Put information in an AI assistant’s long-term memory when it is likely to improve many future answers: stable preferences, recurring constraints, and active goals. Keep each item brief, easy to update, and no more specific than necessary. Don’t use memory as a vault for secrets or as the only copy of text that must remain exact.
What belongs in long-term memory?
A useful memory saves you from repeating context and makes future help more relevant. OpenAI’s Memory FAQ, for example, describes preferences such as location and dietary needs as details that can help personalize responses. That is a practical example, not a universal checklist for every assistant.
- Communication preferences: whether you prefer concise or detailed answers, a particular language, measurement units, or formatting.
- Recurring constraints: dietary preferences, accessibility needs, a budget range, or location when they affect recommendations you request regularly.
- Active goals or projects: a course of study, ongoing project, or job search. Include its current status or a review point so it can be retired when no longer relevant.
- Reusable instructions: explicit guidance that consistently improves assistance and is safe to retain.
A detail earns a place when it is likely to matter again and remembering it would make a noticeable difference. The examples above are recommendations; they are not a fixed list established for all products.
What should you leave out or limit?
- Passwords, recovery codes, and private keys: avoid putting credentials in conversational memory. The available product documentation does not establish a security guarantee for storing them there.
- Highly sensitive personal details: ask whether the exact detail is necessary, whether a less specific version would work, and whether you can inspect and remove it. Avoid retaining intimate details or identifiers unless a specific task calls for them and you understand the system’s controls.
- Temporary facts without an end point: a short-lived circumstance can become misleading. If it needs to be remembered, include when it expires or should be reviewed.
- Exact documents and large text blocks: use a separate document or file that you control for canonical wording, templates, and records. OpenAI says memory is intended for high-level preferences and details, not exact templates or large blocks of verbatim text (Memory FAQ).
- Private information about other people: be conservative about retaining facts they would not reasonably expect to be reused. This is a privacy-minded recommendation, not a universal product rule.
Use this five-question test before saving something
- Reuse: Is this likely to matter in more than one future conversation?
- Impact: Would remembering it noticeably improve the answers?
- Durability: Is it stable, or can you attach an expiry or review date?
- Sensitivity: Could it harm or embarrass someone if it appeared in the wrong context?
- Control: Can you inspect, correct, and remove the memory—and check where the original information also exists?
If the likely benefit is small while the sensitivity or staleness risk is meaningful, leave it out. This is a practical decision framework, not a validated scoring system.
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How to handle sensitive information
Privacy depends on more than whether an assistant initially collects a detail. A 2026 paper, “What to Remember, What to Reveal: Privacy-Aware Memory for Conversational Agents”, treats privacy as a life-cycle issue: how information is written, stored, retrieved, and used matters. The authors propose, among other ideas, separating sanitized searchable information from exact sensitive values and gating retrieval by task relevance and consent. This is a proposed architecture, not evidence that commercial assistants implement those protections.
For any sensitive item, consider whether a broad preference would do instead of an exact identifier or intimate fact. Check the provider’s controls and documentation before relying on them. Legal duties depend on jurisdiction, data type, and your role; general memory guidance cannot settle those obligations.
How to review or remove outdated memory
Review remembered context when your circumstances change, an assistant relies on a wrong assumption, or a fact could have gone stale. Correct it or tell the assistant not to use it. When removing information, check every place it may have been retained:
- Saved memories or summaries
- The conversation where you originally shared it
- Files and connected apps
For ChatGPT, OpenAI says deleting a chat alone does not necessarily delete a separate saved memory. Its documentation also says deleted-memory logs may be retained for up to 30 days for safety and debugging; that is a ChatGPT-specific statement, not a general rule for other services (Memory FAQ). Consult the current documentation for the assistant you use because controls and availability can differ.
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What to compare between assistants
If you are choosing between memory-enabled assistants, check whether you can:
- See what is remembered and where it came from
- Correct or delete individual items
- Understand whether deletion also affects the original chat, files, or connected apps
- Limit retained context to a project or purpose
- Control how sensitive information is retrieved and used
These are useful comparison questions, not a product ranking. The reviewed sources do not establish how competing assistants handle memory or deletion, so verify the provider’s current documentation rather than assuming one service’s controls apply to another.
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Availability can also vary by plan, region, platform, and workspace. For regulated ChatGPT workspaces, OpenAI’s current documentation says improved memory is disabled by default, is not covered under the BAA, and that users should not enter PHI when using it (Memory FAQ). This product-specific guidance is not legal advice about other systems.
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