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…
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…
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…
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…
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…
Scientific data includes context information (metadata) to make its creation reusable in downstream analysis. This metadata comes with a vocabulary that is helpful in understanding how business data – that is data from the systems…
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…
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…
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…
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…