How would you design long-term memory for an AI agent?

Stores only useful, scoped, attributable memories with extraction, verification, retrieval, expiry, correction, and deletion.

1Say itAnswer out loud first

2CompareCompare with Core answer

3RefineRefine with Stronger and Advanced

TL;DR

I store only information with a defined future use, such as an explicit user preference, verified project fact, or durable task artifact. Each memory records owner, source, time, scope, and type, then follows retention and deletion rules. Retrieval is permission-filtered and relevance-limited before selected memories enter the model context.

Full answer below

Practice focus

Memory selection, provenance, privacy, retrieval quality, lifecycle, and user control.

Answer first

Answer path

Core answer first, then checkpoints toward a stronger answer.

Start
Core answer
Start here. This is the direct spoken answer to practice first.
Overview
Long-term memory should improve future tasks without becoming an unbounded store of model guesses.
I store only information with a defined future use, such as an explicit user preference, verified project fact, or durable task artifact. Each memory records owner, source, time, scope, and type, then follows retention and deletion rules. Retrieval is permission-filtered and relevance-limited before selected memories enter the model context.
Checkpoint
Stronger answer
Optional upgrade with examples, trade-offs, and sharper phrasing.
Memory extraction is separate from memory acceptance. Explicit user statements may be stored directly after consent, while model-inferred preferences need lower confidence, expiry, or confirmation. Contradictions create correction or supersession instead of silently keeping both. Users can view and remove relevant memories, and sensitive categories may be prohibited entirely.

Review signals

Use these to catch weak phrasing, shallow reasoning, and risky claims.

Common mistakesCandidateCommon mistakesMistakes that weaken the answer or signal shallow understanding.Open details

Details

Persisting every conversation turn as long-term memory.
Storing model-inferred facts without provenance.
Retrieving memories by vector similarity alone.

How would you design long-term memory for an AI agent?

Practice focus

Answer path

Overview

Review signals

Follow-up prompts

Continue practice

Next in path

Tech stacks

Skill areas

Human editorial direction

Was this drill useful?

Found this answer useful?