StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework

TL;DR

StorySage is a multi-agent conversational system that helps users craft personal autobiographies by capturing memories over multiple sessions, improving narrative coherence and user satisfaction.

Contribution

It introduces a novel multi-agent framework for flexible, user-driven autobiography writing, advancing beyond generic conversational assistants.

Findings

Demonstrates effective multi-session memory collection

Improves narrative completeness and flow

Increases user satisfaction in autobiographical writing

Abstract

Every individual carries a unique and personal life story shaped by their memories and experiences. However, these memories are often scattered and difficult to organize into a coherent narrative, a challenge that defines the task of autobiography writing. Existing conversational writing assistants tend to rely on generic user interactions and pre-defined guidelines, making it difficult for these systems to capture personal memories and develop a complete biography over time. We introduce StorySage, a user-driven software system designed to meet the needs of a diverse group of users that supports a flexible conversation and a structured approach to autobiography writing. Powered by a multi-agent framework composed of an Interviewer, Session Scribe, Planner, Section Writer, and Session Coordinator, our system iteratively collects user memories, updates their autobiography, and plans for future conversations. In experimental simulations, StorySage demonstrates its ability to navigate multiple sessions and capture user memories across many conversations. User studies (N=28) highlight how StorySage maintains improved conversational flow, narrative completeness, and higher user satisfaction when compared to a baseline. In summary, StorySage contributes both a novel architecture for autobiography writing and insights into how multi-agent systems can enhance human-AI creative partnerships.