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 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…
Egeria Advisor: Ingestion Tuning and the Multi-Agent Shift
In my last post, The Egeria Advisor: Casting Out Egeria Expert – Lessons Learned, I shared how we expanded the data scope of the Egeria Advisor to include core code repositories like egeria-python, egeria (Java), and egeria-workspaces. This expansion…
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…
AI Application Development – Building with Context Intelligence
From Planning to Building In our last installment, we discussed project definition and the context and clarity it can provide. In this installment, we’re going to jump into the part that most techies hanker for—the…
Context Intelligence – Project Definition – Establishing the Foundation
In our previous blog, we introduced the AI Application Journey—a framework showing how business context flows through five connected phases. Project Definition is the first and perhaps most critical phase, establishing the foundation that guides…
From Idea to Impact: Navigating the AI Application Journey
Organizations are investing heavily in AI—deploying the latest LLMs, implementing sophisticated RAG systems, building agents with MCP tools. Yet a surprising number of AI projects struggle to reach production or fail outright. The issue is…
Putting the Context into Context Engineering
Dan Wolfson Context engineering is one of the latest buzzwords across the AI community. The basic idea is to both improve the quality and manage the cost of a conversation with an LLM AI by…
PDR – 2025 Year in Review
December, 2025 Dear clients, partners, and friends, As we reach the end of 2025, our fourth year of operations, it is once again time to reflect on our achievements and learning over the past year,…