What Makes an API Tool AI-Native?

As AI applications increasingly depend on inference APIs, I’m wondering what should actually make an API development tool “AI-native.”

For me, it goes beyond sending requests. I’d expect: Easy testing across multiple model endpoints

OpenAPI support for evolving schemas

Automated API testing and validation

Mocking for AI/inference services

Documentation that stays connected to the API

Collaboration across developers and ML teams

I’ve been looking at Apidog because it brings API design, testing, documentation, mocking, and collaboration into one workflow.

For people building with Hugging Face Inference APIs or other LLM services, what would you consider essential in an AI-native Postman alternative?