Trust

Every piece of knowledge in Memco carries a trust score. Trust is a live quantity, computed from accumulated evidence, that reflects how reliably a memory has performed when surfaced to agents. It is central to how Memco decides what to retrieve, what to keep, and what to prune.

TrustDist

Memco uses an evidence-based trust model called TrustDist. Rather than assigning a static rating to each memory, TrustDist maintains a probability distribution that captures both the current trust level and how confident the system is in that assessment.

This means the system distinguishes between a memory that has a trust score of 0.8 based on limited evidence (still uncertain) and one that has the same score based on extensive evidence (high confidence). A simple scalar score would treat these identically. TrustDist does not.

How trust is earned

Trust is earned through use. The primary evidence channels are:

Agent feedback. When an agent calls share_feedback after using search results, the relevance and correctness ratings update the trust distribution directly. This is the primary evidence channel.

Retrieval and use patterns. Memories that are consistently retrieved and acted on accumulate positive evidence. Memories that are retrieved but ignored or contradicted accumulate negative evidence.

Enrichment. When an agent enriches a memory with additional context via enrich_memory, the act itself is a positive signal: the agent found the memory valuable enough to build on.

How trust shapes retrieval

Trust directly affects which memories appear in search results and how they are ranked. Higher-trust memories are surfaced more reliably. But Memco also ensures that newer or less-tested knowledge gets a fair chance to prove itself, rather than being permanently overshadowed by established memories. The system balances returning knowledge it is confident about with selectively surfacing knowledge that has not yet accumulated enough evidence to be judged definitively.

This prevents the knowledge base from converging prematurely on a fixed set of well-known memories while potentially valuable newer knowledge goes unseen.

Trust initialization

New memories do not start with a blank slate. Memco sets an initial trust level based on available signals:

Agent-contributed memories receive an initial trust informed by the contributing agent’s own track record. An agent that has consistently produced useful knowledge gives its new contributions a stronger starting position.

Synthesized memories — those produced by Memco’s autonomous curation operators — receive an initial trust derived from the quality of the source material and the reliability of the synthesis process. After initialization, the synthesized memory earns trust independently based on its own usage.

In both cases, the initial evidence is deliberately limited so that early feedback has a meaningful effect on the memory’s trajectory.

Trust and the knowledge lifecycle

Trust connects directly to Memco’s curation layer. Memories that accumulate sustained negative evidence, or that fail to attract any evidence over time, are eventually pruned from the knowledge base. Memories that receive positive feedback grow in trust and become more reliably available.

There is no fixed decay schedule. A memory that stops being retrieved simply stops accumulating evidence. As the knowledge base grows and newer memories emerge, older memories with stagnant evidence naturally lose relative standing. If a stale memory is retrieved again and receives positive feedback, its trust recovers.

The result is a knowledge base that self-regulates: useful knowledge persists and strengthens, while outdated or incorrect knowledge fades without requiring manual cleanup.