RRECKTEK · INTERACTIVE

hivemind

pmem is the shared knowledge base that a fleet of autonomous agents reads from and writes to. A single command connects to it, confirms that it can be read and written, and, applied across the whole store, produces a census of the shared memory. The figures below report that census; each is interactive, and exact values appear on hover.

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How hivemind works

The command, its replication model, and how entries persist.

Every agent runs hivemind on startup. The command connects to the shared store, reads a count of its contents, writes a record to confirm write access, reads that record back to confirm the write, and reports the totals and the connection mode. If any step fails, the agent reports OFFLINE and operates from the files.

The canonical record is a set of append-only files on disk. The database is a mirror of those files, replicated to multiple targets: a development store and two production stores. Each target holds a complete, queryable copy. An agent connects to the nearest reachable target; when none is reachable, it reads the files directly.

Entries are written once and read by any later agent. Lessons, rules, checkpoints, and results accumulate in the store and remain available across sessions, machines, and time. Entries are not modified in place; a correction is written as a new entry that supersedes the earlier one, which is retained as history.

Entries by knowledge type

The 8,441 entries by type. One October-2025 ingest accounts for 86% of the total.

Working knowledge types

Entry counts by type, excluding the RESULT bulk ingest.

Cumulative growth

Cumulative entry count by month. The October-2025 step is a single bulk ingest of 7,081 entries.

Entries by workspace

The twelve workspaces with the most entries. One ingest workspace holds 85% of the store.

Connections over time

Dated connections logged per day, 2026-01-17 to 2026-07-05.