I couldn't find the right label for the code that AI produces but I think "prototype" is the best one so far. My experience, even though I'm deep in the infrastructure trenches, supports what you say here.
It's a tragicomic to witness an industry that has spent decades trying to figure out how to measure developer productivity fall over itself for any product that claims to improve said productivity by 20-1000% without anything to back it up.
Unfortunately, the industry has a bad habit of building prototypes and putting them into production. Perhaps it's simple ignorance combined with misaligned incentives, where business decisions are often made by people with a weak grasp of technology. What comes to mind is the recent Tea app fiasco. Or a tweet (or substack note?) that said something along the lines of "AI will build your app, then you just need to scale it." Outfits like Facebook and Google have invested million employee-years of effort into "just scaling it", so that kind of statement betrays how disconnected from reality a speaker is.
That is to say, I expect vibe-coding to be like crack cocaine for a large'ish group of people. We'll see a flurry of launches followed by a wave of crashes and data breaches, until at some point pushback builds up in engineering culture.
I do think that even if progress in AI stopped today, it would take us years to fully realize the potential of this technology, and it will at least as large as the deployment of the Internet. But vibe-coding and the dream of the AI-supercharged-100x-developer seem like nothing but dreams at the moment.
1. We are, indeed, completely lost in terms of productivity. We definitely can grasp developers' perceptions. However, these perceptions seem to be disconnected from reality, as a recent METR study showed https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ (note, I don't use it as an argument that AI makes us slower, as the study received some criticism regarding the setup, but rather how AI shifts our perceptions).
Besides perceptions, though? We still roam dangerously close to raw output with complete disregard for whether it actually adds any value or not.
2. As an industry, we do put a lot of prototypes out there, true. And for a good reason. We build a lot of unproven things. Turning them into fully-fledged products would not be economically viable.
Having said that, we utterly fail to recognize when it's time to reset the development strategy, from "let's throw spaghetti on the wall and see what sticks" to paying off the tech debt, taking care of security seriously, rebuilding the fundamentals to prepare for scaling, etc.
I think the Tea app fiasco is a perfect example here.
3. The appeal of vibe coding comes from the visible part of the outcome. We can prompt our way to get a working app with no technical knowledge whatsoever. I am genuinely impressed.
And yet, I have enough technical knowledge to understand what is happening behind the scenes with the code and what it means for the product's long-term sustainability (i.e., it kills it).
4. And yes, there will be many security breaches prying on unsupervised or not-supervised-enough AI-generated code. We already have bad actors exploiting AI weak spots, such as hallucinations: https://en.wikipedia.org/wiki/Slopsquatting
I couldn't find the right label for the code that AI produces but I think "prototype" is the best one so far. My experience, even though I'm deep in the infrastructure trenches, supports what you say here.
It's a tragicomic to witness an industry that has spent decades trying to figure out how to measure developer productivity fall over itself for any product that claims to improve said productivity by 20-1000% without anything to back it up.
Unfortunately, the industry has a bad habit of building prototypes and putting them into production. Perhaps it's simple ignorance combined with misaligned incentives, where business decisions are often made by people with a weak grasp of technology. What comes to mind is the recent Tea app fiasco. Or a tweet (or substack note?) that said something along the lines of "AI will build your app, then you just need to scale it." Outfits like Facebook and Google have invested million employee-years of effort into "just scaling it", so that kind of statement betrays how disconnected from reality a speaker is.
That is to say, I expect vibe-coding to be like crack cocaine for a large'ish group of people. We'll see a flurry of launches followed by a wave of crashes and data breaches, until at some point pushback builds up in engineering culture.
I do think that even if progress in AI stopped today, it would take us years to fully realize the potential of this technology, and it will at least as large as the deployment of the Internet. But vibe-coding and the dream of the AI-supercharged-100x-developer seem like nothing but dreams at the moment.
There are several great observations here:
1. We are, indeed, completely lost in terms of productivity. We definitely can grasp developers' perceptions. However, these perceptions seem to be disconnected from reality, as a recent METR study showed https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/ (note, I don't use it as an argument that AI makes us slower, as the study received some criticism regarding the setup, but rather how AI shifts our perceptions).
Besides perceptions, though? We still roam dangerously close to raw output with complete disregard for whether it actually adds any value or not.
2. As an industry, we do put a lot of prototypes out there, true. And for a good reason. We build a lot of unproven things. Turning them into fully-fledged products would not be economically viable.
Having said that, we utterly fail to recognize when it's time to reset the development strategy, from "let's throw spaghetti on the wall and see what sticks" to paying off the tech debt, taking care of security seriously, rebuilding the fundamentals to prepare for scaling, etc.
I think the Tea app fiasco is a perfect example here.
3. The appeal of vibe coding comes from the visible part of the outcome. We can prompt our way to get a working app with no technical knowledge whatsoever. I am genuinely impressed.
And yet, I have enough technical knowledge to understand what is happening behind the scenes with the code and what it means for the product's long-term sustainability (i.e., it kills it).
4. And yes, there will be many security breaches prying on unsupervised or not-supervised-enough AI-generated code. We already have bad actors exploiting AI weak spots, such as hallucinations: https://en.wikipedia.org/wiki/Slopsquatting
The need to understand good old engineering principles doesn't go away. In fact, if anything, it becomes even more important: https://pawelbrodzinski.substack.com/p/vibe-coding-doesnt-replace-tech-skills