chatchan

7 ms·

1. 1.▲
   ThoughtDAG can now turn local coding-agent sessions into editable context graphs(github.com)

   3 points by chatchan 14d ago|1 comments
2. 2.▲
   by chatchan 14d ago

   After releasing ThoughtDAG in August, the most significant feedback was that while editable context graphs were interesting, people didn't want to migrate their existing work to a separate application. This prompted me to create Sessio
3. 3.▲
   by chatchan 29d ago

   Thanks man! Any feedback is appreciated!
4. 4.▲
   by chatchan 29d ago

   Thanks for sharing, I agree with you. I also had the same struggle with bidirectional integration. I think it makes a distinction here. Because I don't want to create "another" coding agent cli here. The core of my idea is to
5. 5.▲
   by chatchan 1mo ago

   Thanks, oh I see, Cypher acts as a context selector. ThoughtDAG addresses the same issue but uses a visual approach: it searches for nodes first, then uses connections or references to determine which content enters the request. I'd lo
6. 6.▲
   by chatchan 1mo ago

   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 can ask your CLI to access it and get the
7. 7.▲
   by chatchan 1mo ago

   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 ... menu, you can manage your highlights a
8. 8.▲
   by chatchan 1mo ago

   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 and then automatically generate queries?
9. 9.▲
   by chatchan 1mo ago

   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 order; alternatively, automatic refresh
10. 10.▲
    by chatchan 1mo ago

    That sounds interesting. Could you share the arxiv papers? I would love to check them
11. 11.▲
    by chatchan 1mo ago

    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 the question. Or edit the answer by clicki
12. 12.▲
    by chatchan 1mo ago

    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 reasoning, but still leaving traces of ex
13. 13.▲
    by chatchan 1mo ago

    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 context of the incoming request and allowi
14. 14.▲
    by chatchan 1mo ago

    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 :)
15. 15.▲
    by chatchan 1mo ago

    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 interaction methods because the functio
16. 16.▲
    by chatchan 1mo ago

    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, promotional slogans, and unnecessary entry p
17. 17.▲
    by chatchan 1mo ago

    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 thread; understanding it before decidin
18. 18.▲
    by chatchan 1mo ago

    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's collapsed by default and doesn'
19. 19.▲
    by chatchan 1mo ago

    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 packages have been rebuilt. I also agre
20. 20.▲
    by chatchan 1mo ago

    Thank you!
21. 21.▲
    by chatchan 1mo ago

    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 also create, branch, and prune nodes?
22. 22.▲
    by chatchan 1mo ago

    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. Thinking of this as user-directed compa
23. 23.▲
    by chatchan 1mo ago

    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 or plugin boundary that I have not built
24. 24.▲
    by chatchan 1mo ago

    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, restricts browser origins, and forces the
25. 25.▲
    by chatchan 1mo ago

    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 conversation trees. Many workflow canvases also us
26. 26.▲
    by chatchan 1mo ago

    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, and branches do not have to resolve int
27. 27.▲
    by chatchan 1mo ago

    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 node count alone is not a good measure o
28. 28.▲
    by chatchan 1mo ago

    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 an edge, regenerate, and that branch lea
29. 29.▲
    Show HN: ThoughtDAG – An editable context graph for LLM conversations(chenxiachan.github.io)

    136 points by chatchan 1mo ago|63 comments
30. 30.▲
    I built a canvas where LLM chats become an editable map(github.com)

    3 points by chatchan 2mo ago|0 comments