A developer's experiment with ThoughtDAG, a context graph tool for LLMs, found that removing a single edge from the graph changed the model's answer, and that a scoring artifact—where outputs hit the …
ThoughtDAG, an open-source, local-first workspace by developer chenxiachan, lets users control LLM context by wiring nodes so only upstream nodes are serialized into the next model request. The author…
ThoughtDAG, a Show HN project by developer Xia Chen, introduces a graph-based interface that makes LLM context editable, replacing chat with a canvas where edges define the message sequence sent to th…
Xia Chen, a postdoctoral fellow at the Munich Data Science Institute and Georg Nemetschek Institute at the Technical University of Munich, released ThoughtDAG v0.3.13 on August 14, 2026, an open-sourc…
ThoughtDAG, an editable context graph for LLM conversations, launched as a Show HN project with a web demo and desktop app, allowing users to branch, edit, and inspect the context sent to language mod…
Developer chenxiachan has built ThoughtDAG, an open-source tool that visualizes AI conversation context as a graph on an infinite canvas, and now introduces a visible, side-by-side context compaction …
A developer built ThoughtDAG, a prototype that replaces the standard scrollable LLM chat history with a directed acyclic graph (DAG) on an infinite canvas, making context fully editable. Each Q&A exch…
A developer built ThoughtDAG, an open-source prototype that represents LLM conversations as a directed acyclic graph where edges determine which upstream nodes are included in the model's context. The…
ThoughtDAG, an open-source tool that turns LLM conversations into editable thought graphs, launched with no install or signup required. The project, hosted on GitHub, lets users wire nodes to control …