How Microsoft Used Its Own Tech To Lead The Gartner® Magic Quadrant™ for AI Application Development

Microsoft

Dec 17, 2025

Big news: Microsoft has been named a Leader in the 2025 Gartner® Magic Quadrant™ for AI Application Development Platforms. This recognition isn’t just a badge—it’s validation of the work we’ve done to make AI development faster, smarter, and more enterprise-ready.

Behind the scenes, my team and I faced a challenge that every product leader knows well: hundreds of detailed questions from analysts about our platform. These questionnaires are massive, multi-sheet spreadsheets full of nuanced queries. Answering them accurately and consistently is critical, but doing it manually is a time sink.

So we turned to the very technology that earned us this leadership position: the new Microsoft Agent Framework.

Building an Agent to Answer Hundreds of Questions

The Microsoft Agent Framework brings together ideas from Semantic Kernel and AutoGen into the most complete multi-language, multi-agent workflow builder on the market today. To put it to the test, I built the third version of my questionnaire-answering app, a system designed to automate the process of responding to those sprawling analyst questionnaires.

Here’s how it works. Three specialized agents form the core:

Question Answerer: Generates the initial response.

Answer Checker: Validates accuracy and tone.

Link Checker: Ensures every reference link is valid.

This team of agents doesn’t just answer questions; it collaborates, debates, and iterates until the output meets our standards. This is what’s colloquially known as a “maker-checker pattern.” And yes, the repo is public: https://github.com/mcasalaina/QuestionnaireAgent_v3.

From Spec to Reality With Structured Vibe Coding

This is the third iteration of this agentic system. This time, I used Spec Kit, an AI-powered tool that breaks down requirements into user stories, functional specs, and success criteria. It even interviews you with multiple-choice questions, like how to handle edge cases you hadn’t considered. This works wonderfully with structured vibe coding, a process I've blogged about in the past, in which you give an agent like GitHub Copilot a fully fleshed-out spec to ensure it builds exactly what you’re looking for.

Teams of Agents

To continue improving my Questionnaire Agent, I filed Issues in GitHub, and then assigned these issues to GitHub Copilot. I could assign many of these issues at once, and GitHub Copilot spawns an asynchronous coding agent for each, fixing them all at the same time. As the “manager” of this team of coding agents, I review and test their pull requests, and sometimes resolve conflicts if multiple agents edit the same section of code. It is a very effective way to divide the work among a team of agents.

And I applied a similar "divide and conquer" principle to my own Questionnaire Agent – I made it run three teams of agents in parallel, each tackling different questions on the questionnaire at the same time. That’s a team of teams of agents, and it gets the job done.

Why This Matters

This isn’t just a cool demo. It’s a glimpse into how AI can transform real workflows, whether you’re answering questionnaires, generating specs, or fixing bugs. The Microsoft Agent Framework makes it possible to orchestrate complex, multi-agent systems with ease, and it’s available now for developers everywhere.

The Questionnaire Agent’s answers are not perfect. My team and I reviewed every answer, often making revisions as needed. But with each iteration of this agent, it gets better, faster, and more sophisticated, and that saves us all valuable time.

So yes, Gartner recognized us as a Leader. But more importantly, we’re using these AI tools ourselves – because the future of AI isn’t just about building smarter apps. It’s about building apps that help you get stuff done.