Compiling agent tasks into code upfront—rather than deciding actions one step at a time—enables parallelization and validation, dramatically reducing latency and errors in web automation.
This paper introduces a compilation approach for web agents that converts natural language tasks into executable code plans instead of executing step-by-step. By generating multiple candidate plans, validating them against tool specifications, and optimizing for parallelization, the system achieves 10x faster execution and better accuracy than existing sequential approaches.