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The API is the Product

TL;DR >> AI agents can't click buttons. Every feature must be accessible via HTTP APIs, expressed in user-domain language rather than infrastructure concepts. The UI is optional. The API is essential. <<

We’re building products for a future where AI agents are the primary users. Not humans clicking buttons—agents making HTTP requests.

# The UI is Optional

AI agents can’t click “Advanced Settings” buttons. They can’t navigate multi-step wizards. They can’t interpret hover tooltips. If your product only works through a web interface, you’ve already lost the agentic future.

Every feature must be accessible via HTTP APIs. If there’s a capability that exists only in the UI, that’s not a feature—that’s a leak in your platform abstraction.

# Speak User, Not Infrastructure

Most platforms get this wrong: their APIs echo internal architecture. You see endpoints named after database tables, concepts borrowed from microservice boundaries, workflows that mirror internal implementation details.

An agent doesn’t care about your service mesh or your sharding strategy. It cares about resources it can manipulate, workflows it can trigger, and limits it can query. The API should be a clean abstraction layer that hides implementation complexity while exposing complete functionality.

# UI for Clarity, Not Completeness

The UI still matters—for visualization, onboarding, moments when a human needs to understand what’s happening. But the UI is no longer the primary interface, and not the complete interface.

When something fails, the UI shouldn’t echo the API error. It should explain why it failed in human terms, surfacing context that an agent infers but a human needs spelled out. The UI becomes a teacher, not just a controller.

# The Agentic Litmus Test

Can a reasonably intelligent AI agent discover and use every feature your product offers without ever opening a browser?

If not, you have work to do. The API is the product now. Everything else is just a pretty face.

Building go-to-market engines for AI-driven products with purpose. Worked with innovative startups like Numarics, Codeanywhere, Daytona, and Steel on growth strategies and market positioning. Faculty at University of Split, researching AI adoption patterns and developer tools.