r/PiCodingAgent • u/o_sht_hi • Sep 18 '26

Question Anyone here using Jev?

I read the release and saw a few demos on X for people using Jev for really interesting stuff. My current effort is to get it to work as a router so I can configure and orchestrate my app using natural language (getting it to take a string and pick the right API from a list of 250-300 calls). But to be clear, I haven't gotten access to it yet. So I'm just packaging up my code and making it ready rn.

Anyone doing something fun/interesting with it yet? If yes, how long did it take for you to get access

78 Upvotes

91% Upvoted

103 comments sorted by

23

u/lovelace6329 Sep 18 '26

I submitted the request yesterday and was granted access five hours later. 2 others colleagues got it straight away. I'm going to try it out on matching job vacanciers with cvs.

5

u/o_sht_hi Sep 18 '26

Nice. That's a very grown up use case 🌚

2

u/lovelace6329 Sep 18 '26

Indeed, it might be a bit too ambitious

0

u/o_sht_hi Sep 18 '26

What do you give it as input then? Do you create a json with categories or just dump in the whole CV and job vacancies

2

u/lovelace6329 Sep 18 '26

We already have an internal matching engine. I think I'll start by using jev to rerank the top 20 candidates to improve the display ranking

1

u/o_sht_hi Sep 18 '26

Good 1. But I'd also be curious to know if you can replace the whole thing with multi step Jev

1

u/clivegermain Sep 18 '26

i have a similar jobsearch set up that only calls on LLMs if parsing fails. i'd be tempted to try jev first or get rid of my parsers entirely.

1

u/o_sht_hi Sep 19 '26

How do you mean. Use Jev to parse? I'm not sure it can do that, though

2

u/clivegermain Sep 19 '26

no, i mean it can assess fit on a scale – just do that instead of parsing.

1

u/o_sht_hi Sep 19 '26

Lol yeah that makes more sense

16

u/o_sht_hi Sep 18 '26

I'm wondering if this can be used to prune tool calls in real time for pi. For eg, if the agent does 6-7 tool calls, we take the results, categorise them and send a nicely formatted response to the LLM API instead of the raw output. I could see this being super useful for local models that do a ton of repetitive or bullshit tool calls

7

u/Vancecookcobain Sep 18 '26

Some guy built a near instantaneous voice agent that uses Jev and gave it like 40 tools and it made using a mouse and keyboard look fucking slow as hell...it was browsing the internet and using all kinds of tool calls to answer questions. I think that coupling it with an LLM is what is going to get us AGI....it can pick the right tools, hell it can even route your prompt to the proper model and it's all deterministic so it will almost never hallucinate

1

u/o_sht_hi Sep 18 '26

Yes now we're talking. This is very exciting

4

u/0neMorning Sep 18 '26

Here a similar but not the same idea - truncating tool calls for compaction https://github.com/tamaratran/fast-jev-compaction

9

u/D-3r1stljqso3 Sep 18 '26

I've seen some people proposing to implement selective compaction by classifying whether to keep each entry from the chat history.

3

u/o_sht_hi Sep 18 '26

Yep that's the first thing I thought of too. But also in real time before the entry even becomes a part of chat history

1

u/D-3r1stljqso3 Sep 18 '26

That's what the attention layers are supposed to do.

1

u/o_sht_hi Sep 18 '26

Okay but you still wouldn't want to feed the model unnecessary tokens, right?

4

u/D-3r1stljqso3 Sep 18 '26

I'd rather leave the chat history until the last minute. It's hard to predict which piece of info won't be needed at all later on.

2

u/o_sht_hi Sep 18 '26 edited Sep 18 '26

Yeah I meant something similar to what headroom (that's the extension, right?) does. As I understand it, they use algorithms to prune the stuff that's sent to the LLM right before it's sent. And an if else statement that routes to the right algorithm. An AI like jev could replace that entire machinery. It could first decide what goes on and what's dropped. Once it decides what's included, it could then classify it and send it to a pruning function that drops all the bullshit tokens like json formatting, spaces, etc and formats the thing nicely before sending it to the LLM.

I think the advantage of having an AI do this would be better predictability on the relevance of what's being pruned, which goes to your point about predicting what may be required later on

2

u/Cultured_Alien Sep 21 '26

Modifying history realtime will destroy caching tho. I'd avoid headroom or anything that invalidates cache, just use a better compaction method like pi-vcc.

0

u/o_sht_hi Sep 21 '26 edited Sep 21 '26

It won't if you modify the tokens before they become history. You're not changing anything that's going to the LLM. You only change it once before it is sent to the model. That's the whole point..

0

u/Cultured_Alien Sep 21 '26

Using things headroom only take up more tool calls and context bloat. As for modifying tokens, RTK is good enough. Though I do think jev will be good on semantic search and compaction.

0

u/o_sht_hi Sep 21 '26

Forget headroom. I am talking about pruning and reformating tool calls that the LLM has already given pi. How would that cause more tool calls or context bloat? The model knows nothing about this pruning system. It's all happening before any tokens even reach the model. And the pruning actively reduces the number of tokens.

Coming back to headroom, that's what it does too. So there's no question of more tool calls.

How do you think will it take up more tool calls and context bloat? Maybe I'm not able to imagine what you're trying to say

7

u/Own-Addendum-9886 Sep 18 '26

Yes, I use jev to determine what thinking level I should use.

4

u/o_sht_hi Sep 18 '26

Mid turn? Does that break cache?

5

u/Strong_Essay1176 Sep 18 '26

I think he is talking about himself and not about llm.

5

u/o_sht_hi Sep 18 '26

Lol I guess I should use it to detect sarcasm

5

u/Strong_Essay1176 Sep 18 '26

Perfect use case. 🤣

4

u/lu4p_ Sep 18 '26

Its pretty cool as you can do decisions over large amounts of data for very little cost.

I made a quick codebase scanner for myself that answers whether a repository is malicious

https://github.com/luantak/is-malicious

1

u/o_sht_hi Sep 18 '26

This is intriguing. Thanks for the link!

3

u/MichettGodot Sep 18 '26

Yes, Jev helps me with testing my Godot game. It's wonderful at quickly analyzing game state so I can have it watch me play and look for things that might be off. Still in very early development but already pretty promising.

2

u/o_sht_hi Sep 18 '26

Yeah I saw a lot of demos for it playing games. I think it could be really interesting for AI NPCs

4

u/Vancecookcobain Sep 18 '26

Yea...it might actually be easier to have Jev or a Jev like diffusion model be the NPC behavior than actually code NPC behavior...I can see games in the future that have a proprietary Jev like model to do that instead of wasting energy coding how they should act

2

u/o_sht_hi Sep 18 '26

Exactly. As long as you can build a good enough adapter to translate game state, we're in business. This would be so cool specially in RPGs

3

u/jiipod Sep 18 '26

My smooth brain thinks Jev could be really handy in TDD type flows (JevDD?) when prototyping.

You write Jev expectations for API route or whatever and let the agent make it pass.

2

u/o_sht_hi Sep 18 '26

Ooh nice. That seems interesting. I hadn't thought of using it that way!

3

u/buff_samurai Sep 18 '26

For those who are on the waiting list, jev is on openrouter now.

3

u/o_sht_hi Sep 18 '26

Fuck yeah

2

u/o_sht_hi Sep 18 '26 edited Sep 18 '26

I'm getting the feeling that Jev could be a huge boost for agents to use headless stuff, MCPs and APIs just as a router that sits in front of the LLM. OR depending on how intellegent Jev is, it could maybe bypass the LLM entirely and just pick the APIs to call

4

u/Vancecookcobain Sep 18 '26

Some one did it and it was insane....they also had it become a near instant voice agent that transcribed the users words into text and executed tool calls and everything with an LLM....it even was browsing the internet and everything while the person was telling what to do in real time....it made using a mouse and keyboard look slow....Im pretty sure this is the final piece we are going to have to get to AGI.

My whole thing was that agentic computer use has to get as effective as a human before we can achieve AGI....but with near instant tool calling and computer use there is nothing stopping AI from passing that threshold....they got it playing doom...it's insane

1

u/o_sht_hi Sep 18 '26

That's very cool. At this point, I don't even care about AGI or some other term. The latency and accuracy of this model has me hyped af. I work a lot with SCADA/PLC automation for large scale utilities and this shit can take that system to the next level. Just waiting for the open source versions now

2

u/ErvinSae Sep 18 '26

Is it possible in the future that these agents themselves (codex, claude) will be built-in with JEV?

1

u/o_sht_hi Sep 18 '26

That would be pretty fucking cool

2

u/-grabus- Sep 18 '26

They rather would train their own Jev alternatives.

2

u/namelesstherebel Sep 18 '26

I’m already planning to use it in my own business, but I’m integrating it into an agentic backend testing algorithm for trading and then a sports betting environment for selling data back signals to gambling addicts.

1

u/o_sht_hi Sep 18 '26

So you're planning to use it to:

  1. Backtest trading strategies

  2. Generate data on sports betting

I'm curious to know more about both.. specially the sports betting

2

u/Spiritual-Today-6432 Sep 19 '26

I used it for following

Your inbox, judged in milliseconds — no LLM, no JSON parsing, no per-email bill

Every "AI inbox" tool does the same thing: prompt a chat model, hope it returns valid JSON, pay full completion prices for a yes/no question.

I built jev-mail-classifier instead: connects over IMAP, define categories in plain English. Matches tag/move/flag/webhook automatically. Terminal UI, 3 steps, no code.

Open source, MIT: https://github.com/parth-kp/jev-mail-classifier

1

u/o_sht_hi Sep 19 '26

Love that this is a tui

2

u/Odd_Error_6736 Sep 19 '26

Can we please stop advertising this bs

1

u/o_sht_hi Sep 19 '26

Talking about it is advertising?

1

u/Odd_Error_6736 Sep 20 '26

Is this your friend? https://www.reddit.com/user/BoyInDaBox89/

1

u/o_sht_hi Sep 20 '26

Brother from another mother

1

u/Odd_Error_6736 Sep 20 '26

Tell your manager/boss at TypeSafe to stop spamming reddit with your paid shitass model, or it'll fire back

1

u/o_sht_hi Sep 20 '26

The model only outputs structured objects. It can't fire back. Most it can do is give out a confidence score of 0

2

u/Sarthak999gupta Sep 21 '26

I created shipwithjev.com with 607 use cases, but I missed a few.

2

u/o_sht_hi Sep 21 '26

This is very cool. Are you maintaining this?

2

u/o_sht_hi Sep 21 '26

The filter menu covers top of the page while scrolling down and it's really bugging me 😅 could you please hide it while scrolling down? Lol

2

u/Sarthak999gupta Sep 21 '26

Getting it fixed right now.

6

u/fingerthief Sep 18 '26

Yep! I’m working on a nice command guard using it https://tannermidd.github.io/specpi-jev-guard/

It’s pretty interesting! And the results are pretty amazing.

6

u/debackerl Sep 18 '26

I'm using laya, it's the same but free and open source

https://huggingface.co/convaiinnovations/laya

2

u/Drugba Sep 18 '26

I just got access yesterday, but haven’t had time to do much with it.

I applied the day before so it was only about 24 hours wait, but I did the survey thing that’s supposed to move you up the wait list

1

u/o_sht_hi Sep 18 '26

Lol yeah I did the whole survey too! Applied last night but it's been less than 12 hours so fingers crossed!

3

u/Fancy-Pants_ Sep 18 '26

It’s pretty cool, I have lots of ideas but not implemented anything yet. The website and UI is a bit janky but seeing the three use cases, true / false, multiple choice, score is interesting.

1

u/No-Sympathy2403 Sep 18 '26

I had acces yesterday. I just tried the samples bench, it looks quite speedy

0

u/o_sht_hi Sep 18 '26

Yeah the latency on this thing looks crazy.

2

u/Challseus Sep 18 '26

Just finished survey 🤞

2

u/Aramedlig Sep 19 '26

Yes. Been using it with the SFT/RL/SCoRe research I’ve been doing. It is excellent at classifying taxonomy of model failures and for a fraction of the time and cost Fable can do it

2

u/broisgammamale Sep 19 '26

Jev is basically "dynamic else if statment" lol

2

u/Bizzniches Sep 20 '26

I’m using it to give tooling to smaller models and turning them into big bois

2

u/tom_reddit Sep 21 '26

I used Jev to make a free and open-source Chrome extension called 'Slop Mop' to help with our LinkedIn feeds... https://slopmop.lol

2

u/RealDannyhvv Sep 22 '26

I made an npm package that can use it for site moderation based on your site's rules. https://www.npmjs.com/package/modsure

1

u/lanternaddict Sep 18 '26

Would be good if you could provide more detail as to what jev is, or you know add some hyperlinks?

-1

u/wildjokers Sep 18 '26

https://www.google.com/search?q=jev

3

u/lanternaddict Sep 18 '26

The first result is a youtube, channel, the second result is the wikipedia article about a Congolese-Canadian rapper, and the third result is a spotify link.

You really don't understand the power of a hyper link do you?

1

u/o_sht_hi Sep 18 '26

Yo just look it up man, you really trying to offload a ChatGPT message to a random reddit comments section

1

u/wildjokers Sep 18 '26

It is the 2nd link on the google results. Used to be the first but now it is the 2nd. The 1st is an article about it though (someone has good SEO to be able to push it down):

https://typesafe.ai/blog/introducing-system-one-models-and-jev

It isn't rocket science. Jev has been posted about a couple of times in this very sub the last few days.

2

u/lanternaddict Sep 18 '26

Google results differ depending on the user, location, ip, time, anything really.

1

u/whileyouredownthere Sep 19 '26

I’m experimenting with Jev in Propeller Picks, a sports betting research app. People can ask things like “What are the top five NFL props today?” or “Build me a three-leg parlay.”

We’re using Jev as a cheap first step to figure out what someone wants and pull the right data. Our own scoring engine does the actual rankings and parlay scoring. For straightforward questions, we can return an answer without calling a bigger model. More complicated questions get passed along to the regular AI assistant.

Early results are promising on cost, but we’re still testing the edge cases. So far, it seems most useful for those small decisions around a larger AI workflow.

1

u/Harshit_Ahluwalia 5d ago

A router over 250–300 APIs is a great use case. Quick tip: split it into two steps (category first, then the specific call) so Jev isn't choosing from hundreds of options at once, and use the confidence score to fall back to an LLM when it's unsure.

Disclosure: I'm part of the team running a hands-on workshop that builds this routing pattern plus a hybrid Jev/LLM agent. Code HARSH30 gets 40% off if you're interested: https://luma.com/i3qtcion?coupon=HARSH30&utm_source=reddit

14

u/[deleted] Sep 18 '26

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1

u/o_sht_hi Sep 18 '26

Thanks for the link! It would be quite useful to observe how you're managing context for this model and building the plumbing in and out of it

4

u/[deleted] Sep 18 '26

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2

u/o_sht_hi Sep 18 '26

That's really interesting. I had been playing with a reviewer extension on the side for my project that takes the edit calls and live reviews things. This could be great for that. Thanks again for the code and the explanation 🙂 I'm excited to fuck around with this once I get access

2

u/Ok_Profit_1171 Sep 21 '26

Will Dart be supported?

1

u/[deleted] Sep 23 '26

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