them. I've set up a few different agents for this demo. Hookw writer, script writer, and a couple others. Let's start with one so you can see how it works. So here's my prompt. Write me hooks using the research we already did. Remember that cowwork_ressearch. md file? I'm referencing it with the 8 symbol. Then I'm telling Claude to use the hook agent specifically and save everything in a new file called hooks. md. Hit enter and watch what happens. It's not just following my instructions blindly. It's actually thinking about which agent to use. See how it first reads the research file. Now look, I just said hook agent, but Claude code figured out I meant the viral hookw writer agent we created. It's smart enough to connect the dots. Now, while it's working, let me explain something important. You get 200,000 tokens per session. Once you hit that limit, Claude automatically compacts everything, summarizes what you've done, and saves it. So, you never really lose context. It just gets compressed and done. It created hooks. md with seven viral hooks. Notice I never said how many hooks I wanted. The agent just knew that giving options is better. That's the power of a well-built agent. Let's check the file. There it is. Hooks. md. Opening it up. And look at this. Hook one, hook two, all the way to seven. Different types of hooks, why it works, and what type of content it's best for. So, the agent didn't just write hooks. It explained the strategy behind each one all from one simple prompt. So, we've used one agent. Now, let me show you where it gets really powerful. Using multiple agents all working together. Here's what I'm doing. The research is done. The hooks are ready. Now, I want a full script. So, I'm telling Claude to use all the files we created, the research file and the hooks file. But here's the thing. I'm not using just one agent. I'm chaining three agents together. First, the storytelling agent creates the narrative structure. Then, that output goes to my YouTube analyst agent. This one knows my tone of voice, the words I use, everything about my style. And finally, all of that goes to the script writer agent for the final output. Now, watch what Claw does. It's not running all three at once. It's smart enough to go one after the other. Takes the output from the first agent, feeds it to the second, then to the third, just like an assembly line. Quick tip. If you want things to run parallel, you can do that, too. Like sending three research agents to search Instagram, LinkedIn, and Reddit all at the same time. Saves a ton of time. Now, here's something important about tokens. The agent used 15,000 tokens, but my main chat only used 4,000. Each agent gets its own fresh 200,000 tokens. So, if I had done all this research and writing in my main chat, I would have burned through my entire limit. But with agents, everything stays efficient. The YouTube analyst is done. Now it's passing everything to the script writer. The one we built earlier. Let it do its thing and done. It's asking permission to save the script. I'll allow. Now let's see what we got. Look at this complete YouTube script on Claude co-work. Video title, core transformation for viewers, everything. And remember the agents worked with each other automatically. I didn't have to copy paste anything between them. We've got the hook, act one, act two, the demo section, retention hooks throughout, plus all the visual notes for my editor that I asked for, a complete expert level script, and look, it even added an emotional arc showing how the viewer should feel throughout the video. On top of that, title and thumbnail options. The agent went above and beyond. You get all this output without burning through your main context. That's your AI content army. research hooks, full scripts, all done automatically while you just sit back and watch. So, we finally did it. From being scared of that word code and thinking Claude code is only meant for developers to building