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Designing Information Systems for AI Agent Consumption

7 chapters · 32 lessons

1. 1. How Agents Read and Extract Information

   4 lessons

   Understand the technical pipeline agents use to fetch, parse, and extract meaning from web pages and documents.

2. 2. Structured Data and Semantic Markup Fundamentals

   5 lessons

   Apply schema vocabularies, JSON-LD, and metadata patterns to make facts explicit and extractable.

3. 3. Content Architecture for Agent Legibility

   5 lessons

   Design page structures, navigation, and content hierarchies that support both human and machine comprehension.

4. 4. Retrieval-Augmented Generation in Practice

   4 lessons

   Understand how RAG systems combine search, embeddings, and language models to ground agent responses.

5. 5. API and Data Interface Design for Agents

   5 lessons

   Build machine-first interfaces that expose product, inventory, policy, and transactional data in agent-friendly formats.

6. 6. Auditing and Optimizing for Agent Readability

   4 lessons

   Evaluate existing content and systems, identify friction points, and prioritize improvements for agent workflows.

7. 7. Real-World Applications Across Domains

   5 lessons

   Apply agent-first design principles to commerce, documentation, policy systems, and enterprise knowledge bases.