Really liked the framing of Sources → Wiki pages → Rules, and especially the idea of reading an index first to avoid token waste. One thing I keep running into with these systems is that the bottleneck moves from “making notes” to “remembering to revisit the right page at the right time.” Curious if you’ve tried any kind of proactive resurfacing (e.g., daily prompts that pull 3 relevant notes into your workflow) and what heuristics worked best.
Juan, the bottleneck you named is the real one, and we'd reframe the fix. Daily resurfacing is a time-based push, and time-based pushes become the notifications everyone learns to swipe away. What has held up for us is task-triggered retrieval: the agent pulls the relevant page at the moment you start the work, not on a schedule, and your index-first read is already the seed of that, because an index lets the agent judge relevance per task. The heuristic that worked for us is to resurface on the trigger of the task in front of you, so the note appears when it's actually relevant.
The split you're describing (your setup for synthesis, the producer's for pipeline/inbox management) is basically the same divide I see in every AI-native team I've studied: one layer for turning raw input into knowledge, another for turning knowledge into repeatable output. Most people only build the first one and wonder why insights never make it into shipped work. Curious if you've tried connecting the two, like triggering content drafts directly from the wiki pages once they hit a certain link density?
Great setup. If you ever want a ready-made version, I open-sourced mine: https://github.com/eugeniughelbur/obsidian-second-brain on GitHub, 3.4k stars, 45 commands, works across Claude Code, Codex and Gemini. I'm the author, happy to answer questions.
The Reflect command feels like the most important part of this system because it delays synthesis until the person has given the thought more shape.
One question I keep running into in a similar experiment is authorship: once Claude starts creating summaries, pages, and connections, how do you distinguish the person’s meaning from the model’s interpretation?
I’ve found human review of extracted fragments essential. I’m also experimenting with reconstructing connections when needed rather than storing every inferred link permanently. Do you preserve any provenance boundary between your own words and Claude’s inferred connections?
And have you imagined this kind of environment becoming collaborative, with another person bringing their own notes, meanings, and perhaps even their own AI into a shared space?
Really liked the framing of Sources → Wiki pages → Rules, and especially the idea of reading an index first to avoid token waste. One thing I keep running into with these systems is that the bottleneck moves from “making notes” to “remembering to revisit the right page at the right time.” Curious if you’ve tried any kind of proactive resurfacing (e.g., daily prompts that pull 3 relevant notes into your workflow) and what heuristics worked best.
Juan, the bottleneck you named is the real one, and we'd reframe the fix. Daily resurfacing is a time-based push, and time-based pushes become the notifications everyone learns to swipe away. What has held up for us is task-triggered retrieval: the agent pulls the relevant page at the moment you start the work, not on a schedule, and your index-first read is already the seed of that, because an index lets the agent judge relevance per task. The heuristic that worked for us is to resurface on the trigger of the task in front of you, so the note appears when it's actually relevant.
The split you're describing (your setup for synthesis, the producer's for pipeline/inbox management) is basically the same divide I see in every AI-native team I've studied: one layer for turning raw input into knowledge, another for turning knowledge into repeatable output. Most people only build the first one and wonder why insights never make it into shipped work. Curious if you've tried connecting the two, like triggering content drafts directly from the wiki pages once they hit a certain link density?
Great setup. If you ever want a ready-made version, I open-sourced mine: https://github.com/eugeniughelbur/obsidian-second-brain on GitHub, 3.4k stars, 45 commands, works across Claude Code, Codex and Gemini. I'm the author, happy to answer questions.
The Reflect command feels like the most important part of this system because it delays synthesis until the person has given the thought more shape.
One question I keep running into in a similar experiment is authorship: once Claude starts creating summaries, pages, and connections, how do you distinguish the person’s meaning from the model’s interpretation?
I’ve found human review of extracted fragments essential. I’m also experimenting with reconstructing connections when needed rather than storing every inferred link permanently. Do you preserve any provenance boundary between your own words and Claude’s inferred connections?
And have you imagined this kind of environment becoming collaborative, with another person bringing their own notes, meanings, and perhaps even their own AI into a shared space?