Intro · 3:22
Agents versus chat
Cutting through confusing terms: what agents are compared to chat.
- AI terms are confusing: skills, MCPs, harnesses.
- Chat answers; agents act.
- Anyone can set up their own agents.
| Chat | Agent |
|---|---|
| Answers | Acts |
| You drive | It works |
| No tools | Tools |
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What's the key difference?
Chat answers; agents act.
Who can set up agents?
Anyone.
0:00 I think there's a lot of terms, skills, MCPs, agent harnesses that are difficult concepts to understand. So I had my friend Remy come on the podcast and explain it in the most simple terms possible. In this free course on how to master AI agents, he breaks down exactly which each piece is. How they connect together and the simplest ways beginners could start using them today. Enjoy the episode. I beg them to come on. Remy Gaskill's on the pod.
0:30 You've structured your company where you basically have these folders and .md files that run your company. And what I want to do today is I want you to teach people in a beginner friendly fashion. This is only for beginners, how they could do the same thing. How they can set up their own executive assistant, head of marketing, chief financial officer. Basically, I want you to base to tell us the concepts behind all this. By the end of this episode, Remy, do you think you can do that?
1:00 100% Greg. We're going to go through all the concepts that make up an AI agent. And by the end of this video, you will know exactly how you can build up agents to run complete departments of your life and your company. within any agent platform you choose, whether it's Claude, Claude, Kodex, open call, mana, all of them. All right, let's do it. Sweet. So, one of the reasons why I really wanted to make this episode is because I feel like the AI landscape is moving into like stage two.
1:40 From chat to agents. And most people are getting left behind right now, just using the chat models. And the founders and employees that are utilizing agents are like no word of a lie, 10 to 20 times more productive in a day. And when you stack that up over days, weeks, years, you're going to just be miles ahead of the competition. So I really want to make this episode today to help bring everyone up to where the AI landscape is at the moment.
2:00 and to start using agents to manage every department of your business. So the key things to understand here is chat models versus agents. Because the word agent is thrown around lots online. I'm sure you've seen it Greg, like AI agents this, agents this, use this agent for this, and it's kind of lost a lot of meaning. So I wanted to give start by giving a really clear definition of what an agent actually is. So the way I think of it is a chat model is question to answer.
2:30 But then an agent is goal to result. So moving from just like, you asking, AI replies, then you do the work, to you giving the agent a task. It planning out the task and then executing and then delivering you a result. Does that make sense? Crystal clear. I mean, the way I think about it is chat is kind of like ping pong. Back and forth, back and forth. Yep. And agent is, uh, you know, you're giving it, it's a goal.
2:50 I mean, the best way is, yeah, you're giving it a goal and you're hoping that over time, it gets better and closer to that goal. Exactly. Yeah, that's exactly it. And I just think that's a nice way to lay it out in your head is chat is question to answer, agent is goal to result. So when you chat to an agent, you might give it a task like build me a website for XYZ. And then it goes away, it does its work, and it outputs this wonderful website to you.
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