I smell clickbait
this post was submitted on 02 Feb 2026
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Only until AI investor money dries up and vibe coding gets very expensive quickly. Kinda how Uber isn't way cheaper than a taxi now.
This.
until AI investor money dries up
Is that the latest term for "when hell freezes over"?
Microsoft steeply lowered expectations on the AI Sales team, though they have denied this since they got pummelled in their quarterly and there's been a lot of news about how investors are not happy with all the circular AI investments pumping those stocks. When the bubble pops (and all signs point to that), investors will flee. You'll see consolidation, buy-outs, hell maybe even some bullshit bailouts, but ultimately it has to be a sustainable model and that means it will cost developers or they will be pummeled with ads (probably both).
A Majority of CEOs are saying their AI spend has not paid off. Those are the primary customers, not your average joe. MIT reports 95% generative AI failure rate at companies. Altman still hasn't turned a profit. There are Serious power build-out problems for new AI centers (let alone the chips needed). It's an overheated reactionary market. It's the Dot Com bubble all over again.
There will be some more spending to make sure a good chunk of CEOs "add value" (FOMO) and then a critical juncture where AI spending contracts sharply when they continue to see no returns, accelerated if the US economy goes tits up. Then the domino's fall.
Hah, they wish. It's a business, and they need a return on investment eventually. Maybe if we were in a zero interest rate world again, but even that didn't last.
Unless I misunderstood, it will eventually dry up? Investors aren't going to be willing to give money with no returns indefinitely
You say "dries up" like that wasn't always the end goal for rideshare apps. Disrupt, overtake, starve out, hike prices.
With Uber that was indeed the plan and it worked. The same plan was there for AI, but AI isn't doing so well on the whole overtake and starve out thing. They'll have to jump directly to hiking prices. So it's only kinda like Uber.
You sure?
They are targeting the next generation, the next generation will not know how to search the internet without an AI chatbot
We all know that most parents will just let the “Digital Natives” do their thing or/and that kids in a certain age definitely know better than their parents who fear this “technological leap” and don’t get it anyway
I wouldn't be surprised if that's only a temporary problem - if it becomes one at all. People are quickly discovering ways to use LLMs more effectively, and open source models are starting to become competitive with commercial models. If we can continue finding ways to get more out of smaller, open-source models, then maybe we'll be able to run them on consumer or prosumer-grade hardware.
GPUs and TPUs have also been improving their energy efficiency. There seems to be a big commercial focus on that too, as energy availability is quickly becoming a bottleneck.
So far, there is serious cognitive step needed that LLM just can't do to get productive. They can output code but they don't understand what's going on. They don't grasp architecture. Large projects don't fit on their token window. Debugging something vague doesn't work. Fact checking isn't something they do well.
They don't need the entire project to fit in their token windows. There are ways to make them work effectively in large projects. It takes some learning and effort, but I see it regularly in multiple large, complex monorepos.
I still feel somewhat new-ish to using LLMs for code (I was kinda forced to start learning), but when I first jumped into a big codebase with AI configs/docs from people who have been using LLMs for a while, I was kinda shocked. The LLM worked far better than I had ever experienced.
It actually takes a bit of skill to set up a decent workflow/configuration for these things. If you just jump into a big repo that doesn't have configs/docs/optimizations for LLMs, or you haven't figured out a decent workflow, then they'll be underwhelming and significantly less productive.
(I know I'll get downvoted just for describing my experience and observations here, but I don't care. I miss the pre-LLM days very much, but they're gone, whether we like it or not.)
It actually takes a bit of skill to set up a decent workflow/configuration for these things
Exactly this. You can't just replace experienced people with it, and that's basically how it's sold.
Yep, it's a tool for engineers. People who try to ship vibe-coded slop to production will often eventually need an engineer when things fall apart.
This sounds a lot like every framework, 20 years ago you could have written that about rails.
Which IMO makes sense because if code isn't solving anything interesting then you can dynamically generate it relatively easily, and it's easy to get demos up and running, but neither can help you solve interesting problems.
Which isn't to say it won't have a major impact on software for decades, especially low-effort apps.
So far, there is serious cognitive step needed that LLM just can't do to get productive. They can output code but they don't understand what's going on. They don't grasp architecture. Large projects don't fit on their token window.
There's a remarkably effective solution for this, that helps both humans and models alike - write documentation.
It's actually kind of funny how the LLM wave has sparked a renaissance of high-quality documentation. Who would have thought?
High-quality documentation assumes there's someone with experience working on this. That's not the vibe coding they're selling.
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Can you cite some sources on the increased efficiency? Also, can you link to these lower priced, efficient (implied consumer grade) GPUs and TPUs?
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Vibe coding is a black hole. I've had some colleagues try and pass stuff off.
What I'm learning about what matters is that the code itself is secondary to the understanding you develop by creating the code. You don't create the code? You don't develop the understanding. Without the understanding, there is nothing.
Yes. And using the LLM to generate then developing the requisite understanding and making it maintainable is slower than just writing it in the first place. And that effect compounds with repetition.
TheRegister had an article, a year or 2 ago, about using AI in the opposite way: instead of creating the code, someone was using it to discover security-problems in it, & they said it was really useful for that, & most of its identified things, including some codebase which was sending private information off to some internet-server, which really are problems.
I wonder if using LLM's as editors, instead of writers, would be better-use for the things?
_ /\ _
A second pair of eyes has always been an acceptable way to use this imo, but it shouldnt be primary or only
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LLMs definitely kills the trust in open source software, because now everything can be a vibe-coded mess and it's sometimes hard to check.
LLMs definitely kills the trust in ~~open source~~ software, because now everything can be a vibe-coded mess and it's sometimes hard to check.
Might make open source more trustworthy, It can't be any harder to check than closed source.
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yeah it's to the point now where if I see emojis in the readme.md on the repo I just don't even bother.
I used to use emojis in my documentation very lightly because I thought they were a good way to provide visual cues. But now with all the people vibe coding their own readme docs with freaking emojis everywhere I have to stop using them.
Mildly annoying.
Check out this one I came across earlier - https://github.com/Jtensetti/fediverse-career-nexus/blob/main/README.md
It's a federated LinkedIn. ofc it's vibe coded.
Man... of all the vibe coding tools, Lovable has gotta be one of the most useless, too.
I work with people (all middle managers) who love Loveable because they can type a two sentence description of an app and it will immediately vomit something into existence. But the code it generates is an absolute disaster and the UIs it designs (which is supposed to be its main draw) is some of the most generic crap I've ever seen.
0/10, do not recommend.
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Interesting. I thought this will be another post about slop PRs and bug reports but no, it's about open source project not being promoted by AI and missing on adoption and revenue opportunities.
So I think we definitely see (and will see more) 'templatization' of software development. Some ways of writing apps that are easy to understand for AI and are promoted by it will see wider and wider adoption. Not just tools and libraries but also folder structures, design patterns and so on. I'm not sure how bad this will be long term. Maybe it will just stabilize tooling? Do we really need new React state management library every 6 months?
Hard to tell how will this affect the development of proper tools (not vibe coded ones). Commercial tools struggling to get traction will definitely suffer but most of the libraries I use are hobby projects. I still see good tools with good documentation getting enough attention to grow, even fairly obscure ones. Then again, those tools often struggle with getting enough contributors... Are we going to see a split between vibe coded template apps for junior devs and proper tools for professionals? Will EU step in and found the core projects? I still see a way forward so I'm fairly optimistic but it's really hard to predict what will happen in a couple of years.
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Eh. I never considered myself some hard-core old professional, but:
The LLM will not interact with the developers of a library or tool, nor submit usable bug reports, or be aware of any potential issues no matter how well-documented
If an LLM introduces a dependency, I will sure as hell go see it myself. Enough people do not do that for this to become a problem?
ever heard of node.js?
Heard, not used though. Jokes about isEven(tm) too, but I never thought it goes like this in anything intended for external use
there's at least one guy i know of on github whose claim to fame is he finds code in existing node codebases by big corpos that's duplicated, breaks it out into a library, then PRs the original codebase with "instead of doing manually, switch to depending on this library", then adds to his profile "my code is used by ". he had thousands of libraries like that last i checked, most of them less than ten lines of code. the manifest and other boilerplate is way larger than the actual code.
Damn. isEven come alive. But hilarious enough to watch someone do it :)
Your node_modules directory can get so bloated that the community came up with different package managers just for deduplication! pnpm, for example, makes one global-adjacent cache, and then just symlinks the dependencies as needed. This is because the regular npm doesn't, because what if the package changed between the 20ms since I downloaded it for nuxt? (Sorry Nuxt users, had to pick a name)
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There's a term called "dependency hell". Sure, this one dependency is fine, but it depends on 3 other libraries, those 3 depend on a sum of 7 others, etc...
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Microslop played the long game when they bought github
If the abominable intelligence is killing every corner of things we consider good its time to start killing the "AI"...
Open source is not only about publishing code: it's about quality, verifiable, reproducible code at work. If LLMs can't do that, those "vibe coding" projects will hit a hard wall. Still, it's quite clear they badly impact the FOSS ecosystem.
I've been wondering if Stremio has been doing this they had no updates for years and now at least one every week that breaks more things. I'm on the old one just watching the chaos unfold.
The killing part is not necessarily people vibe coding programs into OSS projects, but even if the OSS itself is not vibe coded, people using AI to integrate with it will result in lower engagement and thus killing the ecosystem:
Together, these patterns suggest that AI mediation can divert interaction away from the surfaces where OSS projects monetize and recruit contributors.
From Section 2.3 of the reported paper.
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