🧩 Docs-as-Data
Discover how software docs become a strategic data source for AI through a Docs-as-Data approach linking writing, structure, and AI strategy.
🧩 🆕 Agentic AI: 1. Strategy
Agentic AI strategy for documentation and knowledge bases starts with needs and use cases to define services and expected benefits.
🧩 🆕 Agentic AI: 2. Architecture
Tailor documentation agents through knowledge surfaces, prompt architecture, metadata, rules, skills, tools, and orchestration.
🧩 🆕 Agentic AI: 3. Testing
Prepare documentation agents for real use through output design, test prompts, evaluation datasets, feedback loops, and lifecycle management.
🧩 🆕 AI-Ready Knowledge
Making heterogeneous knowledge AI-ready through dimensions of trust, qualification signals, metadata, and source of truth.
🧩 🆕 When AI Becomes a Documentation Consumer
Explore how to design human- and AI-oriented representations using metadata, existing knowledge and AI-specific data without duplicating content.
🧩 From SEO to GEO
Ensure your documentation is read, understood, and cited by generative AI with SEO and GEO best practices.
🧩 Using AI for Software Documentation
See how AI empowers technical writers with clearer API docs, terminology, localization, and quality checks —through use cases and best practices.