Writing Content for AI: Best Practices and Tips

As AI chatbots rapidly become a preferred channel for customer self-service, the role of technical documentation is evolving.

Writers are no longer creating content just for human readers, but also for AI systems that consume, interpret, and respond using your documentation.

In this webinar recording, Selvaraju Murugesan explores how technical writers can refactor content to be both human-friendly and AI-ready, using insights from Retrieval Augmented Generation (RAG) architecture, the technology behind modern chatbots.

Key takeaways

Understanding the Shift

• Why customers increasingly rely on chatbots over traditional search.
• The transition from SEO to Generative Engine Optimization (GEO).

Writing for Humans vs. Writing for AI

• Principles of concise, accessible writing for human readers.
• Techniques for AI-oriented writing, from metadata and consistent terminology to chunking strategies.

Building Solid Information Architecture

• How taxonomy, structure, and logical sequencing help both humans and AI find answers faster.
• The impact of good content architecture on chatbot response quality.

Inside RAG: How AI Chatbots Retrieve and Generate Answers

• Simplified breakdown of tokens, embeddings, and vector databases.
• Understanding how LLMs use your documentation to generate responses.

Refactoring for AI Readiness

• Best practices for chunking, glossary usage, pronoun clarity, and FAQ placement.
• Practical examples of refactored content and why they work better for AI retrieval.

Evaluation Before Go-Live

• How to test chatbot accuracy with real prompts and ground truth answers.
• Tools and metrics to measure content performance for AI systems.

About the Speaker

Selvaraaju Murugesan received the B.Eng. degree in Mechatronics Engineering (Gold medalist) from Anna University in 2004 and the M.Eng. degree from LaTrobe University, Australia, in 2008. He has received his Ph.D. degree in Computational mathematics, LaTrobe University. He is currently working as a Head of Data Science at SaaS startup Kovai.co. His interests are in the areas of Business Strategy, Data Analytics, Artificial Intelligence, and Technical Documentation.