Putting Context into Context Engineering
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 augmenting the…
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…
The Egeria Advisor: Casting Out Egeria Expert – Lessons Learned
In my last post, The Egeria Advisor: Sharing the Journey, I introduced the foundational vision behind the Egeria Advisor—injecting “Context Intelligence” into AI applications by leveraging organizational and situational context to provide more useful results. But…
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…
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…
Data Preparation in the AI Journey (Part 1) – From Strategy to Operations
It’s widely recognized that data preparation is critical for AI projects. But where does it actually fit in the development process? In my previous post, AI Application Development – Building with Context Intelligence, we explored…
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…