As AI agents increasingly perform tasks on behalf of users, marketing focus will shift from attracting human website visitors to ensuring your product is the agent's "default choice." This means making products accessible via APIs and open-sourcing tools, becoming a trusted data source for automated systems.

The traditional SaaS model of bundling data, logic, and UI is being challenged. To stay relevant, SaaS companies must unbundle their core assets—like semantic models and business logic—so they can be consumed by AI agents, not just humans via a UI. This creates new agent-driven usage and business models.

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.

The rise of AI means product development is shifting from a UI-centric model to a programmatic-first approach. As agents become the primary "users," the focus moves to APIs and other machine-to-machine interfaces. The traditional graphical user interface is becoming a secondary concern, mainly for human oversight.

The internet's primary user is shifting from humans to AI agents, creating a new "machine-to-machine" economy. This presents an opportunity to create agent-native versions of every major SaaS category, from payments and communication (like Notion or Slack) to memory and project management, built specifically for non-human customers.

Participating in AI commerce isn't just about capturing inbound data. Brands must structure and provide outbound data feeds of their inventory and product details in a format that LLMs can readily access for recommendations and transactions. This represents a significant new technical requirement for marketing teams.

The nascent AI agent ecosystem lacks effective discovery mechanisms for third-party tools ('skills'). This creates an opportunity for curated marketplaces that help users find, vet, and even pay for high-quality, trustworthy agent capabilities, solving a key bottleneck to adoption.

The speaker predicts a hybrid pricing model for AI. A flat subscription fee, like a Costco membership, will grant platform access. However, computationally intensive tasks will be paid for via a credit system, akin to buying products in-store. This solves the problem of offering "unlimited" plans for a variable-cost service.

Soon, AI agents will make purchasing decisions for humans, creating a new economy that will dwarf human traffic. Businesses must shift from optimizing a "pixel-perfect" UI for humans to a "bits-perfect" platform for agents, focusing on API clarity, data structure, and overcoming agent biases.