Recall replaces ad-hoc agent memory approaches — full chat logs, vector indexes, or manually re-injected summaries — with a structured, self-updating graph that agents on multiple model families adopted autonomously without explicit prompting, removing the need to repeatedly re-inform agents of updated facts or resolved problems.