# Introduction SmartSnap is a major breakthrough in the search for solutions for autonomous agents. The technology, developed by Meta, focuses on creating agents that can proactively and scalably verify their own performance. ## How SmartSnap Works SmartSnap uses an innovative approach to enable autonomous agents to verify their performance. The idea is that the agent creates a series of evidence snapshots, which are then evaluated by a large language model (LLM) to determine their validity and relevance. ## Principles of Self-Verifying Agent The Self-Verifying Agent is designed with two primary missions: completing a task and verifying its own performance through curated evidence snapshots. The agent uses its online access to perform verification in situ, without requiring external verification from a human. ## Experiments and Results Experiments conducted on mobile tasks across various model families have demonstrated that SmartSnap enables LLM-driven agents to be trained in a scalable manner, achieving improvements of 26.08% and 16.66% respectively for large models.