Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loop
Although information workers may complain about meetings, they are an essential part of their work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides fast, efficient scheduling through structured workflows. Users interact with the system via email, delegating their scheduling needs to the system as if it were a human personal assistant. Common scheduling scenarios are broken down using well-defined workflows and completed as a series of microtasks that are automated when possible and executed by a human otherwise. Unusual scenarios fall back to a trained human assistant who executes them as unstructured macrotasks. We describe the iterative approach we used to develop Calendar.help, and share the lessons learned from scheduling thousands of meetings during a year of real-world deployments. Our findings provide insight into how complex information tasks can be broken down into repeatable components that can be executed efficiently to improve productivity.
Code (0)
등록된 구현이 없습니다.
Tasks
SchedulingSimilar Papers 제목 키워드 기반
CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs
Personal AI assistants are beginning to act as delegates with access to calendars, inboxes, and user preferences. Calendar scheduling makes the trust problem concrete: an assistant must coordinate with other assistants w…
Learning User Preferences and Understanding Calendar Contexts for Event Scheduling
With online calendar services gaining popularity worldwide, calendar data has become one of the richest context sources for understanding human behavior. However, event scheduling is still time-consuming even with the de…
SchedulingAgentic AI Home Energy Management System: A Large Language Model Framework for Residential Load Scheduling
The electricity sector transition requires substantial increases in residential demand response capacity, yet Home Energy Management Systems (HEMS) adoption remains limited by user interaction barriers requiring translat…
Prompt EngineeringPEARL: Self-Evolving Assistant for Time Management with Reinforcement Learning
Overlapping calendar invitations force busy professionals to repeatedly decide which meetings to attend, reschedule, or decline. We refer to this preference-driven decision process as calendar conflict resolution. Automa…
Reinforcement LearningSolving Parallel Machine Scheduling With Precedences and Cumulative Resource Constraints With Calendars
The task of finding efficient production schedules for parallel machines is a challenge that arises in most industrial manufacturing domains. There is a large potential to minimize production costs through automated sche…