用 Claude Code 搭建 AI 员工：九个模块与仓库结构

I think there's a lot of people using claude code wrong. And they're using claude code wrong because it is one of the most powerful pieces of technology that have ever existed. And there's a way to use cloud code that spin up actual AI employees. But the thing is, you have to set it up in a certain way. And today, I'm going to show you what that certain way is. I'm going to show you the nine different areas that you need to master in order to spin up these AI employees.

And this episode might feel a little boring at times because I'm going through a setup. I'm teaching you how to actually do it. But I think that the people that actually stick to the end, the people that actually get their hands dirty, that copy what I do, and I'm going to give away all the prompts and all the sauce in this episode, are going to be able to outperform people, are going to be able to build products that work 24/7, are going to build AI native companies.

AI native companies that just are able to crush. And I'm so excited to put this together for a free course for how to master cloud code like no one ever before with AI agents that run 24/7 that act like AI employees. Enjoy the episode. Shout out to Anthropic for supporting the channel and sponsoring today's episode. The way I think about an AI employee and setting it up is actually pretty simple. If you want to if you want cloud code to act more like an employee, you need to give it the same basic things you would give a person joining your company.

It only makes sense, right? First, it needs a workspace. In this case, the workspace is called a repo. And that's where the product actually lives. That's where the files live. And that's where Claude can actually go and do the work. Second thing it needs is memory. Memory is basically the context that you put into the project. So Claude understands what you're building, who the customer is, what matters right now, what good work looks like, and we'll get into that later, and what you've already learned so it doesn't repeat mistakes.

Then it needs a brief before Claude is like changing things all around. you wanted to understand the assignment. So that's where this thing called plan mode is super super useful. You're basically saying, "Look around, read the context, think through the job, and tell me how you'd approach it before you touch anything." And for something like that, you might want to use like a fable over an opus. We'll talk more about that.

Then it needs a clear ticket, basically an assignment. You know, a real employee does better with an assignment. Why wouldn't an AI employee? Claude is the exact same. The mistake a lot of people make is they'll say, "Make the app better. Make this pop." These very vague prompts uh that are assigned to it. The better way to do it is to be extremely specific. So, if you're, you know, want if you're creating a landing page and you want to create a weight list form, you'd say add a weightless form to the landing page with a success state and check it in desktop preview.

That's going to work just a lot better. The next thing it needs is eyes, you know, and you can finally do this in cloud code, and it's so so exciting. So, uh, you can do it in the desktop app, which is what I I primarily use. You can just say, "Claude, open the app, look at the page, click through the flow, inspect what is confusing, and tell me like what a customer would actually experience by going through this." That's obviously very very different level of usefulness than only editing files.

Then it needs review. So review is just going to look at the before and after changes. So Claude can help review the work too, but you want a system where changes get actually checked against your standards before anything important ships. Um then it needs a schedule. Um, so this is when a lot of people start having that aha moment where it's an actual 247 employee. You can basically give Claude recurring work like a morning brief, weekly issue review, poll request reviews.

Um, Claude calls this routines and we'll get into that uh in in this episode. And the last thing it needs is permissions. So a good employee knows what it can do on its own or when it should ask you for permission. Cloud is the exact same way. Um, so it could read files, it could inspect the repo, it could run tests, uh, it can work on small branches, but before touching things like dependencies, before touching migrations, before touching payments, a thing, these like bigger things, you basically want to make sure that the human owns those trust decisions.

And that's basically the map. So the map is basically workspace, memory, ticket, eyes, reviews, schedule, and permissions. And if you're able to do that, that's what I mean by an AI employee. It's basically this working system. Um, you give Claude a place to work, context to understand the business, you give it a clear way to plan, a way to execute, a way to check the product, a way to review things, a few recurring responsibilities that happen every single day. and then you give boundaries so it doesn't do something super risky.

And once you set it up this way, cloud code starts to feel less of like a one-off chat thing and really more of like an operating layer for your company. So let's talk about how you can actually set up the first step, which is creating a workspace. So in cloud desktop, you're going to want to hit the cloud code section. Um I prefer using it in the desktop app. It's a lot less overwhelming than in the terminal. So, we're going to use use that today.

Um, you're going to want to go and select your project folder um where Claude actually goes and runs. And just for the sake of this demo, we're going to talk about an idea that I found on ideabrows.com, which is basically a mislead responder for med spa med spas. So, basically, someone fills out a form, DMs the business, calls after hours, uh, ask about pricing, but the business responds too late. There's an opportunity to create a cash flowing uh, software business there.

So, we're going to talk about how we'd actually set up this repo, what the structure would be, and what what I would want to do if I'm set if I'm creating an app, if I'm creating a software, I want basically slash app/context/c customers/spec/demo/ routines. I'm going to want 3MD files. And I'm going to talk about what all that means. So slash app is the product slashcontext is the business brain slashc customers is where the sales calls the support notes any objections customer language you put that there uh slashdemos is where you're going to want to put the demo flows loom scripts screenshots things like that routines is where you're going to want to put those recurring prompts like we talked about these like recurring tasks that are going to happen that'll be in the routines and then the the three root file files that you're going to want to have uh the that are MD files that are basically like this operating manual for you are going to be claw.md which tells you how claude to work.

It you're going to want a roadmap.md file that's going to tell claude what matters right now and you're going to want a review.md file which is going to tell Claude how to judge the work before it chips. So the mo the the first the the takeaway I want you to have is claude gets just way more useful when the project explains itself. So how do you actually go and set this thing things up? What are what are what's like the the best way to do it?

This this is what you should do. So here's the prompt. Help me set up this repo as an AI employee workspace. And then you just say create or update claw.md roadmap review/context/c customer/spec/demo routines. And then you say use this business context. So you can say product miss lead responsive for med spa. So you're just basically saying what it is. The buyer you want to explain who the buyer is. So in this case it's a med spa owner and operator.

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