chatchan

Yes. I agree. I've added a small section to the README in the Git repository to describe how it works alongside your coding agent. ThoughtDAG has automatic folder backups as a JSON file. So you c…

Thank you for your feedback! There is a way to delete a highlight. On the node side panel, there is a folded highlight section; you can manage your highlights there. Also, on your canvas, top-right ..…

Thanks! I'm not very familiar with Neo4j and Cypher yet. How do you control the context using Cypher? Do you manually write queries for each request, or do you select nodes through the interface …

Thank you for sharing! That did occur to me. ThoughtDAG now marks affected downstream answers as needing updates after an upstream node is modified, allowing users to rerun the algorithm in dependency…

That sounds interesting. Could you share the arxiv papers? I would love to check them

I agree. Most LLM tools (Claude Web, OpenAI, and their harness) offer re-editable questions. That is how I avoid such problems by myself. In ThoughtDAG, you can re-edit questions by double-clicking th…

The slime mold analogy is very accurate: research begins by exploring multiple directions, then gradually strengthens the path supported by evidence, stopping other branches from entering subsequent r…

I think we need to distinguish between "what the model received" and "why the model generated this answer." ThoughtDAG currently focuses on the former: accurately displaying the co…

If you're referring to the loom analogy, then it's quite similar: you choose which threads to weave into the next context; unwanted threads can be unraveled :)

Thank you for your suggestion. I've added a "How ThoughtDAG differs" section to the README. Rather than listing specific products one by one, I ultimately chose to compare them based on…

Thank you for pointing out this issue. The homepage did indeed use too many common landing page elements before actually showcasing the product. I redesigned the homepage, removing status labels, prom…

I read the discussion you linked. The Transformer and MLP examples you gave illustrate the learning process I hope ThoughtDAG can handle: entering a branch along a question without disrupting the main…

Thank you for carefully reviewing the repo and demo; this suggestion is very insightful. Currently, the node sidebar already has a context list grouped by material, reference, and dialogue, but it…

Thank you for taking the time to inspect this so carefully. You were right, and I treated it as an urgent security issue. The updated version fixed the mentioned problem. All macOS, Windows, and Linux…

Thank you!

Thank you for your feedback! Just want to know. What would be the smallest useful integration for you: allowing the host tool to read the currently selected context, or bidirectional access so it can …

Yes, that is exactly the failure mode I care about and drove me to develop ThoughtDAG! In ThoughtDAG, removing that edge excludes the detail from the next request without deleting the original branch.…

Not directly today. ThoughtDAG currently runs as a standalone local app. If you mean letting a Replit agent read selected graph context and write its results back as nodes, that would require an API o…

Thank you for taking the time to inspect this so carefully. You were right, and I treated it as an urgent security issue. The fix removes shell execution from PDF rendering, strictly validates dpi, re…

Yes, I have seen several adjacent approaches. Microsoft Huabu explores spatial interaction around research materials, while LLM Canvas and tldraw’s branching-chat experiments explore visual conversati…

I can see the Git analogy in branching, merging, and preserving provenance. But in use, I think it feels closer to a mind map or Miro than to version control. Thought does not need an explicit commit,…

I have not noticed a measurable slowdown in practice so far, including canvases with around a hundred nodes. A request only includes the wired ancestors of the current node, not the entire canvas, so …

Hi HN, I built ThoughtDAG around one rule: wires are the context. Each question and answer is a node. When you ask from a node, only its wired upstream nodes are included in the model request. Delete …