Agenda de la conférence

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A tale of .NET migration - classic to modern

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Agents Building Agentic Apps: AI Goes Mobile with .NET MAUI

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Beyond the Prompt: Exploring AI-Assisted Game Development with .NET

How can developers use AI to explore an unfamiliar domain such as game development? This session will follow a small game-development experiment using C#, .NET, Visual Studio Code, Unity, and accessible cloud-based AI tools. The focus will be on the development process: defining a specification, guiding an AI agent, shaping the architecture, reviewing generated code, and validating the result. Along the way, we will connect these practices to web development and other areas of software engineering. No prior game-development experience is required; the session is an exploration of how AI can help developers learn, experiment, and build beyond their usual areas of expertise.

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Bringing the Edge Into Focus

I built a digital microscope that combined IoT and AI into something useful, practical, and centred on accessibility. It could see, read, and talk, and it ran entirely in the cloud. This year, the journey is moving all of it from the cloud to the edge. Join me as we take every capability off the cloud and onto the device itself. Vision, text recognition, speech, conversational AI, and even retrieval, all shifting from hosted services to models running locally on a small device, with no connection required. We will explore what each move from cloud to edge costs, where running locally surprises you, and what living on the device makes possible that the cloud never could. Best of all, this is all still done with .NET and Avalonia. Going from cloud to edge means this accessibility solution now travels with me, signal or not. Hopefully the session sparks some ideas about what else becomes possible when you move the intelligence onto the device.

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Bulletproof RAG: Implementing Enterprise Guardrails, Semantic Caching, and Security

Enterprise-grade RAG: guardrails, semantic caching and security.

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Continuous Quality Monitoring for .NET AI Agents with Amazon Bedrock

Quality engineering for .NET AI agents.

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Don't Ask, Watch: Real-Time Data and AI with .NET 11 and Foundry Local

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Don’t Store the River: Rethinking Analytics for Real-Time Data

What happens when seeing the data faster simply isn’t enough? Real-Time Intelligence is about recognising what matters and acting while the outcome can still be influenced. In this practical, demo-driven session, we’ll build an end-to-end Microsoft Fabric solution that turns a noisy stream of raw events into signals, decisions and actions. Along the way, you’ll learn when to store streaming data, when to aggregate it, and why a real-time dashboard is only part of the story.

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Foundry Local for .NET Developers

Building AI applications usually means relying heavily on cloud-hosted models, which introduces high token costs (COGs), unpredictable latency, and strict data privacy boundaries. While tools like Ollama or LM Studio offer local alternatives, they require your end-users to install heavy, external background dependencies, complicating the app distribution and installation pipeline Enter Microsoft Foundry Local, a lightweight, 20-megabyte, on-device AI runtime that solves these challenges. It packages a highly optimised local AI stack directly inside your process, eliminating the need for self-hosting setups, Docker containers, or external software installations In this session, we will deep-dive into how Foundry Local leverages the performance of ONNX Runtime and WinML to automatically select and run the absolute best variant of a model for your user's specific hardware, whether they have an NVIDIA GPU, Intel/Qualcomm NPU, Apple Silicon, or a standard CPU

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Seamless Navigation in .NET MAUI with Prism

Seamless Navigation in .NET MAUI with Prism. Navigation is one of the trickiest parts of building a cross-platform .NET MAUI app — especially once you need deep linking, tab/flyout navigation, modal flows, and passing parameters between view models without turning your code into spaghetti. Prism brings a mature, battle-tested MVVM and navigation framework to MAUI, giving you a clean, testable way to manage navigation state, dependency injection, and view model lifecycle across platforms. In this session, we'll build seamless navigation flows using Prism's navigation service, explore parameter passing and deep linking, handle navigation lifecycle events (OnNavigatedTo/From), and look at patterns for structuring larger MAUI apps so navigation stays maintainable as the app grows. You'll walk away with practical patterns you can apply directly to your own MAUI apps, and a clear sense of when Prism is the right tool for the job.

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Testing Agentic AI in .NET: skUnit for IChatClient, Agents, and MCP

Modern agentic AI systems rely on many moving parts, from IChatClient pipelines to Microsoft Agent Framework agents to MCP servers that expose external tools and capabilities. As these components interact, the need for reliable, deterministic testing becomes critical. You need to ensure: - Agents reason correctly and follow their execution loop - Tools are discovered and invoked with the right parameters - Responses stay semantically accurate across iterations - Multi‑agent and multi‑server orchestration behaves predictably This is exactly where skUnit excels, a robust .NET testing framework purpose‑built for agentic AI units, including IChatClient, Microsoft Agent Framework agents, and MCP integrations. Whether you're validating a single agent’s reasoning step or end‑to‑end orchestration across multiple tool surfaces, skUnit gives you production‑grade confidence in your AI systems.

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The Hidden Cost of AI: Infrastructure, Trust, and Governance in Emerging Markets

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The Next Era of Orchestrating AI using The Microsoft Agent Framework

Microsoft Agent Framework is Microsoft’s cutting-edge platform for building intelligent, autonomous, and collaborative AI agents. It enables developers to create agents that can reason, communicate, and integrate seamlessly with enterprise systems. In this session, we’ll explore its architecture, key features, real-world applications, and how you can start building your own AI-powered solutions today.

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The Rise of Intelligent Data Applications: .NET Meets Microsoft Fabric

In this session, we'll explore how .NET developers can build intelligent data applications using .NET, Foundry, and Microsoft Fabric. You'll learn how to connect applications with business knowledge, leverage Fabric as an intelligence platform, and build agent-powered experiences that transform raw data into actionable decisions.