When users access SaaS tools through their own AI environments like Codex, they use their own AI model tokens, not the SaaS vendor's. This eliminates a huge cost center for SaaS companies, shifting their business model toward making their apps agent-friendly rather than paying for AI features.

Initial AI market skepticism was based on a SaaS model of selling limited-value subscriptions ('seats'). The new reality is a utility model based on consumption ('tokens'). In an agentic era, a single user can drive thousands of dollars in token usage, creating a virtually uncapped revenue stream that justifies massive infrastructure investment.

As more companies integrate AI, their costs are tied to variable usage (e.g., tokens, inference). This is causing a profound, economy-wide transformation away from predictable seat-based subscriptions towards more dynamic usage-based models to align costs with revenue.

Historically, a developer's primary cost was salary. Now, the constant use of powerful AI coding assistants creates a new, variable infrastructure expense for LLM tokens. This changes the economic model of software development, with costs per engineer potentially rising by dollars per hour.

AI development isn't free; it shifts the economic model of software from zero marginal cost to one with variable costs based on token consumption. This makes Cost of Goods Sold (COGS) a critical, and often new, metric for SaaS founders.

Public markets are incorrectly rewarding SaaS companies for "revenue reacceleration" that comes from reselling LLM tokens. This is flawed because token resale has drastically lower margins than traditional SaaS and creates data silos. The more sustainable model is providing value via new consumption-based APIs for agents.

The traditional per-seat SaaS model is becoming a "tax on productivity" in an agent-driven world. As companies buy agents to do work instead of software for humans, the model shifts. Sam Altman's comment that every company is now an API company reflects this move from user-based pricing to value-based, programmatic access.

A major opportunity exists for SaaS built to be used within AI environments like Codex. This allows users to leverage their personal agent's deep context and shifts expensive token costs from the provider to the end-user, improving margins.

The AI industry has spent trillions on development. The next phase requires proving ROI, which means selling tokens at scale. This will force AI companies to partner with established enterprise players like Salesforce who own the C-suite relationships needed to distribute their products.