Original Summary

I use AI conversations to work through research questions, but useful decisions end up scattered across sessions. I wanted to bring those decisions into a new question without bringing the whole old conversation with them. I'm building ThoughtDAG, an open-source conversation canvas. You can branch a discussion and choose which paths feed the next answer. Wires are context. This update adds Jev as an optional fast selection step: the history index finds candidate excerpts, Jev ranks what's relevant, and your usual LLM develops the answer. With recall enabled, you can inspect the sources and exclude individual items. An old idea can be useful without becoming a permanent instruction. The short animation shows the workflow. The index is stored locally; using Jev sends candidate content to its remote API. Source and setup: https://github.com/chenxiachan/thoughtdag When you revisit old AI conversations, what do you usually need back: a decision, the evidence behind it, or an approach you already ruled out?   submitted by   /u/Lopsided_Scarcity979 [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/27 04:13:30