Everyone talks about AI as if it is about to replace developers. And many teams assume that generating more code will automatically make them faster. But real engineering work is rarely that simple. When you start using AI in a different way, something unexpected happens: the real bottlenecks show up in places you were not looking.

In this session, Tessa shares how she used AI to support a mixed engineering team with offshore developers, internal staff, and external consultants working on a highly complex .NET and Azure platform. Not by automating their work, but by uncovering hidden bottlenecks, improving collaboration, and accelerating modernization efforts that had been stuck for years.

Through concrete, real-world examples, she shows how AI can:
• Highlight patterns in Azure DevOps workflows that no one noticed
• Improve communication and alignment across distributed teams
• Modernize large and aging codebases with LLM-supported refactoring and test generation
• Bring clarity, speed, and confidence back into engineering processes

This is not a theoretical AI story.
It is a field report from someone who has done the work, delivered results, and learned where AI truly makes a difference in modern software teams.

• Target audience: .NET developers, tech leads, architects, DevOps engineers, engineering managers
• Session type: technical / practical / case‑study
• Technical level: intermediate to advanced
• First public delivery: available for conferences from May 2026
• Preferred duration: 30–45 minutes
• Requirements: projector + audio; optional demo environment (Azure/OpenAI)