and recognition in the dev community, future sponsorships, upsells to business users etc) fall faster than productivity increases. OSS devs lose the incentives to create software for others and respond to their needs.

j4coh• 6 months ago

I am not sure if it kills open source, but it probably kills open core. You can just take a project like GitLab and ask an LLM, conveniently trained on the GitLab enterprise edition source code, to generate you a fresh copy of whatever features of EE you care about, but with the license laundered.

linuxftw• 6 months ago

Is arxiv.org the new medium.com now? Seems like recently there has been a plethora of blog-level submissions from there to HN recently.

delegate• 6 months ago

There's some irony in the fact that LLMs are in large part possible because of open source software.

From the tools which were used to design and develop the models (programming languages, libraries) to the operating systems running them to the databases used for storing training data .. plus of course they were trained mostly on open source code.

If OSS didn't exist, it's highly unlikely that LLMs would have been built.

blibble4• 6 months ago

If OSS didn't exist, it's highly unlikely that LLMs would have been built.

would anyone want SlopHub Copilot if it had been trained exclusively on Microsoft's code?

(rhetorical question)

jdiff2• 6 months ago

Turns out that it's only in myth that a snake can eat its own tail without dying.

verdverm• 6 months ago

This study seems flawed at the assumptions and from the start

"most" maintainers make exactly zero dollars. Further, OSS monetization rarely involves developer engagement, it's been all about enterprise feature gating

alentred• 6 months ago

Not an answer to all of our problems, but I wonder if we will see a wider adoption of more complex contribution models. Like "Lieutenants Workflow" Linux was known for, for example. Many possible workflows are explored in the Git Book [1].

[1] https://git-scm.com/book/en/v2/Distributed-Git-Distributed-W...

pmarreck4• 6 months ago

Related but not sure how much attention it's getting:

GPL is a dead man walking since you can have any LLM cleanroom a new implementation in a new language from a public spec with verifiable "never looked at the original source" and it can be more permissively-licensed however you wish (MIT, BSD etc).

case in point, check out my current deps on the project I'm currently working on with LLM assist: https://github.com/pmarreck/validate/tree/yolo/deps

"validate" is a project that currently validates over 100 file formats at the byte level; its goal is to validate as many formats as possible, for posterity/all time.

Why did I avoid GPL (which I am normally a fan of) since this is open-source? I have an even-higher-level project I'm working on, implementing automatic light parity protection (which can proactively repair data without a RAID/ZFS setup) which I want to make for sale, whose code will (initially) be private, and which uses this as a dependency (no sense in protecting data that is already corrupted).

Figured I'd give this to the world for free in the meantime. It's already found a bunch of actually-corrupt files in my collection (note that there's still some false-positive risk; I literally released this just yesterday and it's still actively being worked on) including some cherished photos from a Japan trip I took a few years ago that cannot be replaced.

It has Mac, Windows and Linux builds. Check the github actions page.

natebc• 6 months ago

Did something change? Is LLM generated stuff now able to be protected with copyrights?

I was under the impression that copyright was only available for works created by people.

pmarreck4• 6 months ago

LLMs don’t change that. They’re just tools. The relevant question is whether a human exercised creative judgment in selecting, shaping, or editing the output. Which I most certainly did. Otherwise my month of work here would have just been a minute and a single prompt and then just grabbing a coffee.

We already handle this with cameras, compilers, spell-checkers, and procedural generation. If you push a button and accept whatever falls out, you may not have authorship. If you meaningfully direct and curate the result, you almost certainly do.

Responsibility still lands on the human, which is a good sanity check: there is no such thing as “LLM-authored but human-unaccountable” work. Pretending otherwise is just outsourcing epistemic responsibility to a stochastic tool. Similarly, you can't both assign blame to me when things go wrong, but credit to the LLM when things go right. Or vice versa.

digiown2• 6 months ago

which means full reads and scrubs touch more bits and inevitably brush against those error rates

Does this make sense at all? ZFS scrubs only reads the data you have, not the whole drive, and repairs data if possible. The more data you have, the more you have to validate regardless of the tools used. The BER is also just a terrible metric and is not reflective of how drives actually behave.

dahauns• 6 months ago

verifiable "never looked at the original source"

...erm.

To adress the elephant in the room: Who exactly is supposed to be verifiable to never have looked at the original source? You or the LLM?

pmarreck4• 6 months ago

Both. Good question.

Although it would be much harder to prove, of course, that I never saw the original code/implementation.

romanows• 6 months ago

As long as you hold the copyright to your "validate" project, you can dual license it. So can release it under the (A)GPL and also use it in your closed-source commercial project. I think you would need to make contributors sign a contributor license agreement (CLA) though, to continue using their contributions to "validate" in your closed-source offering.

pmarreck4• 6 months ago

ah, interesting.

donatj• 6 months ago

As the maintainer of a handful of small projects, what I have seen for better or worse is tickets and pull requests completely dry up.

My guess is instead of Googling "library that does X" people are asking AI to solve the problem and it's regurgitating a solution in place? That's my theory anyway.

Olshansky• 6 months ago

Yes and no.

---

Concrete example of a no: I set up [1] in such a way that anyone can implement a new blog -> rss feed; docs, agents.md, open-source, free, etc...

Concrete example of a yes: Company spends too much money on simple software.

--- Our Vision ---

I feel the need to share: https://grove.city/

Human Flywheel: Human tips creator <-> Creator engages with audience

Agent Flywheel: Human creates creative content <-> Agent tips human

Yes, it uses crypto, but it's just stablecoins.

This is going to exist in some fashion and all online content creation (OSS and other) will need it.

---

As with everything, it Obvious

[1] https://github.com/Olshansk/rss-feeds

Sevii• 6 months ago

Vibecoding is great for open source. Open source is already dominated by strong solo programmers like antirez, linus, etc. People with very strong motivations to create software they see as necessary. Vibecoding makes creating open source projects easier. It makes it easier to get from an idea to "Hey guys check this out!" The only downside to open source is the fly by PRs vibecoding enables which are currently draining maintainer time.

progx• 6 months ago

And make one PR after another, i can see how happy Linus & Co. would be of all the garbage features ;-)

tracker110• 6 months ago

I think the solution to the latter is simply to maintain high standards in terms of structure and organization. I've always been a fan of KISS should override any other non-requirement of software. Any my non-requirement, I mean anything that is just subjective. Don't create complexity you don't actually need, or that doesn't make an outsized contribution to making other areas of the code easier to reason with.

Sometimes having dozens of one-off scripts is easier/simpler than trying to create the uber-flexibly one tool does all solution.

program_whiz• 6 months ago

All this talk about how you can vibecode all your apps now, "why use OSS?" is making me laugh. Sure for a little website or a small tool, maybe even a change to your somewhat complex codebase that you thoroughly check and test.

Is anyone replacing firefox, chromium, postgres, nginx, git, linux, etc? It would be idiotic to trade git for a vibe coded source control. I can't even imagine the motivations, maybe "merges the way I like it"?

Not sure, but anyone who's saying this stuff hasn't even taken the basic first level glance at what it would entail. By all means, stop paying $10 a month to "JSON validator SaSS", but also don't complain with the little niggling bugs, maintenance and organization that comes with it. But please stop pretending you can just vibe code your own Kafka, Apache, Vulkan, or PostGRES.

Yes, you can probably go faster (possibly not in the right direction if inexperienced), but ultimately, something like that would still require very senior, experienced person, using the tool in a very guided way with heavy review. By why take on the maintenance, the bug hunting, and everything else, unless that is your main business objective?

Even if you can 10x, if you use that to just take on 10x more maintenance, you haven't increased velocity. To really go faster, that 10x must be focused on the right objective -- distinctive business value. If you use that 10x to generate hundreds of small tools you now have to juggle and maintain, that have no docs or support, no searchable history of problems solved, you may have returned yourself to 1x (or worse).

This is the old "we'll write our own inhouse programming language" but leaking out to apps. Sure, java doesn't work _exactly_ the way you want it to, you probably have complaints. But writing your own lang will be a huge hit to whatever it was you actually wanted to use the language for, and you lose all the docs, forums, LSP / debugging tools, ecosystem, etc.

barelysapient• 6 months ago

I think LLMs also kill off most programming languages. I think we’ll end up with a handful of languages that LLMs most proficient at writing for and the languages required for device or processor compatibility.

The cost improvement for an LLM to emit a feature (with an engineer in the loop) is too much of an improvement. We’ll look at engineers coding in C the same way we look at engineers today who code in assembly. LLM enabled development becomes the new abstraction; probably with a grammar and system for stronger specification formalization.

delaminator2• 6 months ago

I've done a bit of experimentation with that. And the irony is Rust seems to fare best because of the error messages of the compiler.

I have had a lot of conversations with Claude about it and it supports that theory.

13rac1• 6 months ago

Warning: Claude may support the theory, because Claude is a sycophant.

hxugufjfjf2• 6 months ago

Claude told me the exact opposite. Always claims that Python or JavaScript is the best choice because its training corpus is so much larger than the alternatives.

ozten2• 6 months ago

Generative AI is a major setback to OSS licensing. I've been on projects where we needed to do a "cleanroom" implementation and vet the team has never viewed the source code of competing products. Now in the gen AI era, coding agents are IP laundering machines. They are trained on OSS code, but the nuances of the original licenses are lost.

On the whole, I think it is a net gain for civilization, but if we zoom into OSS licensing... not good.

kode-targz• 6 months ago

It could be a net gain for civilization if it stayed open, decentralized and off the hands of private companies, but that's not at all the case. Only tecchies care or even know about open models

ozten2• 6 months ago

Regardless of open or closed models, the reason it is a net gain is that the cost of software production is collapsing and will trend towards zero.

Example: We can achieve more climate solutions (and faster) thanks to technological acceleration.

finaard• 6 months ago

LLMs can be quite useful in reverse engineering - there's typically a lot of steps which are not really difficult, but are hard to script, and still require a bit of an idea what's going on. Quite a bit of that can be automated with LLMs now - so it's also a lot easier now to figure what your proprietary blob does, and either interface with it, or just publish an implementation of the functionality as open source, potentially messing with your business plan.

tracker110• 6 months ago

Probably fair... would also be interesting to try to limit the use of say GPL code to maintaining interoperability, not duplication of internal methods, etc. I also think that the amount of MIT/ISC/BSD, etc. licensed code, with whatever MS and other commercial entities have contributed for this use is probably enough to not be a significant difference to model quality though.

dev_l1x_be• 6 months ago

I think it is not killing opensource. It is changing it. There are more smaller scoped projects created for specific purposes instead of creating a huge project that has gazillion features supporting everything. At least this is my experience.

tracker110• 6 months ago

Largely my take as well.. there's also a LOT of slop and not enough polish or completeness in terms of UX and usability.

tracker110• 6 months ago

I reject the assertion that AI Vibe Coding has to have any affect on how OSS maintainers get paid (or not). Most of those that are paid, are paid because their job is related but the OSS library/project itself is not directly monetized. I don't see AI/Vibe coding changing this... except that now the maintainer can choose or not to accept or use those tools on their project or not.

But the assertion that everything needs to change is absurd. Articles like this are similar in my mind to arguments for communism because every artist deserves a living wage... that's just not how society can sustain itself in reality. Maybe in a world without scarcity, but I don't see scarcity going away any time soon.

sanskritical• 6 months ago

Open source software, by the admission of this article, is a critical input to AI agents useful for code generation. So the way I see it is that there is now an entire industry that is incentivized to financially support open source software for entirely new reasons. To keep the models trained on new languages, libraries, and developments in computer science, they need to make sure that high quality modern code is still freely available, forever.

Vibe coding eventually creates more value for FOSS, not less.

reustle• 6 months ago

There is a reasonable argument that there won’t be many new languages now that models are sufficiently trained. If anything, we may see languages optimized for models and not humans.

gegtik2• 6 months ago

Seems you are arguing that The Tragedy Of The Commons could never happen because people benefit from the Commons

mellosouls• 6 months ago

Sustaining OSS at its current scale under widespread vibe coding requires major changes in how maintainers are paid

A recent discussion on a related topic, apparently following the same misguided idea of how OSS is motivated:

https://news.ycombinator.com/item?id=46565281

(All my new code will be closed-source from now on: 93 points, 112 comments)

matkoniecz5• 6 months ago

from abstract

When OSS is monetized only through direct user engagement (...) Sustaining OSS at its current scale under widespread vibe coding requires major changes in how maintainers are paid.

so it applies to narrow slice of OSS

devinprater• 6 months ago

I'm completely blind. I like Linux. I've started to love Android since getting a Samsung and getting rid of OnePlus, cause accessibility. Termux is cool, but it's accessibility wasn't. So, I had Gemini rangle it up a bit into my fork of Termux [1]

Now it reads (usually) only newly incoming text, I can feel around the screen to read a line at a time, and cursor tracking works well enough. Then I got Emacs and Emacspeak working, having Gemini build DecTalk (TTS engine) for Termux and get the Emacspeak DecTalk speech server working with that. I'm still amazed that, with a Bluetooth keyboard, I have Linux, and Emacs, in my pocket. I can write Org and Markdown, read EPUB books in Emacs with Nov.el, look at an actual calendar not just a list of events, and even use Gemini CLI and Claude Code, all on my phone! This is proof that phones, with enough freedom, can be workstations. If I can get Orca working on a desktop environment in Termux-GUI. But even with just Emacs and the shell, I can do quite a bit.

Then I decided to go wild and make an MUD client for Emacs/Emacspeak, since accessible ones for Android are limited, and I didn't trust my hacks to Termux to handle Tintin++ very well. So, Emacs with Emacspeak it was, and Elmud [2] was born.

Elmud has a few cool features. First of all, since Emacspeak has voice-lock, like font-lock but for TTS, Ansi colors can be "heard", like red being a deeper voice. Also a few MUD clients have sound packs on Windows, which make them sound more like a modern video game, while still being text-based. I got a few of those working with Elmud. You just load one of the supported MUD's, and the sound pack is downloaded and installed for you. It's easy and simple. And honestly, that's what I want my tools to provide, something I, or anyone else who chooses to use them, that is easy to get the most out of.

None of this would have been possible without AI. None of it would have been done. It would have remained a dream. And yes, it was all vibe-coded, mostly with Codex 5.2 on high thinking. And yes, the code may look awful. But honestly, how many closed-source programs look just as bad or even worse under the covers of compilation?

[1] https://github.com/devinprater/Talking-termux-app

[2] https://github.com/devinprater/elmud

chfritz• 6 months ago

AI is poisoning the well from which it drinks. If OSS withers or dies, what will AI train on to get better? Same with StackOverflow.

wessorh2• 6 months ago

I think corporate cloud killed opensource, AI is simply a nail in its coffin. OpenAI's recent announcement did more for software patents than anyone could have ever done when they floated thy own of your ideas.

wessorh2• 6 months ago

geldedus• 6 months ago

Just stop calling AI-assisted coding "vibe coding"

grimmzoww• 6 months ago

Looking for solo devs testing AI continuation tool which i have built and need honest feedback if it is usefull or garbage if you are intersted in checking out - DM me

phendrenad2• 6 months ago

"kills" is a strong word. The phenomenon of single-purpose self-service apps is not to be ignored, and we'll likely see people not only do that, but create apps for friends and family, leading to everyone having an "app guy" who makes apps for them, the same way many people have a "car guy" who can diagnose car problems before they need to take it to the shop,.. but open-source still has a place in high-complexity products where a very small number of people have the requisite knowledge to vibe-code it. E.G. don't expect people to be vibe-coding their own Unix kernels any time soon!

Vibe coding kills open source

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