Use cases

An agent that remembers a project decision

A coding agent’s useful memory is a decision made while working, stored when it happens, and still there after the process is gone. This is that, with no transcript mining afterwards.

Write it when it happens

The context is a label, not a schema. The cue has to share a token with the text, because no embedder is involved. The second process is a new interpreter opening the same directory after checkpoint() returned.

First process. Run.

from fluctlightdb import connect_embedded

brain = connect_embedded("./coding-agent")
brain.experience(
    "The API worker owns transaction boundaries",
    context="decision:api",
    salience=0.8,
)
brain.checkpoint()

Second process, same directory. Run.

from fluctlightdb import connect_embedded

brain = connect_embedded("./coding-agent")
hit = brain.activate("transaction boundaries")["recalls"][0]
print(hit["episode"]["content"])

Printed

The API worker owns transaction boundaries

One directory per agent

Handing this directory to every worker is the failure the paper measures. Give each agent its own path, or pass agent_id on the calls. The limit, in the project’s words:

Stated limit

When many agents share one brain, provenance separation reaches only 18% top-1. Per-case isolation reaches 100%, which is a ceiling rather than multi-tenant readiness. Unaddressed in code. Source: papers/arxiv-v1/main.tex:668-675. Opens the repository in a new tab.