#432 · Primary category: Education & Research

learn-agentic-ai

a2a agentic-ai dapr dapr-pub-sub dapr-service-invocation dapr-sidecar dapr-workflow docker kafka kubernetes langmem mcp openai openai-agents-sdk openai-api postgresql-database rabbitmq rancher-desktop redis serverless-containers

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.

Project last updated:10/26/25

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4.4K

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1.0K

Contributors

16

License

MIT

Why we included this project

This is a structured curriculum for developers who want agentic AI systems that survive contact with production, not just demo chains that work once in a notebook. Built around the DACA design pattern, it walks through how the agent-native stack fits together: OpenAI Agents SDK, MCP, A2A, memory, knowledge graphs, Dapr, and Kubernetes. The material comes from the Panaversity agentic AI engineering program, so concepts come with hands-on exercises and real attention to integration practices and safety guardrails, the parts that usually sink a pilot. Teams that have watched capable models fail to show measurable business results will recognize the problems it addresses. For architects and engineers adopting cloud-native agent infrastructure, it reads like a practical route from first principles to scale.

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