Serving docs to AI agents: Learnings and best practices

Your documentation has a new kind of reader.

AI agents are fetching, parsing, and acting on your content, and they behave nothing like a human skimming an article.

When an AI agent meets your docs, do they find what they need, or do they trigger a hallucination?

In this webinar, Selvaraaju Murugesan, Senior Director – Data Science, will walk through exactly what happens behind the scenes when an AI agent interacts with your documentation.

You will learn how to structure, optimize, and track your content to ensure AI agents retrieve the right information and execute actions accurately.

What You’ll Learn

• The Discovery Phase: How AI agents find your documentation using signals like llms.txt and machine-readable doc indexes.
• The Technical Hurdles: How web fetch characteristics, including JS rendering, crawl limits, custom headers, and rate limits, dictate what an agent can actually read.
• The Consumption Process: How agents process and reuse your content to form answers and drive real-world actions.
• Optimization Frameworks: Best practices for content structuring, creating self-contained pages, maintaining stable URLs, and writing unambiguous headings.
• Closing the Loop: How to set up agent analytics to track who is visiting, what they fetch, where they fail, and how to feed those insights back into your content strategy.

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 Senior Director – Data Science at Kovai.co. His interests are in the areas of Business Strategy, Data Analytics, Artificial Intelligence, and Technical Documentation.