Video m7oLuUo7DBo

[00:00] You can build an entire team of AI agents right now, and it's way easier than you think. One researches your market every morning and hands you a finished report before you even wake up.

[00:12] Another one runs your entire content pipeline. That's what AI agents can do right now, and they are getting better every single week. So, in today's video, I'm going to show you how to build your very first one from scratch.

[00:25] There's no code involved, no complicated setup, and also, I'm going to teach you the one pattern that every good agent is built on. So, you can take it and you can build an agent for whatever you do.

[00:38] And by the end of this, you will have a real agent connected to your actual tools, running on a schedule, handing you finished work while you are so fast asleep. We are going to be building everything on HyperAgent.

[00:52] It's built by the same team behind Airtable, but it is its own separate product. The tool just launched and the agents that we are building today are genuinely insane.

[01:04] Guide yourself. The first 500 people to sign up get $500 in free credits. The link is down in the description below and so is our free school community where we keep all of the prompts, all the workflows, all the guides and everything you need to

[01:18] level up your game. But right now, let's get into the topic and first, let's understand the difference between a chatbot and an agent. Okay, so most people think that an agent is just a smart chatbot.

[01:33] So, they type in a prompt and then they wait for an answer, they copy it somewhere and then they do the actual work themselves. Now, that's not necessarily an agent.

[01:45] A chatbot answers when you speak to it. A real agent has a job, a schedule and also access to your tools. And it does that job whether you are watching it or not. One waits for you, the other one works for you.

[01:59] So now it's time to discuss the pattern. Before we build anything, I just want to discuss this. So let me give you the one idea that this whole video is built on. Because once it clicks, you can build an agent for literally anything.

[02:14] So here's the pattern. You don't start by building an agent. You start with a problem. You can solve that problem once yourself and in a normal conversation.

[02:26] And then only once you've got an output you actually like. Then you turn that solution into an agent that does it on repeat forever. You solve it once, then you make it permanent.

[02:38] And that's the whole thing. So now let me show you exactly what all of that looks like. So now, we are going to be going over to the PC, and first things first, your agent needs something to work with. So, for step number one, that is connect your tools.

[02:52] So, this is where most people just skip ahead, but then they end up looking back and regretting it. And I'm telling you now, don't. Focus on this. Your agent is only as powerful as what it can reach.

[03:04] So, when you sign up and you land on HyperAgent, then head to integrations, you've got native ones like Gmail, Slack and Google Calendar. Now these plug directly into your real stack You see because the more you connect here the more your agent can actually do So take two minutes and connect the tools that you use every day And now let actually solve

[03:27] the real problem, okay? Here's the problem that I want solved. Every week, people are shipping new AI automation workflows. Clever little balls that save hours of time. And the thing is about

[03:40] they are scattered across x-rated, YouTube, newsletters. And you see, the thing is, I want the best ones pulled together for me so that I always know what's worth looking at,

[03:52] what's worth focusing on for my own setup. So, right now, I basically waste an hour digging for that. So, how about we just let or make the agent do it?

[04:04] I'm going to click on Newslet, and this is just a conversation. Now, it's not actually building an agent yet. I'm solving the problem first. So, the quick thing before I send anything. Do you see this toggle over here in the chat box?

[04:19] So, that's plan and execute. Now, execute means it acts right away. Plan means that it shows you exactly what it's going to do before it spends a single credit. Now, if you are starting out, always run plan mode. That's what lets it come back and

[04:35] and check with you before it runs off. Now, what I'm going to do is, I'm just going to describe what I want, and I'm going to make sure that I'm doing it in as simple English as possible. Every week, find the best new AI automation workflows.

[04:51] People are actually building. Pull what makes each one useful, link the source, and put it together as a clean, shareable web page. I can skim in two minutes. Okay, now take a look at what it does.

[05:03] It doesn't just start blindly. It builds a plan. It asks me the couple of things that it genuinely can't guess, and then it starts getting to work. And it's right in front of us.

[05:15] It's searching the web. It's reading real sources. It's pulling the signal out of the noise. And then it builds the output. And here's the payoff. It didn't just hand me a wall of text.

[05:27] It built an actual web page, organized, sourced, clean, and the link is live. So, I can simply open it, I can share it, I can send it to anyone, and they don't even need a hyper-agent account to read it.

[05:41] That's the problem, and now the problem is solved. One conversation, and it's done. Now, I don't want to do this every single week by hand because it's going to take so much time, so let's just take this moment to make it permanent.

[05:57] This is the moment that the whole pattern comes together. I'm going to scroll down to the bottom of the thread and the hyper agent has already suggested turning this into a recurring agent. So I'm going to click on it and then it takes everything that just worked, the research steps, the sources, the page format and packages it into a saved agent.

[06:17] It writes the system prompt for me based on what we just did. Then all I'm going to do is I'm going to give it a name. Let's call it Radar. Okay, and then I set the schedule every Monday at 7am.

[06:31] And then it going to run this exact job on its own and then it going to drop the finished page in my Slack And you see that the simple pattern I solved the problem once and I did so by hand and now it an employee that solves it every single week

[06:47] without even needing me. I don't even need to open that page again. The work just shows up. But here's the thing. Right now, it will do the job, but it might do it a little differently each time.

[07:01] So, let's make it consistent. Now, this is another step that unfortunately a lot of people would skip, and it's the one that separates an okay agent from a great one, and it's called skills.

[07:14] A skill is a saved, repeatable procedure that you give your agent. So, instead of figuring out how to do a task from scratch every run, it actually just follows the exact same proven steps every time.

[07:28] So, I'm going to build one, and I'll create a skill for how I want a workflow visited. So, basically, like, what makes one actually work, including which sources to trust, how to write up each one.

[07:43] I just write it once, then I save it to the agent, and now every single run follows that exact playbook. And here's the difference that that makes. Without the skill, the agent just improvises. It will be slightly different every run, but with it, it's now locked in.

[07:59] It's the same standard over and over. The same structure is always going to be there. It's the same quality every single time. And I did the thinking just once, and now it's based in permanency.

[08:11] And it's not just the skills I built. After this run, look, the agent surfaced all of this on its own. It's saved a memory about how I like the page laid out, and it's flagging a spot in its own output that it thinks it can do better next time.

[08:27] All I need to do is just approve it with a click. So, the skill is the part that I control to keep everything consistent, and on top of that, it's quietly getting even sharper on its own.

[08:39] It's spotting its own weaknesses every single week. So now, I've got radar, and it's finding the best automation workflows every Monday, building a page, following my exact playbook that we created,

[08:52] getting better over time, that's a real agent. Now, let me show you where this gets even more powerful. One agent is useful, but the real shift happens with the second one.

[09:05] Because now they can hand the work off to each other. Radar delivers a page of the best automation workflows every month, but I don't just want to read it.

[09:17] I want it turned into my weekly newsletter. So what I'm going to do is I'm going to bolt a second agent that takes over right where Radar stops. I bolt it the exact same way, but here's the key move.

[09:30] When I set up how it's taken, I don't put it on as a schedule. I set it to watch my Slack channel. So the moment Radar posts the Monday research, the second agent now wakes up on its own.

[09:43] It reads it, and then it gets to work. And I mean, just take a look. Radar posts, and without me touching anything. The second agent picks it up and it drops a full newsletter issue a subject line in intel and each workflow written up in my voice with the why it matters and also the link And it just there it perfect it ready to send and all of it is in my voice because

[10:10] the memories and the skills carry across the whole workspace. I never copied anything between them, Radar did the research, the second agent turned it into the news data and it did so automatically.

[10:22] not two tools sitting next to each other that's a team that hands work down the pipeline and you can simply just keep stacking this one agent feeds the next and then by the end of it you would have bought an entire pipeline that runs

[10:38] itself so now I've got a couple of agents running at once and the obvious question is how do I actually keep track of all of this for this we have the command center. Just think of it as the manager's view of the entire team. Two agents, here's what

[10:56] they cost me this week, and here's how each one scored. Okay, so let me break that down. Every single run shows up here with its exact cost. So, I'm never guessing what the spend is

[11:09] going to be. A few cents for a quick one, a couple of dollars for the heavy research jobs, it's all done right here in real time. And the most important thing is, I'm not going to get anything that's going to surprise me on the bowl later on.

[11:24] And then this column over here, that's called the quality score. So do you remember how the agent grades its own work against the rubric? This is where that basically shows up.

[11:36] Every agent gets a score, and I can watch it climb week over week as they begin to learn. So, I can see at a glance which agent is passionate and also which one needs just a little more training.

[11:50] Now, that's basically the whole thing in one scheme. Who's running, what it's costing me, and how good the work actually is. That's the difference between a pile of automations and an actual team that you are managing.

[12:04] So, let's bring it back to that one pattern because now you've seen it work end to end. You find the problem. You solve it once. And you make sure that you're doing it yourself in a thread.

[12:17] And then you turn that solution into an agent. And you build a skill so it does it right every single time. And that's it. That's how you build any agent for anything. And once you've got one of them running, you never start from zero again.

[12:33] The skills, the memories, the integrations, it all carries forward. Every agent after your first one starts ahead. So, you are not folding, you are simply just stacking it.

[12:45] So, what I want you to do is, I want you to go and give it a try. The first 500 people to sign up gets $500 in free credit. Make sure to go over right now and claim yours at the link in the description below before it's all gone.

[12:58] And also, the prompts, the templates and the skill files that I used today are all inside our free school community. The link is down in the description below as well. And also, if this video helped you, then give this video a like and also subscribe to the channel

[13:10] so that you never miss another upload. And as always, it's been a whole lot of fun. Thank you for making it all the way until the end, and I will catch you on the next one.