RL Nabors

This talk explores the significant costs associated with using large, frontier AI models and proposes a strategy for migrating to smaller, more efficient, on-device models. The core thesis is that by right-sizing models for specific tasks, developers can drastically reduce expenses, improve user experience through lower latency, and enhance security and privacy, all while maintaining or even improving performance for many applications.

This talk introduces WebMCP, a system that enables agents to interact with web content directly within the browser. It explores how existing browser primitives can be leveraged to transform websites into interactive canvases for AI agents, moving beyond simple chat interfaces to richer, embedded experiences. The core idea is to make web content accessible and actionable for agents, similar to how humans navigate and interact with websites.