Mehta expects long-running AI agents to find a clearer business model in the enterprise

Apoorva Mehta said his new company is building long-running agents that continuously seek information and improve their results over time while using less cost and time. He compared an agent’s accumulation of context to onboarding an employee: as the employee gains context and completes more projects, performance improves. In his account, hardware can be one way to provide an agent with more context.

Mehta expects such agents to appear in consumer products too, but thinks their commercial value will become clearer sooner in enterprise settings: companies are willing to pay for faster and better information when it gives them a competitive advantage. He said it is not yet clear how to make consumer AI services sustainably profitable and predicted that this problem would be solved over the next few years. For now, he considers enterprise applications more compelling.