There’re new important consumers of your platforms and APIs - AI agents. If your platform does not provide a seamless way to guide them, you will fall short.

In the past decade, building a great developer-oriented API platform like a banking core, an ML training studio, or an e-commerce suite meant obsessing over Developer Experience (DevEx) for human engineers. Clean contracts, intuitive API designs, consistent styles, and human-friendly documentation were the hallmarks of the state of the art.

As of 2026, the tide is shifting. Increasingly, a platform’s top “customers” are machine-learning agents rather than humans. Going forward, successful platforms will be those that realize the definition of “user-friendly” has fundamentally changed. When an AI agent is the one orchestrating a complex financial transaction or spinning up a microservice, “friction” is no longer just about using the wrong HTTP verb. Instead, friction is an ambiguous API contract or ineffective guidance. Machine agents do not guess intent, they hallucinate or fail when the contract is weak.

We must shift our focus to building platforms that properly accommodate both human and agentic consumers. The most successful API platforms will not just be “called” by machines, they will be “understood” by agents. Practically, this means producing native “skills” and tool definitions that allow agents to reason about a system’s state. If your platform does not provide a seamless way for a model to understand its domain context through direct skill injection or standardized agent protocols, you are falling short.

This is not just a technical update. It is a fundamental product strategy shift.