AI-Powered Content Strategy and Portfolio Development
A guided, multi-course journey that builds this skill from the ground up. Work through the chapters in order, or jump to any lesson.
Progress0%
Content Strategy as a Decision System and the Portfolio Artifacts You Will BuildBusiness Goal Translation Into a KPI Tree SkeletonICP Snapshot With Assumptions, Triggers, Objections, and Moments That MatterPositioning Against Real Alternatives and the Proof Required to Believe ItMessaging Framework Draft: Narrative, Pillars, Reasons-to-Believe, and Objection HandlingSpecificity Tests That Turn Generic Messaging Into Testable Claims
Research Ingestion to Claim Log: From Notes to Verifiable StatementsICP Draft-and-Validate Loop Using Assumptions and EvidenceMessaging Variants by Segment or Stage With Rubric-Based EvaluationA Standard Content Brief That Produces Decision-Grade DraftsSERP-Informed Outlining Inputs as an Intent and Quality MethodRepurposing One Source Asset Into a Consistent Multi-Format Set
Lightweight Editorial Workflow With Stage Gates and Definitions of DoneBrand Voice Guide: Rules, Lexicon, Taboo List, and Annotated ExamplesContent QA Checklist: Verification, Links, Claim Labels, and Review PointsCapacity-Based 4–8 Week Calendar With Owners, Dependencies, and Distribution NotesRepurposing and Distribution Cadence Tied to Next-Step CTAsPerformance and Qualitative Feedback Loops Into Briefs and Messaging Updates
Finalize the KPI Tree: Primary vs. Leading Indicators and Decision UseA Measurement Plan: Definitions, Data Sources, Cadence, and OwnershipDashboard Outline: Views, Interpretation, and Action TriggersExperimentation for Content: Hypotheses, Primary Metrics, and Learning LogsGovernance for AI-Assisted Content: Privacy, Data Handling, and Approved UsesIP Risk Awareness, Disclosure Norms, Bias Checks, and the Final Portfolio Assembly