Did Jev take off briefly and stopped getting talked about a few days later? Yes.
But that doesn't make it a failure. In the era where we have:
a) an AI hype cycle where the benchmark of "successful product" is ChatGPT, Claude Code, etc.
b) a social media environment that only rewards the most-engaged content
It's easy to declare something "fell off" because it didn't immediately revolutionize how everyone does their daily work.
But by that measure, nearly everything is a failure, even if it creates great businesses. That's especially true for infrastructure that runs in the background.
The author ironically thinks people talking about a product is more indicative of its success than its success – which is hype, the very thing he railed against.
E every 2 weeks we have a new hype cycle so all in according to how stuff already works I don't see something special here. I use jev, but it does not solve all my problems.
They literally raised $870 million this month. It's like people think the hype cycle = success of business for some reason. I'm sure a couple of months later, they're going to release something new, hire a lot of PR, and the same people will be "man, Jev had fallen but this new [xyz] brings them so back! [xyz] industry will now be dead!"
HN has a funny was of bubbling up low value article such as this.
Jev is far from being a fallen software. It works and it works well. Just because no one is talking about it does not make it a failure.
We reached inverse hype: where the folks jaded by hype are so jaded that they start to hype the same low value content they normally deride... as long as it speaks counter to any hyped topic.
Ironically, that technique usually pans out since a lot of useless fads get hyped. But every once in a while it causes people to completely and utterly miss the point.
After reading the article I can see that the comments here are a bit off. For example see this quote from the article:
> It’s not dead. Some companies use it while I believe the majority of use cases are addressed by open-weight rivals.
The point the article is making is the incredible way Jev specifically caused insane hysteria and hype, and just as suddently faded away. Not that it's dead or that the concept is severely flawed.
contrary to what i feel is extreme negativity of the author, to me it seems Jev is one of the only novel releases that lived up to the hype and has staying power. Not only that it jump started a whole new "classifier" war, leading to now things like cloudflare's clairic for extraction.
We use it in production. Tested a bunch of alternatives (openai decision api, llm based approaches) and they are either too slow or not as good. But mostly too slow.
Typesafe over-hyped their useful product and successfully got it in front of AI devs. So to be assholingly snarkily reductive I can sum this up as
"founder did founder shit well"
Yeah but do Openrouter stats represent local classifiers? Unlike LMs decision models are quite likely to run at edge, especially because their utility for a specific task improves with training.
> It’s not dead. Some companies use it while I believe the majority of use cases are addressed by open-weight rivals.
The quality of the answers on my datasets are in another league compared to the benchmarks.
I have a mixed language dataset, Jev answers only lack some accuracy, the open weight rivals output just look like random noise
I think there seems to be extremes in both ends and in my opinion neither of these extremes are the ICP. If you're using AI to finish your work, you're not the ICP. If you're building a product and want to implement AI in your product, you're the ICP.
The article says that other models are better at performance or cost. But whaz is not mentioned? Models that are _better_. From my testing, most models are much worse. And if you do an analysis on quality/performance/cost no one is beating Jev. Heck, no one is beating it at performance and cost at the same time.
There‘s a lot of hype with many releasing their decision models the past weeks. But all are worse. So maybe the years they spent in stealth is something you cant replicate in two weeks?
Look up Laya. Also the notion of "best" is flawed because half of that equation depends on the use case. Benchmarks try to answer that by creating artificial use cases and test in isolation but that's not the concrete answer for a given use case either.
Jev feels like what happens when people that have had no serious statistics get a glimpse of what statistics makes possible. I'm not talking about the developers of Jev, I'm talking about the uninformed that went all hype cycle on it. It's well designed and the advanced system a good statistical programmer would write.
this actually very useful where you can rely your classical programming logic with coefficients provided by jev decision model results if (jevResponseJudge < 0.3) doSomething() else doNothing()
how would u code with LLM in such cases? parse responses for keywords? xd
no, they provide very useful interface. Just try it before writing posts about "hype".
Seems to me most of the comments here miss the main point of the article about the pattern of hyped marketing (name dropping and jargon, ambiguity and inflated expectations, drama).
In the digital age, the "fall" of anything just means you, and the people in your bubble, stop using it. It could be something that enough people get value out of it that they can afford to pay for the domain name, and a bunch of other stuff, and you'd never even know. So to claim anything falls, well. There's Yahoo, AOL, Kodak, Snapchat, Facebook, Twitter, and Zombo.com. And they ain't going away.
Doomerism + Wishful thinking. We are what ~3 years into mass adoption of llm tech? Every couple of months it improves. Jev came out a couple of months ago and there is nothing that makes me believe that it will not improve over time as people fine tune small models to work better over time.
But that doesn't make it a failure. In the era where we have:
a) an AI hype cycle where the benchmark of "successful product" is ChatGPT, Claude Code, etc. b) a social media environment that only rewards the most-engaged content
It's easy to declare something "fell off" because it didn't immediately revolutionize how everyone does their daily work.
But by that measure, nearly everything is a failure, even if it creates great businesses. That's especially true for infrastructure that runs in the background.
The author ironically thinks people talking about a product is more indicative of its success than its success – which is hype, the very thing he railed against.
No one was talking about PHP last week either. Till we all got a reminder that a massive chunk of the web is still happily running on it.
Being talked about is a terrible metric for anything other than how much people are talking about something.
Ironically, that technique usually pans out since a lot of useless fads get hyped. But every once in a while it causes people to completely and utterly miss the point.
> It’s not dead. Some companies use it while I believe the majority of use cases are addressed by open-weight rivals.
The point the article is making is the incredible way Jev specifically caused insane hysteria and hype, and just as suddently faded away. Not that it's dead or that the concept is severely flawed.
really early to call it "the fall of jev"
It's the top model for classification.
The quality of the answers on my datasets are in another league compared to the benchmarks. I have a mixed language dataset, Jev answers only lack some accuracy, the open weight rivals output just look like random noise
There‘s a lot of hype with many releasing their decision models the past weeks. But all are worse. So maybe the years they spent in stealth is something you cant replicate in two weeks?
this actually very useful where you can rely your classical programming logic with coefficients provided by jev decision model results if (jevResponseJudge < 0.3) doSomething() else doNothing()
how would u code with LLM in such cases? parse responses for keywords? xd
no, they provide very useful interface. Just try it before writing posts about "hype".
Sure. And yet...