Matt Brailsford discusses the Umbraco.AI.Prompt package, detailing how content editors can utilize prompt templates for AI-generated tasks like SEO titles and alt text. He explains the syntax, available variables, and the importance of using the image: prefix for image prompts, alongside practical examples and tips for maximizing AI capabilities.
2026-04-16 from 18:00 to 20:00 (Europe/London) - Cantarus, Lower Ground Floor, Jutland House, 15 Jutland St, Manchester M1 2BE, Manchester, GB
Adds an Evaluate Page button to the content editor toolbar which sends the current page's content to an AI model and returns a structured quality report
Bolette Kern introduces the Umbraco in AI Community Team and Advisory Board, comprising 27 experts dedicated to enhancing AI integration in Umbraco. Their mission focuses on developing practical AI tools and improving editorial workflows, ensuring AI solutions meet real user needs while fostering creativity and efficiency in content management.
Matt Brailsford discusses the concept of contexts in Umbraco AI, which serve as reusable containers of knowledge that enhance AI output by providing essential background information. Contexts can include various resource types, such as Brand Voice and Text, and can be assigned at multiple levels, improving the relevance and quality of generated content.
Nevitech IT Solutions Ltd developed AI.LogAnalyser during the Umbraco Spark Hackathon, creating an open-source package that integrates AI analysis into the Umbraco backoffice log viewer. Users can click a button for AI-generated insights on log entries, streamlining error diagnosis and remediation using various AI providers through Umbraco AI.
Recorded at Umbraco Spark in Bristol, Emma, Laura, Lotte, and AI engineer Phil Whittaker discuss playful learning, returning to work amid AI changes, renewed motivation for senior developers, and why augmentation is more valuable than automation, with a lively audience.
In this episode of umbraCoffee, hosts Marcin and Callum, along with guest Warren Buckley, discuss AI's impact on developers, recent Umbraco updates, and community collaboration. They highlight features like Content Guard, AI integration, and security improvements, emphasizing the importance of engaging young developers in the Umbraco ecosystem.
2026-04-02 from 18:30 to 20:30 (Europe/London) - MSQ DX - Leeds Office, 28 Sovereign Street, Leeds, West Yorkshire, GB
Sebastiaan Janssen's guide details the setup of the Umbraco.Community.AI.Woowoo package project, utilizing Lottie's Opinionated Package Starter Template. It outlines prerequisites, installation steps, and configurations for a structured Umbraco.AI development environment, including frontend build pipelines and GitHub Actions for NuGet publishing, ensuring a solid foundation for package development.
2026-03-25 from 14:00 to 20:00 (Europe/Copenhagen) - twoday Aarhus, Søren Frichs Vej 44D, 8230 Åbyhøj, Aarhus, DK
2026-04-02 from 18:30 to 20:30 (Europe/London) - MSQ DX - Leeds Office, 28 Sovereign Street, Leeds, West Yorkshire, GB
Umbraco plugin for generating creative meta title and meta description values for pages with missing metadata.
Adds AI-powered log analysis to the Umbraco backoffice log viewer.
AI-powered property validation for Umbraco CMS using the Umbraco.AI infrastructure.
In this blog post by Phil Whittaker, the focus is on Agent Skills for Umbraco, which enhance AI's ability to assist developers in creating backoffice extensions. These skills provide structured knowledge, facilitate rapid prototyping, and improve coding accuracy, ultimately transforming how digital projects are delivered with AI integration.
In the first quarter of 2026, Filip Bech-Larsen highlights significant updates for Umbraco, including the launch of Umbraco Compose, advancements in AI integration, enhanced security in Umbraco Cloud, and improvements in search functionality. The updates aim to enhance stability, scalability, and user experience across the platform.
Umbraco AI offers a modular, opt-in approach to integrating AI features into its CMS, allowing users to select desired functionalities and providers while maintaining data control. The architecture includes core packages for connections, profiles, and prompts, enabling custom AI feature development. A practical example demonstrates an AI log analyzer, showcasing the system's flexibility and provider-agnostic design.