Who I Am
Twenty-five years ago I wrote my first SQL query and have not stopped since. Today I am the Manager of Data Operations at Vail Health, where I lead the data infrastructure that keeps a complex health system running. The work spans everything: data warehousing, data lakes, analytics engineering, visualization, and increasingly, AI architecture. Data is not my job description — it is how I think.
The discipline runs deep. I have spent a quarter century at the intersection of raw operational data and the humans who need to make decisions from it. I understand what it means to build something that works at scale, to maintain it when it breaks at 2 a.m., and to explain it to someone who has never seen a schema. That breadth is what I bring to this hub.
When the AI wave hit in earnest, I did what I always do: I went looking for the technical substance underneath the noise. Most of what I found was written for executives or enthusiasts — high-level, heavily caveated, and stubbornly vague about how anything actually works. I wanted the real thing. So I started building it myself.
What This Hub Is
The AI Intelligence Hub is a technical publishing operation. It covers artificial intelligence and data across the domains I live in: healthcare AI, agentic systems and the Model Context Protocol, Snowflake and the modern data stack, Microsoft's AI platform, vendor platforms, and the technical writeups that explain how these things actually work under the hood.
The content is meant to un-dumb things. Too much AI writing talks down to the reader or buries the mechanism in marketing language. Everything published here assumes you are a professional who can handle precision. If a concept is hard, I explain it carefully — I do not simplify it away.
I built this because I want this information. I use every article, digest, and research brief myself. If it is not useful to me, it does not ship. That filter keeps the quality honest.
What I Publish
There are two publishing cadences. Daily digests track the news cycle — curated stories across each coverage area with a brief and a technical breakdown, so you can stay current without drowning in feeds. Weekly deep-dives are longer-form: platform research briefs on specific vendors, technical writeups that walk through architecture and implementation, and analytical pieces that connect what is happening across the industry.
Daily Digests
Each digest covers one category — Healthcare AI, MCP and Agentic Systems, Snowflake, or Microsoft AI — and surfaces the stories that matter to practitioners. Every entry gets an executive brief and a technical breakdown. The goal is not to summarize the headline; it is to extract what a working data or AI professional should actually know from it.
Deep Research
Platform research briefs are structured evaluations of specific vendors and tools: architecture, capabilities, integration surface, compliance posture, pricing model, and honest red flags. Technical writeups explain how specific technologies work — not the marketing version, the implementation version. These are the documents I wish existed when I was evaluating something for the first time.
Technical Writeups
Long-form technical documents on architecture, data patterns, AI integration, and engineering decisions. Written at the level of someone who will actually build the thing, not someone who needs to approve the budget for it.
What This Is Not
This work is entirely personal. It is not affiliated with Vail Health, does not represent the views or work of my employer, and was not created in any professional capacity. I do this because I love data and I want to share that with the world — full stop.
There are no vendor affiliations, no sponsored content, no affiliate links, and no undisclosed relationships with any company covered in this hub. When I say a platform has a weak integration story or a pricing model that does not scale, I say it because the evidence supports it — not because a competitor paid me to say it, and not because I am afraid to.
This is free. It will remain free. The value here is in the quality of the analysis and the access to information that practitioners need but rarely find aggregated in one place.
Contact
I publish because I want people like me — practitioners who are serious about data and AI — to have access to the depth of information that actually helps them do their work better. If that describes you, I would like to hear from you.
Questions, corrections, topic suggestions, or just a note that something was useful: find me on LinkedIn. I read everything.
Jody Claggett
Manager of Data Operations · Vail Health
25 years in Data Analytics, Warehousing, Lakes, Visualization, and AI Architecture