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Learn Agentic AI patterns and agent-native cloud technologies step by step.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "learn-agentic-ai" yet — see the docs or source repo.
Create a 4-week learning plan for Agentic AI, the DACA design pattern, OpenAI Agents SDK, MCP, A2A, Knowledge Graphs, Dapr, and Kubernetes. Organize it by weekly themes, hands-on tasks, and recommended order.
A structured learning roadmap with topics, hands-on steps, and a recommended sequence.
Explain in simple terms how OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, and Kubernetes relate to each other, and describe their roles in an Agentic AI system.
A clear conceptual explanation showing each component’s role and how they work together.
Design a beginner-friendly hands-on project that uses Dapr, OpenAI Agents SDK, and MCP to build a simple Agentic AI application. Include the project goal, architecture, implementation steps, and acceptance criteria.
An actionable practice project plan for learning by building a working prototype.
Use AI agents to create interactive block-based courses for faster learning.
Get read-only guidance on agent design patterns and architecture choices.
Enable AI agents to read, write, and evolve memory across apps.
Learn to design and apply AI skills in real agent systems.
Generate structured AI agent learning paths, projects, and deployment guidance.
Explore a trilingual agentic AI roadmap with projects and hands-on practice.