Memory & compaction
How agents keep long-term memory across runs without unbounded prompt growth, and how long meetings stay bounded.
A long-running org would blow up its prompt size — and its cost — if every agent carried its entire history verbatim. Quorum keeps context bounded in two places: per-agent memory, and meetings.
Agent memory
Each agent has a long-term memory file, agents/<id>/MEMORY.md, loaded into its
system prompt each turn. It’s how an agent remembers what it learned, decided,
or was granted across cycles and across restarts.
When the file grows past a threshold, older notes are summarized and recent ones kept verbatim — so prompt size and cost stay bounded no matter how long the org runs. The agent’s recent context stays sharp while its older history compresses into a running summary.
Memory is also where operator answers land: when you answer a request an agent raised, the reply is written into that agent’s memory (and inbox), so it actually receives the account, credential, or decision it asked for and uses it next turn. See Dashboard & steering.
Meeting compaction
Meetings are real multi-round debates. A long debate would similarly bloat context, so older turns roll into a summary as the meeting proceeds, keeping the working context bounded. The full transcript still goes to the minutes — nothing is lost to the record, only to the live prompt.
Speakers are also capped, so a large roster doesn’t run a super-linear all-hands.
Worklogs vs. shared content
Memory is per-agent and private to that agent’s directory. Two related things live elsewhere:
- Per-agent worklogs — what an agent did on a task — live under
agents/<id>/alongside its memory. - Shared work docs (decisions, knowledge) live in the org’s CMS under
workspace/cms/, and meeting minutes underworkspace/meetings/— both readable by the whole org.
See Internal systems & data for where each of these sits on disk.
Why it matters
Bounded memory is what makes an org safe to leave running. Without it, prompt size — and therefore cost per turn — grows with history, so a productive org would get more expensive the longer it worked. With summarization, an agent on day thirty pays roughly what it paid on day one, while still remembering the decisions that shaped its work.