. It received 227 points and 35 comments.

I played around with Jev last night and did it for classification tasks that I used Gemini 2.5 flash lite with.

It’s a bit faster and bit cheaper, but this is compared to LLM. The consistency was nice to see, BUT, as someone who trained NLP models prior to LLMs, it’s just BERT with more data. I can see why people would want ready made one shot classifier, and I can see the value of sending multiple classifier in one call, but I wouldn’t call it breakthrough. And I believe many labs will replicate it in no time and might have it as part of their harness.

I see it as a wake up call for the tech community to go back to basics for most tasks instead of relying solely on generic LLMs.

tech

This link was posted by [nandakishor_ml](https://news.ycombinator.com/user?id=nandakishor_ml) 3 hours ago on [HN](https://news.ycombinator.com/item?id=49765348). It received 227 points and 35 comments.

[Top comment](https://news.ycombinator.com/item?id=49765997) by [Oras](https://news.ycombinator.com/user?id=Oras):

> I played around with Jev last night and did it for classification tasks that I used Gemini 2.5 flash lite with.
> 
> It’s a bit faster and bit cheaper, but this is compared to LLM. The consistency was nice to see, BUT, as someone who trained NLP models prior to LLMs, it’s just BERT with more data. I can see why people would want ready made one shot classifier, and I can see the value of sending multiple classifier in one call, but I wouldn’t call it breakthrough. And I believe many labs will replicate it in no time and might have it as part of their harness.
> 
> I see it as a wake up call for the tech community to go back to basics for most tasks instead of relying solely on generic LLMs.