Bits

Multi-agent design patterns — when to use them, building blocks of agent communication and coordination, Group Chat / Hand-off / Collaborative Filtering patterns, and a WorkflowBuilder pipeline walkthrough.

How to build planning agents that decompose complex goals into structured subtasks, route work to specialized agents, and iteratively re-plan based on real-world feedback.

How to build safe and trustworthy AI agents — system message framework, threat mitigation, and human-in-the-loop patterns for secure, reliable agentic systems.

2 + 2 = 5

Agentic RAG — how LLMs autonomously decide when and how to retrieve information, iterate with a maker-checker loop, self-correct, and deliver high-quality grounded responses.

How AI agents use tools via function calling — building blocks, tool schemas, approval modes, and practical examples with Microsoft Agent Framework and Azure AI Agent Service.

A guide to Agentic Design Principles (Space, Time, Core) and three practical patterns — Clear Instructions, Structured Output, and Single Responsibility — for building effective AI agents.

A comparison of Microsoft Agent Framework and Azure AI Agent Service — modular components, multi-agent collaboration, and when to use each for building production AI agents.

A breakdown of AI Agent core components (Environment, Sensors, LLM, Tools, Memory), 7 agent types, when to use agents, and a hands-on Python example with Azure AI Foundry.