The author argues that modular “Skills”—reusable markdown workflows loaded on demand—outperform standalone AI agents by cutting token bloat and maintenance overhead. A live GEO audit system built with Skills shows how you can turn domain expertise into scalable, service-ready products without managing dozens of agents.

• Claude's "Skills" load modular markdown playbooks on demand instead of baking everything into prompts, citing 53 tokens for passive reference vs. embedding a full prompt every time
• A live GEO audit system built entirely on Skills scrapes visibility across ChatGPT/Gemini, flags gaps like missing Wikipedia entries, and auto-generates client-ready reports without spinning up separate agents
• The whole GEO pipeline is public and forkable, letting anyone productize it without building custom infrastructure
• Documenting expertise once in a markdown file and iterating on it lets teams ship service-ready AI products in days rather than maintaining fleets of bespoke agents