ChatGraPhT: A Visual Conversation Interface for Multi-Path Reflection with Agentic LLM Support

Geoff Kimm; Linus Tan

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arXiv · 2512.22790

ChatGraPhT: A Visual Conversation Interface for Multi-Path Reflection with Agentic LLM Support

Geoff Kimm·Linus Tan

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Abstract

Large Language Models (LLMs) are increasingly used in complex knowledge work, yet linear transcript interfaces limit support for reflection. Schon's Reflective Practice distinguishes between reflection-in-action (during a task) and reflection-on-action (after a task), both benefiting from non-linear, revisitable representations of dialogue. ChatGraPhT is an interactive tool that shows dialogue as a visual map, allowing users to branch and merge ideas, edit past messages, and receive guidance that prompts deeper reflection. It supports non-linear, multi-path dialogue, while two agentic LLM assistants provide moment-to-moment and higher-level guidance. Our inquiry suggests that keeping the conversation structure visible, allowing branching and merging, and suggesting patterns or ways to combine ideas deepened user reflective engagement. Contributions are: (1) the design of a node-link, agentic LLM interface for reflective dialogue, and (2) transferable design knowledge on balancing structure and AI support to sustain reflection in complex, open-ended tasks.

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Geoff Kimm, Linus Tan. 2025-12-28. ChatGraPhT: A Visual Conversation Interface for Multi-Path Reflection with Agentic LLM Support. https://arxiv.org/abs/2512.22790

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