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Profy experts remember what you said across sessions. This page explains the structure; for day-to-day management see personal memory and expert memory.

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First, two owners

Memory isn’t one big pool. There are two ownership tracks that never overwrite each other:
What comes out of chatting with an expert does not become personal memory — that path writes expert memory. To make a preference apply everywhere, say it in free chat, or say “remember: …” explicitly at any time.

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Three layers

On the expert side, data flows one way:

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Where memories come from

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Automatic extraction (the main source)

A background pass analyzes the conversation afterwards and keeps only what meets three criteria: specific (not “likes good code”), durable (not “is debugging this right now”), and non-obvious (not “wants working code”). Deduplication runs before every write. There’s a threshold: the expert path requires 5 accumulated turns for that user × expert pair and at least 3 human messages in the session. The counter persists across sessions and expires after 7 days of no interaction. So seeing no new memories after two messages is normal.

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Explicit memories

“Remember: my team has a weekly sync on Wednesdays.” Explicit memories bypass quality gating and land directly — the most reliable route.

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Creator seeding

Creators can pre-seed domain understanding during distillation so an expert has judgment from the first conversation. It doesn’t interfere with your memories, and creators cannot see your memory content.

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Consolidation (Dream)

Periodically the system distills scattered entries into structured knowledge: sync evidence → distill in chunks (at most 12 evidence items per LLM call) → resolve contradictions (the old fact’s validity closes, the new one takes over, history preserved) → update the graph. Deep consolidation only looks at memories with activity in the last 24 hours, has a 600-second budget per tick, and a 6-hour cooldown.
Consolidation never rewrites your memory list. It distills from it and never writes back.

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How much gets injected

Not everything — retrieval runs against a budget: 30 candidates → 1-hop graph expansion from the top 5 → at most 20 facts, capped at 2,000 tokens total. Whichever limit hits first wins; if retrieval fails it degrades to a deterministic top 20. Which memories an answer used is stored with the message, so the citations survive a refresh.
Memory is reference, not instruction. You prefer TypeScript, but when the task is editing a Python project the expert won’t rewrite it in TS — that’s correct.

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What you control

When something is wrong, prefer editing: deleting discards the reasoning distilled from it too, while a rewrite lets the next consolidation redo the work with correct input.

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Common issues

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Next

Personal memory

Your cross-expert profile

Expert memory

Memory list, core memory, and the graph

Temporal memory graph

Entities, facts, and validity windows

Temporary chat

A mode that neither reads nor writes memory