learn-agentic-ai
A hands-on tutorial repo for building Agentic AI applications with the DACA pattern and technologies like OpenAI Agents SDK, Dapr, and Kubernetes.
Tool overview
This repository is a tutorial for building Agentic AI applications using the Dapr Agentic Cloud Ascent (DACA) design pattern. It covers technologies such as OpenAI Agents SDK, memory, MCP, A2A, knowledge graphs, Dapr, Rancher Desktop, and Kubernetes. Strengths include a cohesive learning path that combines agent logic with cloud-native infrastructure, and it is free to study. However, the project is very new (only 8 stars) with limited documentation, and the complex stack requires substantial prior knowledge of containers, AI SDKs, and orchestration. It suits intermediate developers looking to explore agentic patterns hands-on, but it is not a production-ready reference. Running the examples locally may demand a capable machine, and costs may arise from cloud AI APIs if used beyond local models.