Jev is HERE. How to use it
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What is Jev and why is it a game‑changing AI classifier?
JEV is here and it's a big deal. It was created by Diogo Almeida.
How does the 1,700‑email triage demo illustrate Jev’s speed and cost?
Yes, that's the same guy whose research built ChatGPT. Now it's such a big deal because it's a whole new way to do AI.
Why is Jev described as an AI decision‑maker rather than a text generator?
So I brought on my friend Ryan, who's on the founding team of Open Code, to just come on and clearly explain what JEV is, what are some insane use cases, and break down some startup ideas that are now on. Unlocked. As of publishing this, Jev is invite only, but good news, by the end of the episode, you're gonna see how you can get access today.
How can businesses integrate Jev for lead scoring, support routing, and other fast decisions?
So you're gonna want to like, comment, and subscribe right now so your algorithm knows to bring you content like this to get your creative juices flowing in the future. Happy Jev Day, and I'll see you at the end of the episode.
What startup idea uses Jev for instant local‑service matching and quoting?
Stop up and
Ryan Vogel, welcome to the pod.
Which real‑world use cases (Bitcoin signals, video clipping, browser control) showcase Jev’s versatility?
By the end of the episode, what are people gonna learn?
We're gonna learn about a new type of AI.
How can listeners get immediate access to Jev via the Vercel AI Gateway?
An a type of AI that we haven't really seen before, but I think it's good. It's JEV.
What are the final takeaways and why should listeners start experimenting with Jev today?
And uh people are ready for this new type of classifier AI because we've been so used to just learning and using these LLMs, which are slow, they stream. And I think uh, as we'll cover today, this AI is. Fundamentally different in so many different ways with quality, speed and price that there are so many different applic usage applications for it that the possibilities are truly endless and it just becomes on the humans again about how creative you can be.
Cool. And I so I just have a few things I need from you because I haven't used Jev. I want you to give me the simplest possible explanation to Jev. I want you to ex give me like, you know, three or four insane use cases so that people can walk away from this episode with like productivity, making money, just like, you know, even boring use cases that could become, you know, ten million dollar businesses, a hundred million dollar businesses. And I just want you to put it all together, wrap it in a bow that people understand, you know, if they stick around to the end, that they'll be able to understand why they should care about it. Can you commit to that, Ryan Vogel?
I can, I can, and I'll add one better. I'll make it entertaining so that way you can actually get excited about it. Because first up, I'm just gonna start out with a demo. This is my email. I'm not afraid to share it. I uh been working with email. If you know me at all, you know that I love email because it seems unsolved. I mean, like, Greg, how many spam emails do you get every day? Like There's too many, right? There's too many. You can't reply to all of them. And it's just so frustrating. And some of the email algorithms that exist are good, but it's not the best. But then some people are trying to like take like traditional AI, where it's like they're having like a GPT 5.6 Luna, like kind of read every email and then score it.
But that takes time and it's not like instant. And it's just like, oh, I wish we could just have. So This is that. This is using JE. And before I run it, uh, I'm gonna break down JEV in a super simple example. Jev is a classifier. At its truest being, that's what it is. I won't get into the architecture and stuff like that because honestly, I don't even understand it that well. But essentially, you define an input. Let's say uh you have this iPhone as an input, right? And That's the input. And then the output is a schema. So we could uh have the schema be what color is the iPhone is the question almost. And it has uh blue, orange, red, green, yellow as the output options for that question. And the classifier Jev then looks at this phone.
in a text uh format and says, hmm. What uh Is this orange? Is it is it red? It could be red, but then it says, okay, this is about, I'm pretty confident it's 80% orange, but it could be 10% red or it could be 10% blue, which adds up to 100. And it's the probabilities of those choices. So it's not just going to be a 100% affirmative, this is orange, this is blue. This is red, it's uh, hey, I'm 80% confident that this is orange or this is red. And the best way to illustrate that is with this email example.
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Chapters
8 chapters
1
What is Jev and why is it a game‑changing AI classifier?
0:00–0:04
2
How does the 1,700‑email triage demo illustrate Jev’s speed and cost?
0:04–0:13
3
Why is Jev described as an AI decision‑maker rather than a text generator?
0:13–0:34
4
How can businesses integrate Jev for lead scoring, support routing, and other fast decisions?
0:34–0:46
5
What startup idea uses Jev for instant local‑service matching and quoting?
0:46–0:55
6
Which real‑world use cases (Bitcoin signals, video clipping, browser control) showcase Jev’s versatility?
0:55–1:01
7
How can listeners get immediate access to Jev via the Vercel AI Gateway?
1:01–1:07
8
What are the final takeaways and why should listeners start experimenting with Jev today?
1:07–28:23