The Call for Presentations for Visual Studio Live! & Artificial Intelligence Live! @ Microsoft HQ 2027 is now OPEN.

Proposals are due: Monday, December 14, 2026, 11:59 PST

Visual Studio Live! @ Microsoft HQ: August 2-6, 2027

• Microsoft Headquarters, Redmond, WA

Visual Studio Live! & Artificial Intelligence Live! @ Microsoft HQ will offer a combination of in-depth and interactive sessions including lecture-based workshops, hands-on labs, 75-minute breakouts, and 20-minute fast focuses. We invite you to submit sessions in any of these categories. 

Tips for a successful submission:

Speakers are typically booked for at least two 75-minute sessions, so submit 3 or more 75-minute topics (plus any labs/fast focuses you'd like to give), especially overview/intro topics that many other speakers are likely to submit. A clear, track-appropriate title and a description with concrete takeaways matter most, since many speakers submit similar topics; a strong title, abstract, and takeaways are often what separates otherwise-similar submissions. Having several selectable talks also helps us say yes to great speakers who'd otherwise be cut for having only one.

Visual Studio Live!

Application Development

The Application Development track covers development of applications in and around the Microsoft technology stack. We want talks on ASP.NET Core and minimal APIs, Blazor and modern web UI, .NET MAUI and Blazor Hybrid, desktop development with WPF and WinUI, console and worker services, REST and gRPC services, real-time applications with SignalR, and the client-side technologies these apps depend on, including TypeScript, JavaScript frameworks, and component libraries. Sessions grounded in other stacks and ecosystems are welcome when the lessons travel. While we have a dedicated track for data, databases, and data science, this track is a great home for data access frameworks like EF Core and Dapper.

Your topics might demonstrate applied or integration AI as part of an application, be focused on human user interactions and workflows, or be focused on pure backend computing scenarios. We are especially looking for sessions that go beyond the "new project" template into what it takes to build and maintain real applications: UI and component design, state management, authentication and authorization in the app layer, accessibility, offline and occasionally connected scenarios, API versioning and integration, testing strategy, performance and startup tuning, packaging and deployment, and modernizing or upgrading existing apps rather than rewriting them. Whether you're building greenfield, adding a modern front end to something long-lived, or shipping the same codebase to web, desktop, and mobile, bring concrete patterns, trade-offs, and demo-driven guidance attendees can apply to their own applications.

Here are examples of topics that have been selected in past shows for this track:

• Integrating AI into your Apps

• What is new in Blazor

• Creating Secure REST Services

• Building MAUI and Blazor Hybrid Applications

• What's New in EF Core

• Database-as-Code: Beyond the ORM

Career, Leadership, and Human Factors

The Career, Leadership, and Human Factors track covers the people side of building software: how individuals grow, how teams work well together, and how organizations support both. We want talks on leading and influencing at any level, communicating and collaborating across teams and disciplines, and building the resilience, culture, and practices that make sustainable, high-quality work possible. Whether your story is personal (career, wellbeing, mindset) or organizational (culture, change, delivery), the focus should be on people and how they work, not a specific tool or technology. Practical lessons and frameworks attendees can bring back to their teams to make an immediate, positive impact are especially welcome.

Here are examples of topics that have been selected in past shows for this track:

• Human Skills in an AI World: How Technologists Stay Essential

• Elevate Your EQ: Practical Skills to Strengthen Relationships, Regulation, and Leadership Impact

• Navigating Your Career as a Software Engineer

• The Silent Question: What If Technology Disrupts My Role?

Cloud, Architecture, and Security 

The Cloud, Architecture, and Security track covers how systems are designed, deployed, and defended in the cloud, on-premises, at the edge, or across all of them. 

We want cloud talks on Azure, AWS, and GCP, and cloud-native depth on containers, Kubernetes and AKS, Azure Container Apps, serverless, Aspire, distributed application patterns, hybrid and multi-cloud, migration and modernization, cost and governance.

We want architecture talks on the decisions that shape a system including microservices versus modular monoliths, vertical slice architecture and other approaches, domain and API design, messaging and event-driven patterns, integration and legacy interop, resiliency, and observability. Whether you're designing greenfield, rearchitecting something you've outgrown, or hardening a system that's been in production for decades, bring concrete patterns, trade-offs, and lessons from real experiences and environments.

We want security talks that apply to anywhere code runs including identity and access management, authentication and authorization, zero trust, securing APIs and service-to-service calls, secrets and key management, encryption at rest and in transit, supply chain risk, and threat modeling for developers and architects.

Here are examples of topics that have been selected in past shows for this track:

• Zero Downtime at Scale: Architecting Highly Resilient Applications in Azure

• In Defense of Microservices

• Securing Your Cloud Applications with Identity and Networking Best Practices

Data Engineering and Analytics  

The Data Engineering and Analytics track covers the full lifecycle of getting data from source to insight: storage, movement, modeling, and analysis, on Microsoft platforms and beyond. We want talks on SQL Server and Azure SQL, big data and lakehouse architectures including Microsoft Fabric and Azure Databricks, and data integration and pipelines. We're also looking for sessions on choosing the right data store across relational, NoSQL, and specialized options, data security and encryption, and the data science tooling like Jupyter Notebooks that developers use to explore and work with data. Whether you're deep in a single platform or bridging several, bring practical patterns attendees can apply to their own data estates.

Here are examples of topics that have been selected in past shows for this track:

• Top 10 SQL Features for Developers You Might Have Missed

• Choosing the Right Data Store: SQL Server, PostgreSQL, Sqlite, etc.

• Developer's Guide to Fabric Pipelines & Data Engineering Workflows

• Lakehouses, Warehouses, and OneLake Explained: Architecting with Microsoft Fabric

• Where Should I Be Encrypting My Data

Developer Experience and DevOps   

The Developer Experience and DevOps track covers how teams build, ship, and operate software well. We want topics ranging from the day-to-day developer workflow to the pipelines, platforms, and practices that get code into production reliably. On the inner loop side, we want talks on getting the most out of Visual Studio and Visual Studio Code, source control and branching strategies, performance and profiling, testing strategy and automation, and AI-assisted development across both traditional IDEs and CLI-driven tools like GitHub Copilot, Claude Code, and Codex. On the outer loop side, we're looking for agentic DevOps and AI-assisted delivery, CI/CD and release tooling (Azure DevOps, GitHub Actions, and beyond), Site Reliability Engineering, Platform Engineering, and the DevSecOps practices that keep security built in rather than bolted on. Whether your session is about the IDE, the terminal, the pipeline, or the team running all three, we want practical, demo-driven content that attendees can take back and apply. 

Here are examples of topics that have been selected in past shows for this track:

• Team Development for the Future with Agentic AI & GitHub

• Branches That Don't Suck: Smarter Strategies for Modern Dev Teams

• Secure AI Engineering and DevOps for .NET Developers on Azure

• Mastering AI Development & Building AI Apps with GitHub Copilot

• Visual Studio Tips & Tricks

• Improving Performance in .NET Applications

Programming Languages and Fundamentals    

The Programming Languages and Fundamentals track focuses on languages and the runtimes that support them. We want talks on C# and the newest language features, the .NET runtime and how it actually executes your code, the base class libraries and the NuGet ecosystem, and any language or runtime in and around the Microsoft ecosphere, including VB, F#, Python, TypeScript, and JavaScript.

We are especially looking for sessions that build durable skills rather than chase a single release: asynchronous programming and threading, memory management, spans and allocation-free code, generics and type system depth, source generators and reflection, interop and native AOT, algorithms and data structures, testable and idiomatic code, and profiling and benchmarking to know whether a change actually helped. Language comparisons and "X for Y developers" talks are welcome, as are fundamentals sessions that give newer developers a solid foundation and give experienced developers a clearer mental model of what the runtime is doing underneath.

Here are examples of topics that have been selected in past shows for this track:

• What’s New in C#

• What’s New in .NET

• Advanced Threading in .NET

• TypeScript for C# Developers

Artificial Intelligence Live!

Foundation Models, Multimodal AI & Model Engineering

Foundation models are evolving rapidly, offering developers new capabilities, architectures, and deployment options. This track explores how to select, customize, evaluate, optimize, and integrate language and multimodal models into real-world applications. From frontier models and open-weight alternatives to small language models and specialized AI systems, sessions should emphasize practical engineering decisions, implementation techniques, and measurable trade-offs.

Topics in This Track

• Foundation model selection, benchmarking, and evaluation for enterprise applications

• Frontier models, open-weight models, and small language models (SLMs)

• Working with models through Microsoft Foundry and Azure AI services

• Building multimodal applications using text, images, audio, video, and documents

• Real-time voice AI, speech-to-speech applications, and conversational interfaces

• Fine-tuning and model adaptation using LoRA, adapters, and other techniques

• Model optimization, quantization, distillation, and inference acceleration

• Local and self-hosted AI using Ollama, ONNX Runtime, vLLM, and related technologies

• Structured outputs, constrained generation, and reliable model integration

• Model routing, fallback strategies, and multi-model application architectures

• Token optimization, inference performance, latency, and cost management

• Deploying models across Azure, containers, edge devices, and hybrid environments

• Comparing proprietary, open-weight, and specialized models for real-world workloads

AI Agents, Copilots & Intelligent Automation

AI agents are moving beyond simple chat interfaces to become active participants in software applications and business workflows. This track focuses on building intelligent, tool-using systems that can reason, retrieve information, execute tasks, coordinate workflows, and interact with enterprise services. Sessions should demonstrate working agent architectures, practical orchestration techniques, and the engineering challenges involved in making autonomous systems reliable and secure.

Topics in This Track

• Building AI agents using Microsoft Agent Framework

• Developing and deploying agents with Microsoft Foundry Agent Service

• Agent architecture patterns: single-agent, multi-agent, and workflow-based systems

• Tool calling, function calling, and integration with enterprise APIs

• Model Context Protocol (MCP): building and consuming tools and servers

• Agent-to-Agent (A2A) communication and interoperability

• Agent orchestration, delegation, coordination, and state management

• Agent memory, context engineering, and long-running workflows

• Building enterprise copilots using Microsoft 365 Copilot extensibility

• Copilot Studio: custom agents, connectors, actions, and orchestration

• Developing AI-powered workflows using Power Automate, Dataverse, and Microsoft services

• Human-in-the-loop approvals, checkpoints, and exception handling

• Agent identity, permissions, authorization, and secure tool execution

• Debugging agent behavior, tool failures, and orchestration issues

• Practical agent implementations for IT operations, software development, customer support, and enterprise workflows

• Moving from agent prototypes to dependable, production-ready systems

RAG, Enterprise Data & AI Grounding

Enterprise AI applications are only as useful as the information they can reliably access. This track explores the architectures, data pipelines, retrieval techniques, and semantic technologies needed to connect AI applications and agents to trusted enterprise knowledge. Sessions should focus on building accurate, secure, scalable grounding systems that go beyond basic vector search and work with real enterprise data.

Topics in This Track

• Building production-ready Retrieval-Augmented Generation (RAG) applications

• Advanced RAG architectures: hybrid, adaptive, agentic, and graph-based retrieval

• Azure AI Search for vector, hybrid, and semantic retrieval

• Microsoft Foundry IQ and enterprise knowledge integration

• Microsoft Fabric IQ, semantic models, and enterprise ontologies

• Embeddings, chunking strategies, document processing, and indexing pipelines

• Knowledge graphs, GraphRAG, and relationship-aware retrieval

• Connecting AI applications to SQL Server, Azure SQL, Cosmos DB, and PostgreSQL

• Vector search and hybrid retrieval using Microsoft data platforms

• Building AI applications using SQL and existing enterprise data

• Microsoft Fabric data agents and natural-language access to enterprise analytics

• Integrating structured, unstructured, and real-time data into AI applications

• Context engineering, prompt construction, and grounding strategies

• RAG evaluation: retrieval quality, relevance, factual accuracy, and citation verification

• Data permissions, access controls, privacy, and secure enterprise retrieval

• Improving retrieval performance, reducing latency, and controlling costs

• Designing agent-ready data architectures and semantic layers

AI Application Development, Architecture & Integration

Building successful AI applications requires more than connecting an LLM to an API. Developers must combine traditional software engineering practices with new AI patterns, frameworks, and application architectures. This track focuses on practical, code-first development of AI-powered applications using .NET, C#, Python, Azure, and the Microsoft developer ecosystem.

Topics in This Track

• Building AI-powered applications with .NET, C#, and Python

• Integrating AI into ASP.NET Core, Blazor, and existing enterprise applications

• Developing AI solutions using Microsoft Foundry SDKs and APIs

• Using Microsoft Agent Framework in real-world application architectures

• Designing AI-native applications and modernizing existing software with AI capabilities

• AI application architecture patterns, design decisions, and trade-offs

• Building AI-enabled APIs, microservices, and cloud-native applications

• Integrating AI with Azure Functions, Logic Apps, Event Grid, and messaging services

• Streaming responses, asynchronous processing, and real-time AI experiences

• Building conversational interfaces and AI-powered user experiences

• State management, conversation persistence, and context handling

• Structured outputs, validation, error handling, and application reliability

• Developing with GitHub Copilot and AI-assisted software engineering workflows

• Testing, debugging, and maintaining nondeterministic AI application behavior

• Using Visual Studio, VS Code, GitHub, and Azure developer tools for AI development

• Containerizing and deploying AI applications using Azure Container Apps, AKS, and related services

• Practical architectures for scaling AI applications from prototype to production

Production AI Engineering, Evaluation, Security & Operations

Moving AI from a successful demonstration into production introduces challenges that traditional software development practices alone cannot solve. This track covers the engineering discipline required to make AI applications and agents reliable, secure, observable, scalable, and cost-effective. Sessions should demonstrate practical approaches to evaluating AI behavior, managing operational risk, and running AI systems in enterprise environments.

Topics in This Track

• Production AI architecture, deployment strategies, and operational readiness

• AI evaluation frameworks, automated testing, and quality measurement

• Evaluating agent behavior, tool use, task completion, and end-to-end workflows

• LLMOps and AgentOps: operational practices for AI applications and agents

• AI observability: tracing, telemetry, logging, and debugging

• Monitoring with Azure Monitor, Application Insights, and OpenTelemetry

• Building evaluation pipelines and continuous quality improvement workflows

• CI/CD and DevOps practices for AI-powered applications

• Prompt, model, agent, and configuration versioning

• Regression testing, red teaming, and failure analysis

• AI security: prompt injection, data exfiltration, tool misuse, and model abuse

• Identity, authentication, authorization, and least-privilege access for AI agents

• Securing AI applications using Microsoft Entra and Azure security services

• Responsible AI, governance, compliance, and enterprise guardrails

• Managing token usage, infrastructure costs, rate limits, and resource consumption

• Reliability engineering: retries, fallbacks, circuit breakers, and graceful degradation

• Model deployment, monitoring, rollback, and lifecycle management

• Real-world production lessons, architectural failures, and operational best practices

Submission Guidelines

Please include the following information with your submission (failure to supply all requested information may limit opportunities for selection):

• Speaker's Name
• Speaker's Title
• Speaker's Company
• Title of Presentation
• 100-word Description of Presentation
• 3-5 Bullets, explaining what the attendee will learn from presentation (learning objectives)
• Speaker's Color Photo (hi-resolution)
• Speaker's Bio, including previous conference speaking/presentation experience

Speakers chosen to present at a Visual Studio Live! & Artificial Intelligence Live!  conference will receive a stipend for each session they present. Visual Studio Live! & Artificial Intelligence Live! Conferences will also cover hotel accommodations (room and tax only) for a pre-determined number of nights at the host hotel as outlined in the speaker agreement. Speakers are responsible for their own travel costs and incidentals.

We look forward to your submissions.

~ The Visual Studio Live! & Artificial Intelligence Live! Event Team

Speakers chosen to present at Visual Studio Live! & Artificial Intelligence Live! @ Microsoft HQ 2027 will receive a stipend for each session they present. The conference will also cover hotel accommodations (room and tax only) for a pre-determined number of nights at the host hotel as outlined in the speaker agreement. Speakers are responsible for their own travel costs and incidentals.