An API is no longer enough; it must be optimized for AI agents. This means enabling high-volume calls and structured outputs that AI can easily consume. New agentic products will be built on the most accommodating platforms, leaving others behind.

Historically, software was built for predictable human workflows. Now, with AI agents executing thousands of unpredictable, low-latency queries simultaneously, product design must prioritize their needs. These agents will eventually select their own infrastructure, fundamentally changing the B2B buying process.

AI agents are becoming the dominant source of internet traffic, shifting the paradigm from human-centric UI to agent-friendly APIs. Developers optimizing for human users may be designing for a shrinking minority, as automated systems increasingly consume web services.

The paradigm of software development is shifting. Srini Raghavan argues that products must now be built for two types of users: humans and AI agents. This requires creating interfaces, like CLIs and APIs, specifically designed for AI consumption through technologies like MCPs.

AI agents bypass traditional user onboarding, immediately push software to its limits, and even request missing API functionality. This requires a fundamental shift in product development, focusing on robust, agent-friendly infrastructure rather than just human-centric UIs.

The number of AI agents will soon vastly exceed human employees. This requires a fundamental shift in software development, prioritizing API-first design, reliability, and machine-to-machine interaction over traditional human-centric user interfaces.

The user of developer infrastructure is no longer just a human engineer but also AI agents and coding assistants. Stripe has seen LLM traffic to its documentation grow 10x year-over-year, signaling a fundamental shift toward building products and documentation for machine-to-machine interaction.

A new, critical metric for evaluating software is how 'agent-friendly' its API is. This goes beyond traditional developer documentation and ease of use. It focuses on factors like rate limiting, security, and structure that are crucial for building reliable, autonomous AI agents on top of the platform.

As AI agents increasingly perform tasks on behalf of humans, they will interact with software via APIs, not UIs. To stay relevant, SaaS platforms must adopt a 'headless' (API-first) architecture that allows agents to programmatically sign up, configure, and use their services without human intervention.