Overview
A single AI agent may be less accurate or less capable than an experienced human for a particular task. It may also perform worse on a one-shot attempt. Its major advantage is speed and reproducibility. Multiple instances can be launched at the same time, each trying a different path or working on a different target.
This changes the economics of problem solving. One agent can process one website. Ten agents can process ten websites in parallel. One agent can propose one group of ideas. Ten agents can explore ten variations. One agent can implement a solution while another independently reviews it.
Parallelization can compensate for imperfect one-shot accuracy. Instead of assuming that one response must be correct, the system can generate several attempts, compare them, select recurring conclusions, identify outliers, and use a fresh reviewer to catch errors.
The most advanced patterns in this module are variations on this principle. Agents can divide execution work, search a larger solution space, debate one another, operate separate browsers, or inspect one another's outputs.