Well-Architected Framework For Agentic AI

Authors: Sudhir Kumar Kakumanu, Mukesh Shukla, Srushti Anil Patil

Abstract: AI agents are changing how enterprises solve problems. While traditional AI models addressed specific tasks like classification or prediction, AI agents offer goal-driven, autonomous capabilities—sensing, reasoning, planning, and acting. These data-driven autonomous systems depend on high-quality, well-governed data to reason, ground decisions, and deliver reliable outcomes. However, deploying AI agents in complex enterprise environments is difficult. This paper presents the Well-Architected Framework (WAF) for AI Agents and an executable WAF Auditor Agent. The framework defines nine pillars—spanning data foundation, security, governance, and beyond—from Agent Complexity to Sustainability, while the Auditor Agent turns these guidelines into an automated assessment workflow. This allows organizations to evaluate architectural designs and receive recommendations before and during development, providing a clear path to production readiness.

DOI: http://doi.org/10.5281/zenodo.21715658