FG—01AI Design Field Guide

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PTN—38

Legible memory

Show people exactly what the system remembers about them, in plain language they can read, edit, and delete.

When an AI remembers things, the memory itself becomes part of the interface. If people can’t see what’s stored, every personalized response is a small jump scare: the assistant knows your kid’s name, your codebase conventions, that project you abandoned — and you have no idea what else. Legible memory turns the store into a first-class surface: a readable list of remembered facts, each one editable and deletable, written the way a person would say it.

The bar is “plain language,” not “data export.” A JSON dump of embeddings satisfies a compliance checkbox and nothing else. ChatGPT’s memory panel got this right: discrete sentences like “Prefers concise answers” that you can delete individually. The moment memory is written for humans, it also becomes correctable — people fix wrong memories instead of fighting their downstream effects forever.

Legibility also disciplines the system. If a remembered fact would look creepy written down — inferred income bracket, guessed health condition — that’s a signal you shouldn’t be storing it, or at minimum shouldn’t be acting on it silently. The memory panel is where your data practices meet daylight; design it as if a journalist will screenshot it, because eventually one will.

The pattern emerged the moment assistants crossed from stateless chat to persistent memory — ChatGPT’s memory launch made the store a product surface overnight, and every team since has faced the same tradeoff: memory aggressive enough to be useful is aggressive enough to be creepy, and legibility is the only lever that moves both sides at once. Maturity shows in the write path, not the read path. Immature products let you view memories; mature ones announce each write inline, label inference apart from instruction, and prove that deletion propagates. When people start deliberately teaching the memory — “remember that we ship Fridays” — the surface has earned its trust.

When to use

Design considerations

Pitfalls

In the wild

ChatGPT
Maintains a memory panel of plain-language facts; shows “Memory updated” toasts inline when it saves something, and lets users delete individual memories or wipe all of them.
Claude
Project instructions and preferences are user-authored text the person can read and edit verbatim — memory as a document you own rather than a profile inferred about you.
Notion AI
Answers questions grounded in workspace content the user can already see and edit, so “what it knows” maps directly to pages rather than a hidden profile.
Google Gemini
Offers a saved-info surface where users can view and remove details Gemini uses to personalize responses.

Principles served

Discussed in the guide