How can Agentic AI contribute in middleware technologies (API Gateway, Service Bus and Event brokers) mainly in integration automations, observability, and security?

Agentic AI contributes to middleware by enabling both AI for code and code for AI. On one side, AI for code helps automate integration logic, generating APIs, transformations, and event flows with minimal human input and increases the productivity of middleware (or infrastructure software) developers. On the other, code for AI ensures that APIs, integrations, and event brokers can operationalize AI by exposing models, chaining agents, and enforcing policies around them. This duality turns middleware into an execution layer where AI is not just used to write the code but becomes part of the code runtime, optimizing automation, observability, and security continuously and contextually. APIs, integrations, and IAM provide the foundation for adopting AI in the enterprise by reusing existing data, systems, and personnel. 

Utilize the best patterns and practices in designing the solutions. Finally, generate the boilerplate code, test cases, and fake test data.