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Tag: Generative AI

Spec-Driven Development: When the Spec Is Too Big
Spec-Driven Development: When the Spec Is Too Big

Spec-Driven Development: When the Spec Is Too Big

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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:…

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Spec-Driven Development: The Methodology Behind the Magic
Spec-Driven Development: The Methodology Behind the Magic

Spec-Driven Development: The Methodology Behind the Magic

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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,…

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Stop Coding. Start Building from Specs.
Stop Coding. Start Building from Specs.

Stop Coding. Start Building from Specs.

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…

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Copilot Studio Child Agents: ServiceNow Incident Pipeline
Copilot Studio Child Agents: ServiceNow Incident Pipeline

Copilot Studio Child Agents: ServiceNow Incident Pipeline

“The dangerous part starts when people try to build one agent for everything. Then you don’t have automation anymore – you have a very polite chaos machine.” Fellow MVP and friend Marcel Lehmann commented that on my last post. And yes – he was describing exactly what I had built at first. Until I started to split my agents and recombine them again with a new feature. This is the final part of my Teams ITSM Copilot series. You’ve seen…

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Building a Copilot Studio Incident Collector for Microsoft Teams
Building a Copilot Studio Incident Collector for Microsoft Teams

Building a Copilot Studio Incident Collector for Microsoft Teams

Your Teams channel is busy. Messages come in constantly – questions, announcements, status updates, and a well known “I have a quick question…” that turns into a long thread. But how do you know which ones are actually incidents? In my previous post, I introduced a multi-agent ITSM system built with Copilot Studio. One agent qualifies incidents, another tracks them in ServiceNow. But before any of that happens, someone needs to watch the channels. That’s the job of the Incident…

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Hey Code, Specify!

Hey Code, Specify!

I was deep into spec-driven development with GitHub’s Spec Kit. Writing detailed specifications. Describing what I wanted AI agents to build. And I was typing. A lot. My fingers became the bottleneck. Then I thought: why am I typing when I could be talking? I opened Copilot Chat and looked for a microphone. Nothing. Turns out there’s a small extension you need: “VS Code Speech for Copilot.” I installed it and the microphone appeared. But then I discovered something better. The…

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Building an AI Agent That Generates Test Data

Building an AI Agent That Generates Test Data

Recently, I was creating an agent with the goal to identify potential incidents in Teams community of practice channels. I started building this agent to find problems such as “I need help” and create ServiceNow incidents from its information. Testing it meant feeding realistic support cases into the system. But here’s the problem: real support data contains sensitive information. Project names. Client issues. Internal struggles. You can’t demo that publicly. You can’t even use it safely in testing. This isn’t…

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Agents, Agents, Agents

Agents, Agents, Agents

The Agents topic is everywhere and omnipresent. Everybody tells you; this is the next big thing. You need an army of agents that finish your work. But how do I build such agents? Should I go for pro-code or for low-code? Should I use AI Foundry or Copilot Studio. Furthermore, what is a good example of building an agent? This was also the billion dollar-question for me. Today, I will showcase a small example to you where I will build…

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Using AI for Data Correction

Using AI for Data Correction

How do you usually use Generative AI? That’s a question I get asked quite often. Most of the time, my answer is something like this: “I use it to summarize texts. I also draft ideas together with the AI, and it helps me write content more efficiently.” But this is just one piece of the puzzle. In automation scenarios within the Power Platform, I also utilize AI for data correction. Today, I will explain how this process works. In detail,…

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Better RAG – Data Preparation for Copilot – Part 2

Better RAG – Data Preparation for Copilot – Part 2

In my last blog post, I explained you why data preparation for Copilot Agents is necessary. In other words, why we must improve the raw data for RAG (Retrieval Augmented Generation). Today I will delve more into the technical details of the preparation step. Let’s discover together what I can do to improve my raw PDF documents. First, I will explain to you how I extract content as Markdown from these documents with Azure AI Document Intelligence. I’m implementing this…

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