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Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.

Subagents4.2k stars979 forksJupyter NotebookMITUpdated 7mo ago
Editor's note

Panaversity's learn-agentic-ai repository is a structured curriculum for the Certified Agentic and Robotic AI Engineer program, teaching developers how to build and deploy production-scale AI agent systems using the Dapr Agentic Cloud Ascent (DACA) design pattern. The course material, delivered primarily as Jupyter Notebooks, walks through the OpenAI Agents SDK, the Model Context Protocol (MCP) for standardized tool access, the Agent-to-Agent (A2A) protocol for inter-agent collaboration, LangMem for agent memory, and knowledge graphs for structured reasoning. Infrastructure topics cover Kubernetes orchestration, Dapr's actor and workflow primitives, Redis, PostgreSQL, RabbitMQ, Kafka, and Rancher Desktop for local cluster development. A concrete engineering focus throughout is architecting systems capable of handling 10 million concurrent agents, using Dapr's virtual actor model and Kubernetes horizontal pod autoscaling as the primary scaling mechanisms. Developers, cloud engineers, and students entering the agentic AI field are the primary audience.

ClaudeWave Trust Score
90/100
Verified
Passed
  • Open-source license (MIT)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Mature repo (>1y old)
  • Documented (README)
Flags
  • !Inactive (>180d)
Last scanned: 6/11/2026
Install as a Claude Code subagent
Method: Clone
Terminal
git clone https://github.com/panaversity/learn-agentic-ai && cp learn-agentic-ai/*.md ~/.claude/agents/
1. Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
2. Start a new Claude Code session to load the agents.
3. Delegate work to them with the Task/Agent tool or by name.
Use cases

Subagents overview

README preview not available. Visit the repo on GitHub for full documentation.
a2aagentic-aidaprdapr-pub-subdapr-service-invocationdapr-sidecardapr-workflowdockerkafkakuberneteslangmemmcpopenaiopenai-agents-sdkopenai-apipostgresql-databaserabbitmqrancher-desktopredisserverless-containers

What people ask about learn-agentic-ai

What is panaversity/learn-agentic-ai?

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panaversity/learn-agentic-ai is subagents for the Claude AI ecosystem. Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes. It has 4.2k GitHub stars and was last updated 7mo ago.

How do I install learn-agentic-ai?

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You can install learn-agentic-ai by cloning the repository (https://github.com/panaversity/learn-agentic-ai) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is panaversity/learn-agentic-ai safe to use?

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Our security agent has analyzed panaversity/learn-agentic-ai and assigned a Trust Score of 90/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains panaversity/learn-agentic-ai?

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panaversity/learn-agentic-ai is maintained by panaversity. The last recorded GitHub activity is from 7mo ago, with 59 open issues.

Are there alternatives to learn-agentic-ai?

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Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.

Deploy learn-agentic-ai to your cloud

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