Egeria Resource Explorer (Part 4): Surveys Measure, Chat Asks
Active Surveying Beyond the Catalog Perimeter | Part 4 Why a tool built on careful surveys also needs a chat panel, and what we do to keep the answers honest. In Part 3 we followed…
Egeria Resource Explorer (Part 3): Asking a Question
Active Surveying Beyond the Catalog Perimeter · Part 3 What happens when you actually ask one: prerequisites, what it costs, and how the answer gets published. In Part 2 we took a single row of…
Egeria Resource Explorer (Part 2): The Anatomy of a Question
Active Surveying Beyond the Catalog Perimeter · Part 2 One catalog of questions across five resource types, and what a single row of it actually contains. If the Funnel Is the Shape, This Is the…
Egeria Resource Explorer: Effective Exploration and the Survey Funnel
Survey first, catalog the worthy.
Egeria Workspaces 6.1 — and an open demo you can try in two minutes
Four and a half months ago, egeria-workspaces was one working demo. Since the v6.02 tag on April 2nd, it’s grown into a small constellation of purpose-built apps over Egeria’s metadata — plus the time-travel, bulk…
Egeria Advisor: Literate Governance and the Collaborative Canvas
In my last post, Egeria Advisor: The Live Gateway and the Feedback Loop, we explored how the Egeria Advisor transitioned from a passive reference guide into an active operational tool by integrating the Model Context…
Egeria Advisor: The Live Gateway and the Feedback Loop
In my last post, I detailed how we addressed the challenge of non-determinism by moving to a coordinated multi-agent architecture and introducing explicit Intent and Perspective controls into the front-end Web UI. By wrapping our…
The Egeria Advisor – Sharing the Journey
Dan Wolfson We have to build systems that people want to use, that provide value to them individually, that makes their work life better – not just view humans as knowledge sources to train the…
Responsibilities and activities supporting data readiness for AI projects
In my first post on Data Readiness, I introduced the notion of a Data Readiness activity to provide the AI development team with the political power to make the resources (typically data and subject matter…
Data Preparation in the AI Journey (Part 2)
In my previous post, I outlined five key pillars: Scope, Compliance, Trustworthiness, Understandability, and Cost. While these pillars provide a design framework, moving an AI application from an interesting experiment to a production-grade tool is not a…