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Marketing Against the Grain

My 11-Skill AI Content Team (Built in Claude Code)

28 min episode · 2 min read

Episode

28 min

Read time

2 min

Topics

Startups, Leadership, Artificial Intelligence

AI-Generated Summary

Key Takeaways

  • Lookalike Content Scaling: Feed Claude Code a data dump of your top-performing posts — the system analyzes the top 30% by engagement, extracts structural and emotional patterns, then generates new content ideas mapped to those winning formulas. Without performance data, it analyzes the full dataset. Works with other creators' content if you lack your own archive.
  • Self-Improving Feedback Loop: Build a companion app that captures every piece of content the system produces, then manually input performance metrics monthly. Run a review skill that reads all performance data and automatically rewrites the underlying skill files — meaning the content system improves itself each month based on what actually performed well or poorly.
  • Audience Profile Over ICP: A content audience profile differs from a standard ICP. It maps vocabulary the audience uses versus avoids, emotional registers, validation hooks, and specific content formats they react to — all grounded in engagement data. One profile per platform per persona produces more targeted output than a single generic customer profile.
  • Orchestrator Skill Architecture: Build one master orchestrator skill that calls all other skills automatically. When activated, it loads the correct audience profile, writing style, and prior research, then executes tasks across the full system. This eliminates manual navigation between tools and enables a fully autonomous mode where content is generated overnight without human input.
  • Post Enrichment Layer: After generating a first draft, run a separate enrichment skill that appends platform-specific modules — data points, case studies, executive quotes, or narrative examples — sourced from external research. Each enriched post logs its enrichment source, word count, hook pattern type, and originating talking point file, creating a traceable content production record.

What It Covers

A marketer builds an 11-skill AI content system in Claude Code, structured across five layers: audience profiling, writing style generation, research and ideation, multi-platform drafting, and a self-improving feedback loop that updates all skills monthly based on real content performance data.

Key Questions Answered

  • Lookalike Content Scaling: Feed Claude Code a data dump of your top-performing posts — the system analyzes the top 30% by engagement, extracts structural and emotional patterns, then generates new content ideas mapped to those winning formulas. Without performance data, it analyzes the full dataset. Works with other creators' content if you lack your own archive.
  • Self-Improving Feedback Loop: Build a companion app that captures every piece of content the system produces, then manually input performance metrics monthly. Run a review skill that reads all performance data and automatically rewrites the underlying skill files — meaning the content system improves itself each month based on what actually performed well or poorly.
  • Audience Profile Over ICP: A content audience profile differs from a standard ICP. It maps vocabulary the audience uses versus avoids, emotional registers, validation hooks, and specific content formats they react to — all grounded in engagement data. One profile per platform per persona produces more targeted output than a single generic customer profile.
  • Orchestrator Skill Architecture: Build one master orchestrator skill that calls all other skills automatically. When activated, it loads the correct audience profile, writing style, and prior research, then executes tasks across the full system. This eliminates manual navigation between tools and enables a fully autonomous mode where content is generated overnight without human input.
  • Post Enrichment Layer: After generating a first draft, run a separate enrichment skill that appends platform-specific modules — data points, case studies, executive quotes, or narrative examples — sourced from external research. Each enriched post logs its enrichment source, word count, hook pattern type, and originating talking point file, creating a traceable content production record.

Notable Moment

The system includes a fully autonomous mode where Claude Code runs the entire content pipeline overnight — pulling research, generating drafts across LinkedIn, Substack, and X, and saving outputs — so the user arrives each morning to completed content without having initiated a single prompt.

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Episode Transcript

I gave Claude Code 51 of my Substack posts, and in five minutes, it told me exactly why some of my content works, why some of it doesn't, and then it generated an infinite number of new ideas that map to my winning formula. Now that's just one skill of a much bigger content system that I've been building over the last number of months. It's an entire AI content team built in cloud code. It's actually 11 skills across five different layers of content. It can research your audience, analyze what content works, draft posts for LinkedIn newsletter, YouTube transcripts, and then it can actually improve itself every single month. On this episode, I'm going to give you a look over my shoulder on how I use Cloud Code to create content, how I use my content team, and I'm going to give you one of the best skills for free. Let's get into that and more on this episode of Marketing Against the Grain. Here's a quick word from HubSpot. HubSpot helped Tumblr solve a big problem. They needed to move fast to produce trending content, but their marketing team was stuck waiting on engineers to code every single email campaign. Now they use HubSpot's customer platform to email real time trending content to millions of users in just seconds. The impact? Three times more engagement, double the content creation. Wanna move faster like Tumblr? Visit hubspot.com. So we are going to give a look over my shoulder as I use my AI content team to create content. Now it's going to be awesome. So what is this? This is really for people who wanna start to see the possibility of cloud code. And if you are a system thinker, a system thinker, how you can use cloud code to be your super weapon, how you can use cloud code to supercharge anything that you're doing in work if you can think about how to build systems with it and in it. And this system is all about content. So I'm gonna give you a quick visual of the system that I'm going to bring you through today. This is over on my Substack for people who want to check it out. And so this is the system we're gonna go through today. The little starred one here is what I'm gonna give you all for free. And so it has an orchestrator skill. So the orchestrator skill is going to actually use all the other skills, which makes it really easy to use the system. You can kinda just dive with the orchestrator skill and ask it to do things, and it goes and uses all of the other skills for you. It makes using these systems really, really easy. You can build a content audience profile, which basically you wanna figure out who you're creating the content for, build a profile, and make sure all of the content is tailored for that person. The system does …

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  • Claude CodeRecommended

    by Anthropic

    A marketer builds an 11-skill AI content system in Claude Code, structured across five layers: audience profiling, writing style generation, research and ideation, multi-platform drafting, and a self-improving feedback loop.

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