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Publications

Publications

A split blue-and-orange technology illustration comparing Microsoft Fabric Mirroring and Eventhouse. Blue database cylinders and data pipelines appear on the left, while orange event streams flow into a stacked analytics platform on the right. Centered text reads “Mirroring or Eventhouse?” with “J. Michael Smith” below. A split blue-and-orange technology illustration comparing Microsoft Fabric Mirroring and Eventhouse. Blue database cylinders and data pipelines appear on the left, while orange event streams flow into a stacked analytics platform on the right. Centered text reads “Mirroring or Eventhouse?” with “J. Michael Smith” below.
02/10/ 2026
Mirroring or Eventhouse?

A team I was talking with recently had a familiar mid-market reporting problem. Their nightly refresh took eight hours. The data lived in on-premises SQL Server, stitched together with linked servers, and almost none of the tables had indexes. Reports were stale by the time anyone opened them, and if a job failed overnight, they were stale for a full day. They wanted to move to Fabric and build semantic models on top. The first question on the table was whether to connect the linked server to Eventhouse…

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Illustrated infographic titled “The Most Expensive AI Model Is the One You Didn’t Need” by J. Michael Smith, showing how an AI request is routed by intent, confidence, and policy to deterministic data retrieval, a small specialized model, or a complex reasoning model based on the intelligence required. Illustrated infographic titled “The Most Expensive AI Model Is the One You Didn’t Need” by J. Michael Smith, showing how an AI request is routed by intent, confidence, and policy to deterministic data retrieval, a small specialized model, or a complex reasoning model based on the intelligence required.
25/09/ 2026
The Most Expensive AI Model Is the One You Didn’t Need

There is a growing conversation about the cost of artificial intelligence. Tokens cost money. GPUs cost money. AI subscriptions cost money. Enterprise licensing costs money. As organizations put AI into more business processes, those costs scale surprisingly quickly. All of that is true, and I think most of the conversation is happening at the wrong layer. Before asking what an AI model costs, we should ask two simpler questions: Did this task need an AI model at all, and if it did, did it need that model? That…

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Illustration for “Right Tool. Wrong Architecture.” showing a balance between 95% of business needs already met and a 5% missing capability, with integration, security, data, skills, operations, and vendor considerations. Illustration for “Right Tool. Wrong Architecture.” showing a balance between 95% of business needs already met and a 5% missing capability, with integration, security, data, skills, operations, and vendor considerations.
18/09/ 2026
Right Tool. Wrong Architecture.

There is a question we should ask more often when evaluating new technology: if we can already solve 95 percent of this problem, what is the remaining 5 percent worth? Not just the difference in licensing cost. What is that 5 percent worth after we account for another platform, another integration, another security model, another place for data to live, another skill set to maintain, and another vendor relationship to manage? I have always believed in using the right tool for the right job. I still do. But…

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11/09/ 2026
We Built the Grader Before We Built the Agent

Anyone can build a chat window that answers questions about invoices. Connect a language model to the data, ask, “What is our outstanding AR for this company?” and it’ll give you something. In a demonstration, it can look like magic. The problem is the word something. In accounts receivable, an answer that is close isn’t a smaller version of the right answer. It’s a wrong answer wearing a suit. If someone carries that number into a collections call, financial report, or board presentation, “approximately right” isn’t helpful. It’s…

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09/09/ 2026
The Journey Begins

The texlytics Charter Series The Journey Begins Nine weeks ago, I began sharing the ideas behind the texlytics Charter. I did not write it because texlytics needed more polished language. I wrote it because I wanted to be honest about what I am building, why I am building it, and the kind of company I want texlytics to become. I have spent much of my career untangling data, systems, and processes. Along the way, I have seen technology create incredible opportunities, but I have also seen what happens…

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04/09/ 2026
Your ERP Is Not Your Source of Truth. And That’s Okay.

One of the most common questions I hear when talking with business leaders is, “What’s the best ERP system?” It is a reasonable question, but after more than twenty-five years of designing integrations, building data platforms, and helping organizations solve technology problems, I have come to believe it is the wrong place to start. The better question is not which system can do everything. It is how we make all the systems already running the business work together. The Reality of Modern Business I have yet to work…

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