AI changed what a product is

Products used to have edges. You drew a box, positioned what was inside, priced it, sold it. The entire go-to-market stack—positioning, competitive analysis, pricing, sales enablement—assumes a bounded thing.

AI agents, MCP, and composability protocols broke that assumption. An agent discovers your API and wires it into workflows you never imagined. Your product becomes one node in a chain that didn’t exist yesterday. Surface area is emergent, not shipped. Defined at runtime by the agent, not your product team.

The GTM consequences are everywhere. You can’t position a moving target. Your competitor isn’t just your category. It’s anything in the agent’s toolkit that approximates your function.

Subscription and per-seat pricing assume human purchasing decisions, but agent-mediated usage is bursty and autonomous. Your sales motion now has two buyers: the human with budget and the developer or agent choosing tools. And your analytics show what the agent does, not what the human values, making product-market fit harder to read.

Old moats erode fast when agents swap tools per-call with no loyalty. Features, brand, switching costs. None of them hold. Data quality, reliability, and composability depth do. Trust does too, but who evaluates trust when the buyer is an LLM is an open problem.

Your API surface is your product now. Position on trust and reliability, not features. Rethink pricing for autonomous usage. And pay attention to who controls the curation layer. Tool registries, agent defaults, discovery protocols. That’s where distribution lives next.