About the author
Tom Cranstoun
Co-founder at Tityra | Content systems architect
Tom Cranstoun is a content systems architect and co-founder of Tityra. His work in publishing technology began in 1977 and spans the Superbase database, the BBC's electronic newsroom and Adobe Experience Manager. He now writes about what happens when AI agents read the content those systems publish.
More about Tom
UNDERSTAND AGENT ACCESS
Learn how website content is delivered to clients.
CONNECT FINDINGS TO EVIDENCE
Follow practical explanations of website content audit methods.
PUT GUIDANCE INTO PRACTICE
Find clear next steps for your content and delivery teams.
About the author
Tom began writing assembler in 1977, co-authored the Superbase database and worked on the BBC's electronic newsroom. He later spent more than a decade working with Adobe Experience Manager (AEM). His work includes publishing systems for Twitter, Ford and MediaMonks, and a Nissan-Renault programme spanning hundreds of websites.
While working with Adobe Edge Delivery Services, Tom found that an error message that disappears before it can be read, or a page that leaves its current state implicit, can cause problems for people and automated readers. That work informed his approach to Machine Experience (MX). In his writing on Edge Delivery Services, he explains how semantic HTML and explicit state help readers work out what happened. He recommends putting essential information in the initial HTML so it can be retrieved before JavaScript runs.
Through Digital Domain Technologies, Tom reviews implementation plans and advises teams on AEM architecture, Edge Delivery Services and AI integration. He mentors the people who will maintain the systems, speaks at industry events and is a member of Boye & Company's CMS Experts Group. Tom founded The Gathering, an independent community working on open standards for machine-readable content. He wrote MX: The Handbook to document practical patterns for publishing content that people and software can use. At Tityra, he applies this work to Agent Experience and the evidence teams use to decide what to fix first.
