Stories
Post-its cluster. Stories cross-link.
This is what makes the library think like human memory does.
A story is where the dots get joined. Many post-its from many files, gathered around one casefile. Many casefiles, gathered into one narrative on top.
L4 — A story per casefile
Many post-its, one woven narrative.
A casefile collects all the post-its tied to one thing — an engagement, a vessel, a person, a project. The story-builder weaves those post-its into a single readable story.md on disk. It’s rewritten as new post-its arrive — not appended.
How the dots get joined
A story — anatomy
story.md lives in the casefile folder. The DB stores a hash.L5 — One final story on top
”Where are we right now?”
The final story weaves every active casefile’s story into one calm narrative. It is rewritten daily — or whenever something major lands. When an agent wakes up, the final story is loaded first. That is how an agent knows the state of everything before it answers a single question.
Each casefile
has its own story.md. Updated as new post-its arrive.
Daily routine
A higher-quality model reads every active story.
One narrative
Stories woven into final-story.md. The top of the stack.
Cold-start inject
Every agent reads the final story on its way in.
Ready to work
The agent already knows the state of the office. No human briefing needed.
Why this is closer to human memory
Humans do not recall facts as isolated rows. We recall stories. A name reminds us of a place, which reminds us of a meeting, which reminds us of a decision. Many things, thought of together, cross-linked.
A pile of vector embeddings cannot do that. Stories can. The library is built to think the way the brain does.
Every claim resolves to a raw byte
If the final story makes a statement, you can walk down the chain until you reach the original byte.
No floating facts. No invented citations. Every claim has a thread back to a real file.