Online course: Create & repurpose platform-native social content
Build a Claude Code content automation system your team can run every week
Build a Claude Code repo for content analysis, ideation, repurposing, reporting, and performance tracking.
- Analyze the performance of your top social media content to identify what’s driving engagement and results.
- Use sources like Google, Reddit, and competitor content to identify trending topics and new content opportunities.
- Create a reusable AI writing system with tone of voice guidelines, brand rules, and writing references so agents can write more like your team.
- Repurpose one piece of content into multiple formats and channels using platform-specific best practices.
- Set up automated weekly or monthly reports for stakeholders summarizing content performance, trends, and key insights.
Leave with practical workflows. No prior automation experience needed.
Trusted by marketers at
Your content workflow can be automated end-to-end
Content research, analysis, reporting, and repurposing all follow repeatable workflows.
When these workflows stay manual, teams lose time on repetitive tasks instead of strategy and creative work.
With Claude Code, teams can automate large parts of the content pipeline, move faster, and build more scalable content systems.
Course overview | Watch it on your schedule
Lesson 01: Build custom marketing agents for specific content tasks
Learn how to design content marketing workflows as AI agent systems. Map out the agents, skills, workflows, and references needed to make the system work.
- Distinguish between agents and skills
- Define inputs, tools, and outputs for each workflow component
- Design your first campaign agent system on paper
- Understand the dependencies before connecting real data and content systems
Lesson 02: Connect AI to live data sources
Use tools like Apify to connect your agents to data from platforms like LinkedIn, YouTube, Instagram, Reddit, and Google so they can analyze live content, trends, and performance data.
- Identify the data sources your agents need to make informed decisions
- Use MCP and connectors to plug agents into your team’s existing tools
- Set up Apify integrations for live performance visibility
- Build agent logic that turns raw data into actionable priorities
Lesson 03: AI-powered topic research and competitor analysis
Use AI agents to identify the biggest questions, pain points, and trends your audience is searching for, then turn those insights into content ideas designed to answer them.
- Analyze Google SERP pages and identify the questions people are searching for most.
- Go through relevant Reddit discussions to uncover audience pain points, trends, and recurring conversations.
- Analyze competitor social content to identify which topics and formats are driving the most engagement.
- Generate a prioritized list of content ideas based on search demand, audience discussions, and competitor performance.
Lesson 04: Build a content repurposing system
Repurpose your top-performing content into multiple formats, including carousels, video scripts, newsletters, social posts, and blogs.
- Create tone of voice and brand reference files so AI agents can write more consistently like your brand.
- Build platform-specific skills and workflows so content is properly adapted for channels like LinkedIn, newsletters, blogs, and video scripts.
- Create QA workflows to review accuracy, messaging, structure, and overall copy quality before publishing.
Lesson 05: Summarize analytics and create weekly reports
Much time is wasted on manual reporting. Build agents that pull your performance data, spot trends and gaps, and deliver formatted weekly summaries so your team always knows what’s working and what needs attention.
- Design a reporting agent that pulls data from your own social media platforms,
- Turn raw analytics into insights that highlight trends and opportunities
- Format reports automatically so stakeholders get consistent, actionable summaries
- Schedule weekly runs so reporting becomes hands-off
Meet your instructor
Content Lead at CXL, focused on practical applications of AI in marketing. Trained 2000+ marketers from Unilever, Red Bull, Heineken and more.
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