10 INSANE Jev Use Cases. It's Not What They Told You.

0:00Jeff is the most hyped AI model of the year, and it's not what they're telling you. They're calling it the next big model, a GPT killer. Some are even saying it's about to change AI coding forever, but it's none of that. It can't write, it can't code, it can't hold a conversation. I was able to beat it at a

0:20game of checkers without even trying. So, no, this is not a smarter Claude, it's not a GPT killer. What it is is a completely different kind of AI. And after this video, you will change the way you use every model you already pay for. Because here's what they skip in the hype. Jeff doesn't think, it decides in about 200 milliseconds, and the output is basically free. The guy who built it is an ex-OpenAI researcher who worked on the tech behind ChatGPT. So, in this video, I'm going to show you what Jeff actually is, the 10 ways I'd actually use it, and the places I would

1:03not use it just yet. Let's get started. Okay, so, what is Jeff? The easiest way to think about it is fast brain versus slow brain. Your slow brain is when you sit and reason through a problem. That's Claude, that's GPT, that's every model you have ever used. They think, they write, then they explain. Jeff is your fast brain, the part of your brain that looks at a shirt and just knows that it's blue. You don't have to think about what color it is, you just come to that

1:36awareness in the snap of a finger. That's Jeff for you in a nutshell. You hand it messy text, and it hands back one of three things: a yes or no answer, a pick from your list, or a score. And every answer comes with a confidence number, so you know when it's sure and when it's guessing. And here's the part that blows me away about all of this. Up until now, AI models have been racing towards which can be the smartest. And the smarter a model gets, the more time it can take to complete a simple task. I mean, try asking GPT-6 Astra to make thousands of tiny decisions, and you're

2:16going to be waiting minutes and paying for every word it thinks. Jev, on the other hand, can't ramble. It can't hallucinate a broken format, and it answers in about 200 milliseconds. Type safe, the company behind Jev, says it's up to 193 times faster and over 400 times cheaper than a normal model. And its output tokens are free. So, this isn't a model you chat with. It's more like a smart if

2:48statement you drop into your workflow. And that one small shift just unlocked a world of possibilities. So, let me show you the 10 places you can use Jev to your advantage. The first place I would point Jev is at a pile I don't want to read. Like, your inbox, for example, is an obvious choice. That's because you can hand it thousands of emails and ask it three things at once. Like, this automation I created. I gave it all of my emails and asked it, "Is this a receipt? Is this a brand deal? Or is this a scam?" And in a click of a

3:24button, you can see how quick this is. It can sort through every single thing. And there you go, done in 4 seconds. Cost us $0.007, and it was able to sort through 69 emails per second. Nice. And this isn't just for email. I mean, you can point it at your support tickets, your DMs, your YouTube comments, any stack of text you'd normally sort by hand or have an expensive AI sort by hand. It will do it better and faster than Claude, GPT, or any model. The second one is a bit of the same idea, but here's something else that's now possible thanks to Jev's speed of execution. You can have it

4:07create real-time filters on your browser feed, and it will tag every post as a page loads and break them down for you into different categories like breaking news, actual signal, or slop, for example. Like, look at this right now. Likely human, 84% likely human, likely human. We can actually, with this plugin, enable only AI slop. I only want to see AI slop. And we refresh, there you go. We'll only be able to see AI slop on our feed, and we can do the opposite. We can filter out AI slop from our feed. And I mean, you can do this on Twitter, you can do this on LinkedIn, on

4:46Reddit. This is just this open-source tool, even other websites, but the sky's the limit here. And you can even have it filter out, quote unquote, slop from your timeline in real time. This is a tool someone open-sourced, by the way, and it flags AI slop on X, Reddit, LinkedIn, wherever. As always, if you want the link to all the tools and all the resources I share in this video, I'll drop them all down on the first link in the description below. Moving on to use case number three. Here's where it can start helping you make money. If you have a lead pipeline or a CRM, say,

5:23for example, a lead fills out a form, Jev can score it instantly on how good of a fit it is for you. So, here you can see with this lead, it's a three out of three. With this one, it's a zero out of three. And based on how much of a fit or which type of lead it is, you know, you can customize this as much as you want, and you can have template replies for each type of lead. For example, template A, say for example, it's a a great fit of a lead, it's a three out of three, and they're in the AI niche, then it picks template A. Hi Maya, this

5:57is exactly the kind of build I do. Grab a 20-minute scoping call here. Say it's not a fit, for example, it's going to go with template D, which is a no. Hi Aisha, thank you for thinking of me, I'm not the right fit for this one. See how quick this is? And we can keep going. If it's a spam, it can just not answer at all. If it's a type B, so it's a marketing lead, for example, it can send them our marketing template. I mean, literally, what it can do is how creative you can get. Those are its limits, essentially, right? So, it can score leads for how well of a fit they

6:33are. It can see what type of lead that is in instances, and then it can decide which template is best for them in instances, literally in 300 milliseconds. There are so many ways you can expand and build on top of this. Now, here's a fun one. Up to here, Jeb's been sorting data, but you can drop it inside an agent as the thing that picks the next move. Someone built a flight booker where Jeb reads the page and chooses the next click every single step of the way, and it booked a flight in about 7 seconds. A normal model doing this is slow and pricey because it

7:14thinks out loud on every single click. But Jeb on the other hand, it it just moves. So, you can have Jeb control your computer for you much faster than any other model. I'll also include this free tool inside the first link in the description. All right, this next one is cool. It's a single text box, and as you type, Jeb figures out what you actually mean, and the box morphs into the right thing. If you type a date, you get a date picker. If you type a color, you get a color swatch. And it all happens in real time because of how fast Jeff is in deciding and executing on every

7:53single keystroke. This is an interface you could not build before. Use case number six is you can have Jeff power your website search bar. Instead of users having to type the exact keyword to find something on your website, you can have Jeff on the back end guess what they are looking for and populate the answers in real time. Previously, this was possible, but it needed whole embeddings pipelines and a vector database. It was expensive and it was a pain to set up, but this skips all of that. It grabs the keyword hits first, then Jeff reranks them by what you actually meant. And because Jeff is fast

8:35and it can't be talked out of its format, it makes for a perfect bouncer. And no, I'm not talking about a bouncer at the club. I'm of course talking about it being a bouncer for your AI agents. Say for example, you have a research automation for your AI agent. For example, an automation where every day you want Claude to fetch the top AI news. And the way Claude does it typically is it casts a wide net. It looks for things that might look like the answer you're looking for and it

9:08summarizes all that data back to you. Well, instead of Claude being the one who decides what to scrape and what to discard, you can wire Jeff in a way for it to be the primary bouncer on your sources. Meaning the information gets to Jeff first and it gets to quickly scan things like is this safe? Is this useful? Are we on goal or on target? Is this the answer essentially that we're looking for? So if you test this automation out, we click go and it cast the white net and look at this. Damn, this is quick. There you go. It scraped through 173 resources and it decided to

9:49hand 33 to Claude. I don't know if you saw just how quick it was doing this. But then, we can hand it to Claude and let Claude do the the work itself if you need the high thinking. Just look at the difference between how fast Jeff was and how much time Claude is taking to read just 33 items. Come on, Claude. Jeff was

10:11way faster than you. There you go. Claude finished its run, but all in all, um with this automation, I tested one with just Claude and one with Jeff. And now that we put Jeff in the middle in front of Claude, it spent 78% fewer tokens, essentially. So, without the bouncer, we spent 29,000 tokens on this request. With Jeff as the bouncer, we spent 6,000. The junk gets caught at the door before your expensive model ever sees it. The next use case is for anyone who runs ads. You can feed Jeff a stack of your competitors or your niches ad copies and have it break down every

10:53single one of them. It can look for things like what's the offer, what's the angle, what's the selling point, is it urgency, fear, a discount. And if we run it, then in a couple of seconds, you have a map of exactly what your whole market is running. Just like that. You can see the selling points that are working for them, save time, make money, easy, no skill. You can break down the types of hooks, the funnel stage, anything and everything you can think of in mere seconds. Hiring is the same thing here, but with higher stakes. You can hand Jeff every applicant and your criteria and it can score each one and

11:35cite the exact points that earned that score. One company, for example, put Jev in front of their recruiting search and went from minutes to practical seconds. And at the same time, the data was accurate. So, fast and accurate. You're not letting it hire, essentially. You're letting it hand you the short list much faster. And finally, this is the one that makes everything we've covered so far click. You put Jev in front of your whole stack. Everything that comes in,

12:07it looks at and decides where it goes. Cheap stuff, send it to our automation bots. Questions, to the thinking bots. Important stuff, send it directly to me. That's the essential idea here. You stop paying a frontier model to read your spam and you only spend the big money on the things that actually need the brain. Now, here's a fair warning. This is where all the hype on social media falls apart. Jev is dumb and that's on purpose. It can't reason that checkers game you saw me play against it from the video's intro, for example. It lost because it makes a snap call every move and forgets the one before. It has a

12:52tiny context window, a fraction of what Claude or GPT give you. And the answers aren't guaranteed right. The format is locked, but the concept is a fast guess with a confidence score. So, test it before you trust it. That rhymes. And here's a kicker. The single most popular Jev demo online is from someone who used Jev to compact Claude's memory. The post got thousands of likes, but it's one of the worst things you can do with Jev because Jev doesn't have the reasoning or the context to compact well. Same story with using it to judge another AI's answers or to write text one letter at a time. You can have it do those

13:36things. It's just that that would be a bad idea. It's a snap decision model. So, give it snap decisions. So, here's where I land. Jev is not a better model than Claude or GPT and it's not trying to be. It's the cheap fast layer that goes in front of them. If I'm building anything that makes the small decision thousands of times, I would put Jev there and save the expensive models for the actual thinking. That is the unlock Jev gives us. It's not the model that replaces your AI. It's the model that stops your AI from burning money where it's not needed. Comment which of the 10

14:19use cases I mentioned you'd build first and I dropped all 10 setups in a free document. The link is in the description below so you can steal any of them. And if you enjoyed this video, make sure to leave a like and if you're new to my channel, then subscribe because I have a ton more content like this coming your way. Oh, and the algorithm gods just told me you're very likely to enjoy this next video as well. So, click it and

14:46I'll see you there.