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Introduction

What is AI Platform Engineering​

As Platform Engineering, SRE and DevOps environments grow in complexity, traditional approaches often lead to delays, increased operational overhead, and developer frustration. By adopting Multi-Agentic Systems and Agentic AI, Platform Engineering teams can move from manual, task-driven processes to more adaptive and automated operations, better supporting development and business goals.

Intro

AI Platform Engineering project provides a customizable, secure, enterprise-ready, and cloud deployable reference multi-agent system that streamlines platform operations through persona-driven “usecase agents” such as Platform Engineer, Incident Engineer, and Product Owner etc. Each usecase agent is empowered by a set of specialized sub-agents that integrate seamlessly with essential engineering tools. Below are some common platform agents leveraged by the persona agents:

  • 🚀 ArgoCD Agent for continuous deployment
  • 🚨 PagerDuty Agent for incident management
  • 🐙 GitHub Agent for version control
  • 🗂️ Jira Agent for project management
  • 💬 Slack Agent for team communication

...and many more platform agents are available for additional tools and use cases.

Together, these sub-agents enable users to perform complex operations using agentic workflows by invoking relavant APIs using MCP tools. The system also includes:

  • A curated prompt library: A carefully evaluated collection of prompts designed for high accuracy and optimal workflow performance in multi-agent systems. These prompts guide persona agents (such as "Platform Engineer" or "Incident Engineer") using standardized instructions and questions, ensuring effective collaboration, incident response, platform operations, and knowledge sharing.
  • Multiple End-user interfaces: Easily invoke agentic workflows programmatically using standard A2A protocol or through intuitive UIs, enabling seamless integration with existing systems like Backstage (Internal Developer Portals).
  • End-to-end security: Secure agentic communication and task execution across all agents, ensuring API RBACs to meet enterprise requirements.
  • Enterprise-ready cloud deployment architecture: Reference deployment patterns for scalable, secure, and resilient multi-agent systems in cloud and hybrid environments

Goals of the project​

  • Enable Platform Engineering teams with a curated, validated set of persona-specific multi-agent systems (MAS) tailored to their unique enterprise requirements.

  • Foster an ecosystem of AI Platform Engineering practitioners to collaboratively develop high-quality, reusable prompt engineering libraries and commonly used platform tools.

  • A carefully curated library of meta-prompts, continuously evaluated for effectiveness with both our agents and the MCP server to drive optimal performance in agentic workflows.

Who we are​

We are Platform Engineers, SREs, and Developers from a variety of companies in the CNCF and CNOE.io ecosystems, passionate about open source and advancing the use of agentic AI in Platform Engineering.