Perplexity Details Brain Memory Architecture and Agent API Testing

Perplexity on November 2, 2026, published a technical guide to persistent AI agent memory, detailing the Brain system in Perplexity Computer, the Agent API’s memory-building components, and tests for whether stored context improves an agent’s later work.

Brain’s Architecture and Reported Results

Perplexity describes Brain as its self-improving memory system for Computer, built to organize past work and corrections into an evolving knowledge wiki. It uses token-level memory, meaning information is stored outside the model and read into context when needed. Changing a wiki page alters what the agent can read on a later task without modifying the model’s learned weights.

Brain stores these records as files in the agent’s sandbox across three layers. The sessions/ directory retains raw transcripts and their summaries, notes/ organizes distilled information by subject, and knowledge/ contains the wiki’s linked Markdown pages about people, projects and concepts. The guide classifies session records as episodic memory and the wiki as semantic memory; Skills and saved instructions provide procedural memory for how tasks should be performed.

Background agents called Dream process each day’s session records overnight, produce summaries and revise the wiki when information has changed. Perplexity says it checks staged edits before they are committed through Git, leaving a diff available for inspection. Each memory entry links back to its…