How to Design APIs for an AI World 🔌
A thorough analysis of how AI changes what is needed from a good API, with real-world examples + some speculations about the future.
As engineers, we've been building applications for different audiences throughout the decades.
At first, we only built for humans — creating visual interfaces, buttons, and forms. Then came the APIs, and we started building for humans and other software — predictable systems talking to each other through well-defined contracts.
Now it feels like we are entering a third era, where a relevant consumer is neither human nor traditional software. It's AI.
And here is the thing: AI agents don't behave like either of their predecessors. On one side, AI looks like regular software: LLM calls are fundamentally API calls, and our basic mental models about load, latency, and cost, still apply.
On the other side, AI brings a degree of understanding and… chaos that, in many respects, makes them closer to how humans do things. They can:
Figure out when (and to some degree, how) to use tools by themselves.
Make sense of unstructured data — they don’t need strict syntax (e.g. JSON) to work.
Make unpredictable mistakes and are inherently non-deterministic.
It is obvious that to get the most value out of AI, we need to ensure it can interact with the rest of our tech stack. Advancements like MCP have driven progress, but it’s also clear that simply piping LLMs to APIs in the same ways we always have won’t get us the most value out of this collaboration. We need to rethink how we approach API design with a new consumer in mind: one that is neither software nor human. Because, in a way, AI agents are both.
While we are firmly in the realm of speculation here, I believe we have been working with AI for long enough to be able to set some coordinates that are unlikely to change, and consider what AI-first APIs may look like.
To help me with this, I am also bringing in none other than Ankit Sobti, co-founder and CTO of Postman. Postman is the world’s leading API platform, and Ankit has been working at the forefront of this space for more than 10 years.
So here is what we will cover today:
✨ Thriving in ambiguity — an unprecedented reality for software systems.
🤖 Designing APIs for AI — exploring AI's unique quirks and how to use them for good.
🔌 MCP — the current state of AI-first API protocols.
🔮 Beyond APIs — preparing for an agent-to-agent future.
Let's dive in!
