The future of B2B marketing is not SEO; it's being the default recommendation when a user asks an AI agent for a solution. Software buyers will increasingly trust an agent's direct answer over traditional discovery channels, making it critical for vendors to win this new point of discovery.

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.

When a need for website heat mapping arose, the AI agent researched options, selected Microsoft Clarity because it was free and had a good API, and guided the implementation. The entire discovery, evaluation, and procurement process occurred without human vendor research, bypassing traditional B2B sales entirely.

Generative Engine Optimization (GEO) isn't just about appearing in AI search results. Investor Jason Lemkin argues the real prize is becoming the default tool an agent selects when asked a direct question like, "What's the best CRM for me?" This shift from discovery to direct recommendation is the new competitive landscape for software vendors.

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.

The evolution of search won't stop with LLMs. The next stage involves autonomous AI agents that complete tasks like booking travel on a user's behalf. Marketers must shift their focus from answering human queries to ensuring their products and services are discoverable and selectable by these agents.

AI agents interact with software exclusively through APIs, bypassing the UI. This means a product with a dated front-end can become highly valuable and competitive in the agentic era if it exposes a robust, modern, and well-documented API layer that agents can leverage.

When AI agents are connected to legacy software like Marketo, they hit API limits and performance issues. The agents themselves then effectively recommend leaving that vendor for more modern platforms, becoming a driving force in tech stack decisions.

The team describes rarely using the native user interfaces of their SaaS tools (Notion, Posthog, etc.). Instead, they orchestrate these tools through a central AI model like Codex. This indicates the primary value of modern SaaS is shifting from its UI to how effectively it can be controlled by AI agents via APIs and MCPs.