GitHub Copilot showed me something new: GPT-5.6 Sol, plus a 30% discount. Yes, and I couldn’t resist trying it on a Dataverse task. Why not see the new model in action, right? As a result, that decision burned nearly a month’s budget before the task was even done. But here’s the thing: the expensive part isn’t the story worth telling. What came out of it was a GitHub Copilot custom skill – a reusable file that captures everything the agent…
Missed my session at M365 Con DACH 2026? Good news – the recording is live. One note before you press play: it’s in German. On paper, my session covers Power Platform and document processing with AI Foundry Content Understanding. That’s the abstract I submitted. Reality had other plans. Shortly before the talk, my demo environment fell apart, and I had to rebuild it fast. So I turned to GitHub Copilot. It rebuilt the Dataverse tables, flows, and the Content Understanding…
The backlog from my last post had one line I couldn’t ignore: status transitions weren’t implemented yet. Tables, views, the model-driven app – all done. The missing piece was the Dataverse Agent Task contract itself. In other words, the part that lets Power Platform and Azure talk to each other. That wasn’t a bug. It was a missing seam. Without an explicit contract, two teams can’t build independently. They can’t test independently either. Remember my post about project decomposition? I…
“Dad, can we build an app with AI?” That question started a spec-driven development experiment I’ll never forget. He was seventeen. No coding background, no CS classes. Just frustration with the school carpool situation: thirty parents in a WhatsApp thread, nobody knowing who was driving, every morning a small disaster. I said yes. But on one condition: we use GitHub 🌱 SpecKit. He looked puzzled. Fair enough. So I explained: it’s a framework for Spec-Driven Development. Describe the problem the…
My spec was done. The plan too. Time to build the Dataverse foundation: the piece everything in my Expense Management system would run on. I connected the Dataverse MCP server in VS Code, opened my prepared spec, and ran /speckit.implement in GitHub Copilot. The GitHub 🌱 SpecKit workflow with Copilot to implement my Dataverse solution felt ready. I expected it to just work. It didn’t. The MCP hit its limits fast. Cryptic errors, wrong solution placement, no model-driven app support….
The Dataverse-first restart was done. However, my spec looked sharper. The data model had a center of gravity, and that part actually worked. Solving one problem, however, revealed another. One spec was still covering six very different concerns: different timelines, different risk profiles, and different people who would eventually build and own each piece. Nothing defined where one concern ended and another began. That’s not a spec problem. Instead, it’s a structure problem. In my previous post, I said the…
I ended my last post “Spec-Driven Development: When the Spec Is Too Big” with a promise: “My next post covers what happens when I restart with Dataverse-first.” Here it is. But Dataverse-first is harder to put into a spec than it sounds. I wanted AI to develop my optimal data model and not to dictate it upfront. The trick was giving GitHub 🌱 SpecKit the right bigger picture first. Describe the full problem. Steer toward the data layer. Then strengthen…
I had a spec, I had GitHub Copilot Pro+! A new billing period with fresh credits has begun. So I started to refurbish my Expense Management system. In detail, I was building with a fresh spec that should rebuild the whole system in one run. And yes, that was the problem. Everything looked good. Copilot credits were melting away during implementation. Some hours later I had my first results. The Azure portal showed me what was there. Content Understanding analyzers:…
Most developers I know have been here. They type a detailed prompt into their AI agent. The output looks right. They run it, tweak a detail, run it again – and somewhere around the third attempt, the whole thing has quietly shifted into something else. The problem is not the AI. The problem is the approach. Spec-driven development changes that. Before a single file gets created, you define intent. You build a shared understanding for your business stakeholders, your architect,…
I haven’t written a line of code since January. Not because I couldn’t. I stopped because spec-driven development showed me I was spending time on the wrong part of the job. Today, it is easy to type “build me XYZ” and get code in seconds. I did that too. Sometimes the result looked great. Then I ran the same prompt again and got something different. Logic shifted. Edge cases disappeared. The output stopped being predictable. The turning point came when…