Jev AI Full COURSE 1 HOUR (Build & Automate Anything)

Julian Goldie (0:00)

GEV AI, the full one-hour course on how to build and automate anything. So today we're going to be talking about GEV AI, how to use it, how to use it for free, how to basically build and automate anything. And this is the full course, step-by-step, walking you through what might be the most revolutionary AI model that's just dropped this year. And it's a totally different class of model for AI that can potentially make your AI models 20 to 200 times faster, and 40 to 400 times cheaper. And you can basically build and automate anything. So you can see, for example, in this post from Ronak, he actually built out a system where Jeff is playing Minecraft. You can also get it for free.

We'll be talking about how to use it, GitHub projects, what Jeff AI is, how it works, how to build and automate AI apps with Jeff, how to control your computer with Jeff AI voice agents, how to reduce token costs on Astra 6 and Claude Table 5 using the system, and also 10 example builds with Jeff AI and actual use cases. So feel free to check out whichever bit you're interested in. By the way, if you want to get access to this for free, it is free until September 25th as of making this. If you're watching it after that point, well, you can actually get Jeff directly from Open Router, and then you can create an API key like this. Once you've done that, you can actually just go into any AI agent, whether that's ChatGPT or Claude, and start using it. Now, if you want to see some examples of what we've built with it, you can use it for controlling your browser with your voice, for example. You could even, for example, have a live app like you can see right here, which we can basically use extremely fast and pretty much real time using this system right here combined with Jeff AI. So you can basically build and automate anything, and it is unbelievably powerful. So with that, let's just get straight into it, and we'll start talking about what Jeff AI is, where you can use it, the use cases. And again, we'll be covering all of this. The person behind it is one of the people who actually co-invented Chat Cheapertee. His name is Diogo Almeida. He spent the last two years quiet, building a new way to train models. And this week, he released GEV. J-E-V. And the numbers he put on it are 20 to 200 times faster than a normal AI model, and 40 to 400 times cheaper. And then, somebody actually plugged it into Claude Code as a plugin, one second later, that Claude session went from nearly like 1 million tokens down to 86,000. One second, same work, same session, but a fraction of the context, which is pretty wild.

So, what actually is this thing? And why is everyone building with it inside a week? Well, GEV is not a chatbot. It's not a coding model. It doesn't write at all. You can't ask it for an email. You can't ask it for code even. You can't even ask it to explain why it picks something. What it does do is make decisions, fast ones, thousands of them. So, you can hand it the current decision and the current situation. You hand it a question with set answers. It picks one and tells you how sure it is. Now, TypeSafe AI, the company behind it, calls this a system one model.

So, you want to think of it like the fast part of your brain. When you see a red light, you don't write a paragraph about the red light. You just stop. That's system one. Writing the paragraph is system two. And right now, every AI agent you run uses the paragraph brain for everything, including the red lights. Now, here's what that actually looks like in real life. Let's say, for example, you have an agent doing research for you. Along the way, it has to answer a pile of tiny questions. Do I have enough sources yet? Should I right now keep looking? Is this good enough to send, or should a person check it? Which tool do I use next? And every one of those tiny questions currently goes to a big model, a big model that reads the whole history, thinks about it, writes out its reasoning, formats it, hands it back, seconds go by, tokens get spent, and the actual answer was one word. That's the gap Jev feels. And once you understand that gap, you start seeing everywhere in your own setup. And there are three kinds of questions you can ask it, and they cover almost everyone. So the first one is choice. You pick from a list. Which step goes next? Which folder does this go in? Which of my writers handles this? It gives you the pick plus a probability for every option, plus how confident it is overall. The second is score. So you would rate this against levels you define yourself. How relevant is the source on the scale from unrelated to directly on topic? How strong is this lead? It gives you a number back and it can land between levels, not just on them. And the third one is called null. It's a yes or no.