The AI Agent Economy Explained (How to Make Money From It)
TThe Coding Koala
Small Business/StartupsComputing/SoftwareInternet Technology
Transcript
00:00:00By the year 2030, the AI agent market is expected to hit around $50 billion,
00:00:05which is honestly a stupid number for any industry to be growing at.
00:00:09And if you're one of those people who's missed out on a bunch of other money-making
00:00:12opportunities on the internet, you really don't want to miss this one.
00:00:15So in this video, we're going to break down what the agent economy actually is,
00:00:20how people are already making money from it, and how you can go build your own agent.
00:00:24And here is the best part, you don't need to know how to code to do this.
00:00:27Okay, so if you already know what an AI agent is, you can skip ahead to the next section.
00:00:32But for beginners, here's a simple explanation.
00:00:35So you already know what AI means, like ChatGPT or whatever you've already been using.
00:00:40So a regular AI tool is basically reactive.
00:00:43You ask it something, and it answers.
00:00:45And then it just sits there waiting for you to ask the next thing.
00:00:48An agent is different.
00:00:50It's like giving a body to your AI brain.
00:00:52You tell it what to do, and it actually goes and does the work itself,
00:00:56independently without you doing anything.
00:00:58Some great examples of this are coding agents, which can code independently once you tell them
00:01:03what to do, or customer service agents, which can actually do stuff like a real employee.
00:01:08I hope that was clear enough, but if you're still confused, you can just ask Claude.
00:01:12Anyway, let's move on to the interesting part.
00:01:14So how are people actually making money from this?
00:01:16Well, there are a bunch of different ways, but I'm going to save you the time and just
00:01:20tell you which ones are actually worth paying attention to.
00:01:22The first method is productized agent services, the one with the real long-term money.
00:01:27Here's what that means.
00:01:28In the simplest way possible, you build one solid agent that solves one specific problem,
00:01:33and then you just sell that exact same thing to a bunch of similar businesses.
00:01:37So say you build an agent that automatically replies to Google reviews for a business.
00:01:42You don't need to reinvent that for every client.
00:01:45You sell that one agent to 50 different businesses, and you charge each one a couple hundred bucks a month.
00:01:50That's the part where this stops being a one-off gig and starts being an actual business.
00:01:56Then there's consulting.
00:01:57Instead of building one agent and selling it to multiple customers, you walk into a business,
00:02:02figure out what their problem is or what repetitive task is eating up their time,
00:02:07and build them a custom agent just for them.
00:02:09It's more work per client than the productized route, but it pays really well,
00:02:13and barely anyone's doing it properly yet, which is exactly why it's worth mentioning.
00:02:17These are two common methods, but another important thing you need to understand is how AI agents are priced.
00:02:23A lot of businesses are moving away from flat subscription pricing and charging based on results instead.
00:02:29So instead of just charging $200 a month no matter what, you get paid per result the agent brings in.
00:02:35Which, if you think about it, is a way smarter way to sell something,
00:02:38because it's a lot easier to convince someone to pay you for results.
00:02:42Okay, so at this point you're probably thinking,
00:02:44"This sounds great, but how do I actually build one of these things and start making money for GTA 6?"
00:02:50So there are basically three paths depending on how technical you are.
00:02:53If you don't want to touch any code at all, there are no code agent builders.
00:02:57Tools like Linde or N8N, where you basically just describe what you want in plain English,
00:03:02drag a few blocks around, connect it to the apps you already use, and it spits out a working agent.
00:03:07Perfect if you're just starting out and don't know how to code.
00:03:10You can easily find tutorials for these tools on YouTube,
00:03:13so you don't have to worry about how you'll learn them.
00:03:15There's a second path too.
00:03:17If you're a little more comfortable with tech, there are frameworks like Langchain or Crew AI,
00:03:21where instead of dragging blocks around, you're writing some code to define exactly
00:03:25what steps your agent should take and even how multiple agents can work together on the same task.
00:03:30It's more controlled than the no-code route, but still nowhere near as intense as building everything
00:03:35from scratch.
00:03:35And if you're actually a hardcore developer, you can go build agents completely from scratch using
00:03:41something like the Clawed Agent SDK or OpenAI's Agent SDK, full freedom over how your agent behaves,
00:03:48what it remembers, and what it's allowed to touch with zero limits and zero training wheels.
00:03:53You can pick any of these depending on your skill set. Just know that the higher you move up this pyramid,
00:03:58the more control you get over your agent.
00:04:00But there's one issue I faced when building my own agent, which you'll probably face it too.
00:04:04I had to manage 10 different API keys for one single agent.
00:04:08See, an agent on its own is just a brain. It can think and plan all it wants, but it can't actually
00:04:14perform actions without using an API. Think of an API as a door your agent can walk through to get into
00:04:20another app or service. If you want your agent to search the internet, you need one API. If you wanted
00:04:25to send an email, that's another separate API. If you wanted to make a payment, that's another one.
00:04:31And every single one of these usually means signing up separately on that provider's platform and
00:04:36grabbing a key. So the more useful you want your agent to be, the more keys you end up needing.
00:04:42And that's exactly the problem this video's sponsor, Monad, solves. It is a unified tool access and payment
00:04:48platform. So instead of going and signing up for 10 different providers separately, you give your agent
00:04:54one API key and it suddenly has access to over 2000 APIs and tools all through that single connection.
00:05:01And here's the part one actually think is the coolest. You don't even need to tell your agent
00:05:05exactly which tool to use. You just tell it what you're trying to do and it goes and discovers the
00:05:10right tool on its own, compares a bunch of options by fit and price and runs it instantly. No separate signup
00:05:17that I've needed. And instead of a monthly subscription for every single tool, it all comes out of one
00:05:22balance. And you're paying insanely small amounts per call, like fractions of a cent, only for what
00:05:28your agent actually uses. And remember those three ways we talked about earlier. Doesn't matter which
00:05:32one you picked, Monad just works for everything. Drop it in as a skill if you're on a no code builder,
00:05:38connect it through MCP if you're using something like Langchain or Crew AI, or hook it up straight
00:05:43from the terminal if you're coding your agent from scratch. Same tool access, same balance,
00:05:49no matter how you built your agent. I've dropped the link in the description and they're giving away
00:05:53free credit so you can try it yourself. And that's everything I need to tell in this video. You now know
00:05:58what an AI agent is, how people are making money from it and the different ways you can build one yourself.
00:06:04If you're into this kind of tech business content, make sure to subscribe and go check
00:06:08out Monit AI. I'll see you guys in the next one.
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