An obscure, sparsely funded startup in China made a huge splash on the global AI scene when it launched DeepSeek R1 in Jan 2025! It showed the world that established players like OpenAI and Google could be challenged with fast, efficient, cost effective models developed with a fraction of the investments needed. Let’s explore how we can learn from this and subsequent successes to not just use AI but also help build the use cases for India’s AI future.

Stop building isolated applications and start cultivating internal and external ecosystems. This keynote introduces the strategic shift needed to scale engineering and accelerate business value exponentially. We will move Beyond Code by focusing platform thinking and needed mindset shift. Learn the core architectural principles that mandate separation from specific vendors and define stable interfaces as the primary delivery mechanism. We will explore the critical cultural changes like prioritizing generalized design and adopting clear contractual agreements that enable true organizational agility. Walk away with a clear roadmap for future-proofing your organization by thinking, designing, and operating reusable, scalable utility layers (or enablers).

This will be a fun filled session taking about silly mistakes done by enterprises causing financial burden and security debt.

In today’s fast-paced digital landscape, business goals, development speed, and operational stability cannot work in silos. This session on BizDevOps explores how organizations can break down barriers between business, development, and operations to drive true agility, faster value delivery, and measurable business impact. Through practical examples and real-world insights, we’ll uncover how BizDevOps enables alignment of strategy with execution, continuous feedback loops, and customer-centric innovation—helping teams move beyond DevOps to achieve sustainable digital transformation.

We have been using GitHub Copilot only as a developer assistant in our IDEs - but that is just 25% of what a developer does in his job - rest he builds, releases, updates tickets, documents, tests, deploys, integrates - let us take a look on how the overall GitHub platform can be leveraged to accomplish the rest of the 75% of a developer's workitems.

The AI gateway in Azure API Management is a set of capabilities that help you manage your AI backends effectively. In this session we will explore all possible features and rea world use cases.

Join this session to explore Auto Triage AI, a generative AI-powered solution that automates the entire bug triage workflow in Azure DevOps. We’ll break down how AI can intelligently create, update, and follow up on product issues, reducing manual effort while improving speed, accuracy, and scalability for support teams. Learn how AI-driven triage can transform your product issue management and unlock a more efficient, zero-touch workflow.

This session covers design considerations, development tips and distribution best practices for non-GUI applications, including server applications, CLI applications and automation tools which run on all three popular platforms: Windows, Linux and macOS.

Improved productivity with AI tools usage comes with increased security risks and compliance concerns. Microsoft Purview addresses this scenario and allows AI tools usage with enhanced security and compliance environment.

Ever wondered how programming languages, configuration formats, or domain-specific languages are built? Join us for a live coding journey where we'll build a simple parser from scratch using Yantra—a modern LALR(1) parser generator—and see how modern tooling makes grammar development feel like writing any other code. No compiler theory degree required!

A deep dive into how MCP (Model Context Protocol) brings contextual intelligence to AI agents—connecting them to live tools, data, and APIs. Let's explore how MCP servers orchestrate rich context across APIs, documents, and enterprise data, enabling agents to plan, reason, and act with precision. Finally, we’ll dive into governance, security guardrails, and quality evaluation for enterprise-scale deployments.

Building your own copilot is great. But the job doesn't end there. To be successful with it, you have to make sure it is being monitored and corrected. In this session we will explore ways to keep an eye out on your copilots in production.

Microsoft 365 is evolving into an intelligent, agent-driven platform — empowering organizations to bring their own AI to life. This session walks you through every option available to create and integrate agents inside the Microsoft 365 environment.

We’ll cover SharePoint Agents and Knowledge Agents, explore Declarative Agents, and connect the dots with Azure AI Foundry and Semantic Kernel. Learn how these technologies converge to help you design agents that reason, act, and adapt within the flow of work.

Turn your IDE into an AI‑native platform: Copilot accelerates code, unlock context orchestration across docs, APIs, and data. We’ll show cross‑language retrieval, tool use, and agentic planning, then cover enterprise governance, policy guardrails, quality evaluation, and cost‑to‑serve tuning.

Empowering AI Agents to Think, Collaborate, and Act as One - Discover how to design intelligent, cooperative AI systems using the Agent-to-Agent (A2A) Protocol. Learn how multiple AI agents can communicate, share goals, and make collective decisions - transforming isolated models into a unified, dynamic ecosystem that thinks, collaborates, and acts as one.

Learn how to move beyond simple chatbots and build intelligent, context-aware AI systems with LangChain. We’ll explore its building blocks, chains, agents, and tools—and show how they can be combined to create dynamic, data-connected applications.

Ever wondered why your "autonomous" AI agent nails the demo… and then falls apart by Monday morning in production? In this session, we’ll dissect the real engineering aspects behind it. Expect real architectures, failures, and learnings you can steal to make your agents reliable enough that you’re not scared to ship them.

With the evolution of Microsoft Teams Toolkit into the Microsoft 365 Agents Toolkit, developers now have a broader set of tools to build intelligent apps and agents across Microsoft 365. But with so many new capabilities—Declarative Agents, Custom Engine Agents, Copilot Connectors, Agents for Teams, and more—it can be challenging to know where to start and which approach fits your use case.

Analytics is a process of discovering, interpreting, and communicating significant patterns in data. Quite simply, analytics helps us see insights and meaningful data that we might not otherwise detect. Enterprises need to depend on various vendors and tools in order to analyze their data. Cloud-service Providers like Azure and AWS have these tools available as Platform-as-a-Service (PaaS) where you would need to configure individual services, integrate them which adds to complexities. With Microsoft Fabric service, it has tried to overcome this challenge by bringing all analytical solutions of Azure onto one platform with Software-as-a-Service (SaaS) foundation. In this training, participants will learn the capabilities of Microsoft Fabric and work with its components to solve their analytical problems.

Agentic AI refers to autonomous artificial intelligence systems that can set goals, make decisions, and act independently with minimal human input. This is used in dynamic environments where adaptability and self-direction are crucial. The Agentic AI is a form of Artificial Intelligence designed to behave like an autonomous agent. When the traditional AI, which relies heavily on human instructions and operates within fixed parameters, the Agentic AI can perceive its environment, reason, learn, and take action and decision to achieve goals on its own. In this session we will talk about building Agentic AI Applications.

If you are C# developer and want to start with AI ML and then this session is for you. In this session we will walk through important pillars of machine learning from C# Developer perspective and how they can start their AI ML journey.
* AI vs ML
* Understanding FLAPM( Features ,Labels , Algo, Pipeline and Model)
* Model is all Maths.
* Simple example of regression prediction using C# ML.NET
* AutoML introduction.
* What about Texts ? BOW , TF&*IDF , One Hot , Embeddings , Transformers
* Simple .NET interview preparation application using Azure Open AI , Semantic Kernel , Prompts and Embeddings.
* Agentic AI and generative AI discussion.