Learn Machine Experience

When an AI agent visits your website, it reads the HTML, not the pixels. If your content lacks semantic structure, metadata, and explicit instructions, the agent guesses. When it guesses, it hallucinates. MX eliminates the guesswork. And it goes beyond the website: contracts, policy documents, product specifications, and technical reports don't live on the web, but agents inside enterprise tools are reading them too. These resources explain what MX is, why it matters, and how to apply it, from core principles to common mistakes to the full set of MX patterns.

Choose your learning path

What is MX?

Machine Experience is the discipline of designing digital systems so that machines can read, trust, and act, reliably, safely and consistently.

Why MX matters

AI agents are becoming a new consumption layer for enterprise digital platforms. If your content isn't structured for them, they route around you.

Key principles

The core principles that guide every MX implementation, from semantic HTML to structured data to governance metadata.

Benefits of MX

What your organization gains from implementing Machine Experience, discoverability, citation, trust, and competitive advantage.

Explicit over implicit

When AI must "think" (infer from incomplete context), it hallucinates. Explicit structure prevents this. The foundational principle of MX.

Common mistakes

The pitfalls teams fall into when designing for machines, and how to avoid them.

The MX Principles

All 20 MX principles, the rules we build by. Not guidelines. Not suggestions. The things that stay true even when everything else changes.

Training vs Inference

Two fundamentally different ways machines access your website, and why both demand the same solution.

Accessibility & AI convergence

How accessibility standards and AI agent requirements converge, one investment, multiple returns.

Want to apply MX to your own website and document estate? Explore our services or get in touch.