Microsoft Developer Day 2026 at Work
Source: My personal notes from a developer day with Microsoft at work
Artificial Intelligence (AI) Technology Platform Design Concepts
Section titled “Artificial Intelligence (AI) Technology Platform Design Concepts”Service functionality
Section titled “Service functionality”- Managed infrastructure
- Configuration, less code
- Multiple clouds available (Azure, AWS, GCP)
- Secure
- Good defaults: selection of models
Interfaces for clients
Section titled “Interfaces for clients”- API access for all services
- Agent
- Catalogue with different task types like document generation and management, research, validation, forms, data queries
- Model Context Protocol (MCP) open standard for LLM to tool communication described in Develop AI agents on Azure - Agents in Azure AI Solutions
- Model connectors - vendor and open source models
- Model configuration, version controlled
- Data and Storage - vaults, repositories, cache, search
- Search, filtering
- Caching, response caching
- Retrieval Augmented Generation (RAG) - Retrieval Augmented Generation (RAG)
- Governance - security and administration
- Token quotas, content safety, security mitigation in place, identity, client secrets
- Security team
GitHub Copilot to Build a Full Stack Application
Section titled “GitHub Copilot to Build a Full Stack Application”See GitHub Copilot, Building a Full Stack Application - GitHub Copilot, Building a Full Stack Application
Azure Databricks and Fabric, Data Analytics and AI
Section titled “Azure Databricks and Fabric, Data Analytics and AI”Use case: Start with data, securely transform, structure, and share data for use. Enable data science work while preserving data ownership.
Platform options
Section titled “Platform options”Azure Databricks <– mirror functions –> Microsoft Fabric
Azure Databricks:
- Data Warehouse vs Data Lakehouse vs Data Lake - Data Warehouse vs Data Lakehouse vs Data Lake (OneLake)
- Data catalog, data models and governance (Unity Catalog (UC))
Microsoft Fabric:
- Data Factory - ETL, data transformations
- Analytics - Azure Synapse, Power BI
- Databases
- Governance - Purview
- AI - Copilot
Using the Platforms’ Tools
Section titled “Using the Platforms’ Tools”Use Case followed by Tool
- Data analysis with building agents - Use DataBricks, Fabric, Copilot Studio
- Analytics AI assistant - DataBricks AI/BI Genie
- Data access and application management - Azure AI Foundry
- Semantic models and ontology (defined relationships and definitions) to allow for reports and self service - Fabric IQ
Power Platform for Developers
Section titled “Power Platform for Developers”Overview of Microsoft Power Platform - Microsoft Power Platform for low code, vibe code, and pro code development of analytics, apps, workflows, agents, and AI.
Solution Development Cycle
Section titled “Solution Development Cycle”Demonstration: provide requirements within Power Apps vibe code interface to build app. Development is done in web interface. Could connect to SharePoint, Dataverse for data and files.
Integrate with VS Code Power Platform plugin to build and manage app.
In Azure DevOps, there are Power Platform pipelines where solution packages can be deployed to different environments.
- Artifact: Power Platform solution
- Task: Deployment to specified environment