What's NewΒΆ
Track the latest labs, content updates, and improvements to the AI Agents Learning Hub.
β¨ This page is auto-generated from the git history on every deploy.
March 2026ΒΆ
π New Labs AddedΒΆ
| Lab | Title | Level | Path |
|---|---|---|---|
| Lab 001 | What are AI Agents? | L50 | All paths |
| Lab 002 | AI Agent Landscape 2025 | L50 | All paths |
| Lab 003 | Choosing the Right Tool | L50 | All paths |
| Lab 004 | How LLMs Work | L50 | All paths |
| Lab 005 | Prompt Engineering | L50 | All paths |
| Lab 006 | What is RAG? | L50 | π RAG |
| Lab 007 | What are Embeddings? | L50 | π RAG |
| Lab 008 | Responsible AI for Agent Builders | L50 | All paths |
| Lab 009 | Azure OpenAI Service Quickstart | L100 | π Microsoft Foundry |
| Lab 010 | GitHub Copilot β First Steps | L100 | π€ GitHub Copilot |
| Lab 011 | Copilot Studio β First Agent | L100 | Agent Builder β Teams |
| Lab 012 | What is MCP? Anatomy of the Protocol | L100 | π MCP |
| Lab 013 | GitHub Models β Free LLM Inference | L100 | π€ GitHub Copilot |
| Lab 014 | Semantic Kernel β Hello Agent | L100 | π§ Semantic Kernel |
| Lab 015 | Ollama β Run LLMs Locally for Free | L100 | All paths |
| Lab 016 | GitHub Copilot Agent Mode | L100 | π€ GitHub Copilot |
| Lab 017 | Structured Output & JSON Mode | L100 | All paths |
| Lab 018 | Function Calling & Tool Use | L100 | βοΈ Pro Code Agents |
| Lab 019 | Streaming Responses in Agents | L100 | βοΈ Pro Code Agents |
| Lab 020 | Build an MCP Server in Python | L200 | π MCP |
| Lab 021 | Build an MCP Server in C# | L200 | MCP |
| Lab 022 | RAG Pipeline with GitHub Models + pgvector | L200 | RAG |
| Lab 023 | Semantic Kernel β Plugins, Memory & Planners | L200 | Semantic Kernel |
| Lab 024 | Teams AI Library Bot | L200 | Agent Builder β Teams |
| Lab 025 | VS Code Copilot Chat Participant | L200 | Agent Builder β VS Code |
| Lab 026 | Agentic RAG Pattern | L200 | RAG |
| Lab 027 | Agent Memory Patterns | L200 | Pro Code |
| Lab 028 | Deploy MCP Server to Azure Container Apps | L300 | MCP |
| Lab 029 | LangChain & LangGraph Basics | L200 | π» Pro Code |
| Lab 030 | Microsoft Foundry Agent Service + MCP | L300 | Foundry + MCP |
| Lab 031 | pgvector Semantic Search on Azure | L300 | RAG |
| Lab 032 | Row Level Security for Agents | L300 | Foundry + Security |
| Lab 033 | Agent Observability with Application Insights | L300 | Microsoft Foundry |
| Lab 034 | Multi-Agent Orchestration with Semantic Kernel | L300 | Semantic Kernel |
| Lab 035 | Agent Evaluation with Azure AI Eval SDK | L300 | Pro Code |
| Lab 036 | Prompt Injection Defense & Agent Security | L300 | Pro Code |
| Lab 037 | CI/CD for AI Agents with GitHub Actions | L300 | Pro Code |
| Lab 038 | AI Cost Optimization | L300 | π» Pro Code |
| Lab 039 | Vector Database Comparison | L300 | π RAG |
| Lab 040 | Production Multi-Agent with AutoGen | L400 | Pro Code Agents |
| Lab 041 | Custom GitHub Copilot Extension | L400 | GitHub Copilot |
| Lab 042 | Enterprise RAG with Evaluations | L400 | RAG |
| Lab 043 | Multimodal Agents with GPT-4o Vision | L300 | π» Pro Code |
| Lab 044 | Phi-4 + Ollama in Production | L400 | Pro Code |
| Lab 045 | GitHub Copilot Workspace | L200 | π€ GitHub Copilot |
| Lab 046 | Microsoft Agent 365 β Enterprise Agent Governance | L300 | βοΈ Pro Code |
| Lab 047 | Work IQ β Copilot Adoption Analytics | L200 | All paths |
| Lab 048 | Work IQ β Copilot Impact Analytics & Power BI | L300 | All paths |
| Lab 049 | Foundry IQ β Agent Tracing with OpenTelemetry | L300 | π Microsoft Foundry |
| Lab 050 | Multi-Agent Observability with GenAI Semantic Conventions | L400 | π Microsoft Foundry |
| Lab 051 | Fabric IQ β Real-Time Intelligence Agents | L300 | All paths |
| Lab 052 | Fabric IQ β Conversational Data Agent (NL β SQL) | L200 | β |
| Lab 053 | Fabric IQ β Batch AI Enrichment with AI Functions | L300 | All paths |
| Lab 054 | A2A Protocol β Build Interoperable Multi-Agent Systems | L200 | All paths |
| Lab 055 | A2A + MCP Full Stack β Agent Interoperability Capstone | L400 | βοΈ Pro Code |
| Lab 056 | Federated M365 Copilot Connectors with MCP | L300 | All paths |
| Lab 057 | Computer-Using Agents β Desktop Automation | L300 | βοΈ Pro Code |
| Lab 058 | Browser Automation Agents with OpenAI CUA | L300 | βοΈ Pro Code |
| Lab 059 | Voice Agents with GPT Realtime API | L200 | All paths |
| Lab 060 | Reasoning Models β Chain-of-Thought with o3 and DeepSeek R1 | L200 | All paths |
| Lab 061 | SLMs β Phi-4 Mini for Low-Cost Agent Skills | L200 | All paths |
| Lab 062 | On-Device Agents with Phi Silica β Windows AI APIs | L300 | All paths |
| Lab 063 | Agent Identity β Entra OBO Flow & Least Privilege | L300 | All paths |
| Lab 064 | Securing MCP at Scale with Azure API Management | L400 | βοΈ Pro Code |
| Lab 065 | Purview DSPM for AI β Govern Agent Data Flows | L300 | All paths |
| Lab 066 | Copilot Studio Enterprise Governance | L300 | All paths |
| Lab 067 | GraphRAG β Knowledge Graphs for Cross-Document Retrieval | L300 | All paths |
| Lab 068 | Hybrid Search β Vector + BM25 + Semantic Ranker | L200 | All paths |
| Lab 069 | Declarative Agents for Microsoft 365 Copilot | L100 | All paths |
| Lab 070 | Agent UX Patterns β Chat, Adaptive Cards & Proactive Notifications | L100 | All paths |
| Lab 071 | Context Caching β Cutting Costs for Large-Document Agents | L300 | All paths |
| Lab 072 | Structured Outputs β Guaranteed JSON for Agents | L100 | All paths |
| Lab 073 | Agent Benchmarking with SWE-bench | L300 | All paths |
| Lab 074 | Foundry Agent Service β Production Multi-Agent Deployment | L300 | π Microsoft Foundry |
| Lab 075 | Power BI Copilot β Autonomous Analytics & Data Storytelling | L100 | All paths |
| Lab 076 | Microsoft Agent Framework β From SK to MAF | L200 | All paths |
| Lab 077 | AG-UI Protocol β Connect Agents to User Interfaces | L200 | All paths |
| Lab 078 | Foundry Local β Run AI Models Offline | L100 | All paths |
| Lab 079 | Deep Research Agents β Multi-Step Knowledge Synthesis | L300 | All paths |
| Lab 080 | MarkItDown + MCP β Document Ingestion for Agents | L200 | All paths |
| Lab 081 | Agentic Coding Tools β Claude Code vs Copilot CLI | L100 | All paths |
| Lab 082 | Agent Guardrails β NeMo & Azure Content Safety | L300 | All paths |
| Lab 083 | Multi-Modal RAG β Images, Tables & Charts in Documents | L300 | All paths |
| Lab 084 | Capstone β Build the Complete OutdoorGear Agent | L400 | All paths |
π¦ Sample DatasetsΒΆ
All labs share a consistent OutdoorGear Inc. scenario with ready-to-use datasets:
| File | Contents |
|---|---|
data/products.csv |
25 outdoor gear products with categories, prices, specs |
data/knowledge-base.json |
42 RAG-ready documents: policies, FAQs, product guides |
data/orders.csv |
20 sample customer orders for RLS and order tracking labs |
ποΈ Infrastructure TemplatesΒΆ
Deploy-to-Azure one-click buttons for three Bicep templates:
| Template | What it deploys |
|---|---|
infra/lab-028-mcp-container-apps/ |
Azure Container Apps + ACR for MCP servers |
infra/lab-030-foundry/ |
Azure AI Foundry + Storage + AI Services |
infra/lab-031-pgvector/ |
Azure PostgreSQL Flexible Server with pgvector |
πΊοΈ RoadmapΒΆ
All 75 labs have been published! Want to contribute a new lab or suggest improvements?
See CONTRIBUTING.md or open a proposal.