Agent Workflow Memory (AWM) induces common sub-routine workflows from agent experiences and integrates them into agent memory. It operates in two modes: offline, where workflows are induced from ground-truth annotated examples, and online, where workflows are learned from past experiences on the fly without auxiliary data. The framework is evaluated on WebArena and Mind2Web benchmarks, demonstrating improved agent generalization in web navigation tasks.