The Content Creator Agent: Your AI Writing Team for £0
Content is one of the best uses of AI I've found. Not because AI writes brilliantly on its own — it often doesn't — but because content creation maps perfectly onto the agent team model. Research. Outline. Draft. Edit. Adapt. Each of those is a distinct job, and each benefits from focused attention rather than one overcrowded prompt.
What I'm going to show you is how to build a personal content creation system using AI agents. No tools to buy. No subscriptions beyond what you already have. Just a set of focused prompts that work together as a team.
The problem with one-shot content
Most people use AI for content like this: "Write me a blog post about X." The result is usually fine. Maybe 70% of the way there. Structurally okay, missing any distinctive voice, occasionally factually thin, probably a bit generic.
The issue is that you've asked one agent to do everything at once. The AI is simultaneously figuring out what to say, how to say it, what order to say it in, what tone to use, and what facts to include. That's too many constraints in conflict with each other.
When you break it apart, you can go much deeper at each stage. And the final output genuinely reflects your thinking, not just a statistical average of everyone else's writing on the topic.
"The goal isn't AI that writes for you. It's AI that handles the mechanical parts so you can focus on the thinking."
The five agents in your content team
Here's the team I've built up over time. Each agent has a specific role, a focused prompt, and a defined output format. You don't need all five for every piece — but knowing what each does helps you pick the right ones.
🔎 Agent 1: The Researcher
Finds what's actually worth saying about your topic. Not just "what is X" — but what's interesting, recent, surprising, or counterintuitive about X. Output: bullet points only, no prose.
📄 Agent 2: The Outliner
Takes the research and builds a structure. Not the content — just the skeleton. Decides what goes in, what order, and why. Output: numbered sections with one-line descriptions.
✍️ Agent 3: The Writer
Writes the piece from the outline. Has a specific voice brief, knows the format, and doesn't go off-brief. This is where your style guidelines live.
🔎 Agent 4: The Reviewer
Checks the draft against specific criteria. Produces structured feedback, not rewrites. Output: pass/fail per criterion, with notes.
📱 Agent 5: The Social Adapter
Takes the finished piece and creates platform-specific versions. Different length, different format, same core message. One prompt to produce all your distribution content.
How to run the team in practice
You don't need special software. You need a chat interface (Claude, ChatGPT, Gemini — whatever you use) and somewhere to store the prompts so you're not retyping them.
Full content pipeline — one piece of content
The whole thing takes about 20-30 minutes for a 1,000-word piece, including your review time. Compare that to writing from scratch, which for most people is 2-3 hours.
Where to store the prompts
The simplest approach: a document or notes file with all five prompts saved as templates. When you start a new piece, you copy the right prompt, fill in the brackets, and paste it in.
If you're on Claude, you can use Projects to store your prompts and keep context across conversations. Each agent gets its own project, or you can keep them in one project and switch between them.
If you write a lot of content, it's worth spending an hour customising the voice brief in Agent 3 to match exactly how you want to sound. That's the prompt that has the most leverage — everything flows from the Writer's output.
Making it more automatic
Once you're comfortable with the manual version, you can start connecting agents more directly.
Claude Code lets you run all five agents in sequence with outputs passing automatically between them. You describe the piece you want, the team runs, and you come back to a draft and social content ready for review. I've used this for this blog — articles I wrote at night while asleep.
💡 The overnight run
One practical use: queue up three or four pieces before you go to bed. The agent team runs overnight. In the morning you have drafts to review. The revision step — adding your examples, adjusting the voice, catching anything that feels off — takes 10-15 minutes per piece.
You go from "I need to write more content" to "I have content, I just need to make it mine." That's a different problem. A much easier one.
What the AI can't do
This system is genuinely useful, but it has real limits. Here's what you have to provide yourself:
- Original insights. The Researcher can find facts. It can't have your experience, your perspective, or your original take on something. That has to come from you — either in the brief or in the revision step.
- Real-world examples from your life. Generic examples from AI are noticeably weaker than specific examples from experience. The best use of the system is to let AI handle the structure and facts, then swap in your own examples.
- Fact verification. Especially for recent events. The Reviewer prompt asks the agent to flag uncertain claims, but you should still check anything where being wrong would matter.
- Your voice. The Writer prompt helps, but it still needs editing to sound like you. The more specific your voice brief, the less editing you need — but some editing is always required.
⚠️ The authenticity problem
Content that feels obviously AI-generated is less trusted, less read, and less shared. The whole point of this system is to make content that sounds like you — using AI to handle the mechanical work, not replace the thinking.
If you skip the revision step and publish raw AI output, you'll get content that's technically fine and distinctly forgettable. The system only works if you show up for the final 20%.
Scaling to a content series
The real value shows up when you're producing a series — not just one piece, but ten, twenty, fifty on related topics. At that point:
- The Researcher builds up a shared knowledge base that subsequent posts draw on
- The Writer gets better at your voice because you've refined the prompt over multiple iterations
- The Social Adapter produces content for every platform from every piece, not just the big ones
- You develop a library of content that covers your territory comprehensively
The Stackless blog runs on exactly this model. Each post in the non-expert series (privacy, security, agents, this one) went through the same team. The voice brief evolved slightly each time based on what worked. The series ended up consistent because the process was consistent.
Your first piece
Take a topic you know something about — or want to know more about. Fill in the brackets in the Researcher prompt. Run it. See what comes back.
Don't aim for perfection on the first run. Aim for something you can edit into shape in under 30 minutes. That's the bar. Once you've done it once, you'll know where the prompts need adjusting for your use case.
The team's there. You just need to give it a brief.