i have some ideas for agent brains It's about knowledge graphs. let me brainstorm let's get some clarity on what we need:
an inbox
several automations digesting new input
first of all there are several input channels
there is the feed channel
then there are just notes i create and put into an input-folder
the most important element of the system is signal awareness
on discord i could set the priority (signal-strength) via text msg or reactions
my md-files have a stars-parameter in the frontmatter
another important design choice would be to label ai-generated information where possible to avoid self-pollution For now I would like to curate myself what I allow to enter into the second brain, but I can see a future where would observe my interactions to some degree and add important info by its own
#Second Brain
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I’d model this as a pipeline with a pretty hard boundary between capture, triage, and memory write.
Rough shape:
-
Inbox layer
Everything lands here first: Discord feed messages, manual notes, files in an input folder, links, transcripts, screenshots, whatever. Nothing from the inbox should be treated as trusted memory yet. -
Triage layer
This is where signal awareness lives. Normalize all sources into the same fields, something like:
source: discord | note | file | web | manual
created_at:
author:
signal_strength: 0-5
human_curated: true | false
ai_generated: true | false
status: inbox | candidate | accepted | rejected | archived
tags: []
Discord reactions/text priority and Markdown stars can both map into signal_strength. That gives you one scoring model instead of source-specific logic everywhere.
- Quarantine for AI-generated content
I think you’re right to worry about self-pollution. I’d make AI-generated notes second-class until explicitly accepted. The agent can summarize, cluster, and propose links, but the durable graph should distinguish:
- human-authored fact
- human-approved AI summary
- unapproved AI inference
- observed behavior / weak signal
- Graph write layer