#432 · Primary category: Education & Research
learn-agentic-ai
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
GitHub Stars
4.4K
Forks
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.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
JavaGuide
Java Interview & Backend General Interview Guide, covering computer fundamentals, databases, distributed systems, high concurrency, system design, and AI application development.
system-prompts-and-models-of-ai-tools
A curated collection of system prompts, internal tools, and AI models from popular AI assistants and coding agents.
30-seconds-of-code
Coding articles to level up your development skills
generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI