What you'll learn

Modern GenAI applications often become tightly coupled to individual AI providers, making them difficult to evolve, migrate, and govern as APIs, models, and interoperability standards rapidly change. In this course, Ensuring Interoperability in GenAI Systems, you'll gain the ability to design interoperable, provider-agnostic GenAI applications that remain maintainable, portable, and compliant throughout their lifecycle. First, you'll explore how to build standardized AI integrations using common API patterns, provider abstractions, and secure communication mechanisms. Next, you'll discover strategies for managing API evolution through versioning, feature management, and emerging interoperability standards such as Model Context Protocol (MCP) and Agent-to-Agent (A2A). Finally, you'll learn how to apply governance, compliance, auditability, and enterprise best practices to interoperable GenAI system designs. When you're finished with this course, you'll have the skills and knowledge of GenAI interoperability needed to build enterprise AI applications that can evolve confidently across providers, technologies, and regulatory requirements.