4:00 AM - 5:00 AM (UTC)

Design smarter AI workflows with visual orchestration, token optimization and extensible agent capabilities. Session Introduction AI agents are working across larger codebases and increasingly complex systems, making visual orchestration and efficient context management essential for modern development. In this session, you’ll explore how to design smarter, token-optimized AI workflows using Canvases in the GitHub Copilot app, context engineering, and extensible agent capabilities. Through practical demonstrations, you’ll see how developers can coordinate multi-agent work, manage context more effectively, and move beyond linear chat prompts to visual agent orchestration. You Will Learn • How to use Canvases in the GitHub Copilot app as a visual workspace for complex, multi-agent development • How token budgeting, prompt caching, and context trimming can improve workflow efficiency • How to extend agent workflows with Agent Plugins and Model Context Protocol (MCP) • Best practices for moving from one-shot prompting to collaborative agent orchestration Technologies Used • GitHub Copilot harnesses including CLI, app, and Visual Studio Code • Agent Plugins and Model Context Protocol (MCP) • Token optimization and context engineering Who Should Attend • Developers building agentic workflows across complex codebases • Engineers looking to improve AI workflow efficiency and context management • Teams extending GitHub Copilot with reusable agent capabilities • Anyone interested in visual, multi-agent development experiences

4:00 AM - 5:00 AM (UTC)

Measure, benchmark, and continuously improve Microsoft Foundry AI Agents using Microsoft IQ, Evaluations, and the Agent optimiser. Session Introduction Building an AI agent is just the beginning. Getting it right up front means giving it excellent context - but once it's live, keeping it good is a job of its own: evaluations to monitor quality, optimisation to keep cost in check, and reliable ways to tell whether any change actually helps In this session, you'll learn how to measure, benchmark, and continuously improve AI workflow quality using Microsoft Foundry, Evaluations, and the Agent Optimizer, and how Microsoft IQ gives your agent excellent context. You'll see how continuous evaluation replaces guesswork with measurable signals across your agent's lifecycle. You Will Learn • How to compare and select models with Microsoft Foundry • How to add organisational context to your Agents • How to build continuous evaluation pipelines for your Agents • How to profile the balance between quality, speed, and token cost • How to use Agent Optimizer to improve your Agents • How to manage your Agent in a CI/CD pipeline Technologies Used • Microsoft Foundry • Microsoft Foundry Extension for Visual Studio Code • Microsoft Foundry Evaluations and the Agent Optimizer • GitHub actions to integrate with Foundry Who Should Attend • Anyone interested in building, evaluating and optimizing Agents, in Microsoft Foundry • Teams introducing Agents into GitHub and CI/CD processes

4:00 AM - 5:00 AM (UTC)

From legacy modernization to AI operations: Modernize applications and operate AI systems at scale with self-healing agents and enterprise-grade operational intelligence Session Introduction Modernizing legacy applications at scale is only half the journey — the AI systems that follow demand continuous monitoring, rapid incident response, and dependable day-to-day operations, all without adding engineering burden. In this session, you’ll follow that path end to end: modernize legacy applications with automated, reviewable upgrades, then operate and scale AI systems using self-healing agents and enterprise-grade operational intelligence. You’ll see how AI can streamline large-scale application updates, connect runtime signals to remediation, and make complex operational work easier to review and govern. You Will Learn • How to scale legacy application assessments and upgrades with Copilot Modernize CLI • How stacked pull requests can make large automated migrations easier to review • How the Azure SRE Agent can help diagnose issues and propose tested remediations • How to track operational impact using token efficiency, recovery time, and acceptance signals Technologies Used • Azure SRE Agent • Copilot App Modernization Agent & Modernize CLI • Stacked Pull Requests • Human-in-the-Loop Governance Patterns Who Should Attend • Teams modernizing legacy applications across multiple repositories • Developers and platform engineers operating AI systems in production • Site reliability and DevOps teams exploring agent-assisted remediation • Technology leaders focused on scalable, resilient AI operations