Motif: Discovering and Automating Personal Web Workflows
Recent advances in LLMs and existing work on programming by demonstration have made it possible for end users to create automations by explicitly demonstrating their behavior to LLMs. However, these approaches rely on the assumption that users know what to automate and what is capable of being automated. Additionally, automation via LLM agents is often expensive compared with programs. We introduce Motif, a system that passively observes everyday browser activity to discover recurring interaction patterns that are programmable, makes recommendations to users whenever a pattern is discovered and generate a program to install after user confirmation. Users can review, and refine the program...
| Authors | Shaokang Jiang, Daye Nam |
|---|---|
| Primary category | cs.HC |
| Published | 12 July 2026 |
| Last updated at source | 12 July 2026 |
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