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Everyday use cases

You do not need to understand vector search or database internals to understand why FactLane exists.

The basic problem is simple: an AI assistant is more useful when it can reuse important facts from earlier work, but old memory should not silently become the final authority over what is true now.

FactLane does not replace your assistant. It sits behind a compatible AI-agent app or host as its local memory layer. Once connected, the everyday experience can stay much simpler than the technical setup.

Remember my preferences between sessions​

Imagine telling an assistant:

Keep answers concise, explain in Arabic, and preserve English technical terms.

That preference may be useful next week or in another session. FactLane can store it as a bounded fact rather than requiring the assistant to replay the old conversation.

The important boundary is that a newer instruction still wins. If you later say:

Go deep on this one.

FactLane memory does not have the authority to override your current request.

Remember the important facts about my project​

You may repeatedly need an assistant to know things such as:

  • the product goal;
  • the current supported release;
  • an architectural decision;
  • the repository or project scope;
  • an agreed workflow rule.

Instead of pasting a long project history into every session, a compatible host can retrieve eligible FactLane facts for the exact project scope.

Facts that can become stale still need freshness and verification discipline. “Current release is v0.1.3” is not the same kind of memory as “I prefer concise answers.”

Remember how I like recurring work handled​

FactLane can represent durable workflow facts such as:

Production changes require owner approval.

or:

Run local tests before preparing a review.

The exact authority of the connected agent still comes from the host configuration and current instructions. A memory describing a rule is supporting state; it is not a mechanism for granting new execution permissions.

Reuse approved facts across more than one agent host​

More than one compatible local agent host can use the same governed FactLane store when the operator configures them against that environment.

This lets the hosts reuse facts instead of sharing entire transcripts.

The hosts do not gain identical authority merely because they see the same tools. Launcher profiles and trusted context determine what each connection may do.

Let an assistant propose a useful memory without trusting it immediately​

An ordinary delegated agent can be allowed to contribute a Candidate:

This looks worth remembering.

That is deliberately different from:

This is verified Current truth.

A separate trusted verification operation is required to promote an eligible Candidate. The agent cannot self-promote by putting a privileged identity claim into its request.

Read Core concepts for the Candidate → Current lifecycle.

Keep memory inside the right boundary​

FactLane does not treat memory as one giant bucket. A fact can belong to a user, one exact project, one workflow inside a project, one tool/agent environment, or a narrowly defined workflow rule that is deliberately allowed to cross projects.

For example, a fact about one project should not implicitly fan out into another project merely because the same assistant is connected.

See Core concepts for the plain-language scope model and Architecture for the exact identity rules.

Next: check fit before setup​

If these examples match the problem you are trying to solve, use the FAQ as the decision checkpoint. It covers fit, non-goals, where data lives, and what the current technical setup requires.

One boundary is worth knowing now: v0.1.3 still needs someone to install FactLane and configure a compatible local host. If that is acceptable, continue with the FAQ, then Core concepts.