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AI Agents: Concepts and Your First Implementation
AI Agents: Concepts and Your First Implementation
What AI agents actually are, how they differ from chatbots, and a hands-on walkthrough to build your first working agent with Microsoft Agent Framework in under 30 minutes.
Prompt Engineering for AI Agents -- Grounding, Roles, and YAML Configuration
Prompt Engineering for AI Agents -- Grounding, Roles, and YAML Configuration
How to write agent prompts that prevent hallucination, adapt to user roles, and stay maintainable -- with YAML-based configuration you can version-control.
Building Domain-Specific Tools -- Giving Agents Real Capabilities
Building Domain-Specific Tools -- Giving Agents Real Capabilities
How to build production-quality agent tools that query databases, validate business rules, and automatically scope data to the current user.
Multi-Agent Architecture: Orchestration and the A2A Protocol
Multi-Agent Architecture: Orchestration and the A2A Protocol
How to build an orchestrator that routes requests to specialist agents, and the A2A protocol that makes agent-to-agent communication standardized, secure, and framework-independent.
Observability -- Tracing Multi-Agent Workflows with OpenTelemetry
Observability -- Tracing Multi-Agent Workflows with OpenTelemetry
How to instrument multi-agent systems with OpenTelemetry -- auto-instrumented traces across agents, LLM calls, and database queries, visualized in .NET Aspire Dashboard.
Frontend: Rich Cards and Streaming Responses
Frontend: Rich Cards and Streaming Responses
Transform agent text responses into interactive product cards and order cards, then add token-by-token streaming via SSE so the UI feels instant -- all without changing the backend agents.
Production Readiness: Auth, RBAC, and Deployment
Production Readiness: Auth, RBAC, and Deployment
JWT authentication, role-based access control, user-scoped data isolation for a multi-agent system, then Docker Compose architecture with a one-command startup for all 11 services.
Agent Memory -- Remembering Across Conversations
Agent Memory -- Remembering Across Conversations
Give your agents persistent memory -- store user preferences, recall past interactions, and personalize responses across conversations.
Evaluating Agent Quality -- Testing What You Cannot Unit Test
Evaluating Agent Quality -- Testing What You Cannot Unit Test
Build a repeatable evaluation pipeline for multi-agent correctness -- golden datasets, automated scoring, and CI/CD integration.