AI Conversation Memory
Carry durable preferences between AI conversations without replaying every past message.
What it adds
A reviewable store of durable facts and preferences, scoped by user and workspace, retrieved selectively into new conversations.
What your agent is told to do
5
What your agent is told to do
5-
1
Define what qualifies as memory before writing any of it: stable preferences, standing instructions, and settled facts about how this user or workspace works. A one-off request inside a single conversation is not memory.
-
2
Give the user a screen listing everything remembered, in plain sentences, with the ability to edit, delete, and turn memory off entirely. A store the user cannot inspect will be assumed to contain more than it does.
-
3
Scope every entry to a user, a workspace, and the assistant it applies to, and enforce that scope on retrieval. One person's preference must never surface in a colleague's conversation, and a workspace fact must not follow the user elsewhere.
-
4
Retrieve only the entries relevant to the current conversation and show which ones were applied. Injecting the whole store into every request costs tokens, dilutes the context, and drags in preferences that do not apply.
-
5
Do not write memory silently. Surface a proposed entry for confirmation, or at minimum notify the user that something was remembered with a one-click undo, so an inference never becomes a permanent fact without their knowledge.
Edge cases it handles
8
Edge cases it handles
8- Passing detail does not belong in long-term memory. Exclude anything transient, anything sensitive such as health, financial, or credential information, and anything scoped to a single task, and apply a retention window so unused entries expire.
- Every entry must be visible, editable, and deletable individually, and deleting one must remove it from retrieval immediately rather than at the next background rebuild.
- Scope is enforced at retrieval, not just at write time. A memory written in one workspace must be unreachable from another even when the same person is signed in.
- The model will infer things that are not true. Do not promote an inference into memory on its own; require a direct statement from the user or an explicit confirmation, and record which it was.
- Retrieve a bounded, relevant subset per conversation and show the user which memories were applied to a given answer, so a surprising response can be traced to the entry that caused it.
- Memories conflict as preferences change. Prefer the most recent, flag the contradiction for the user, and never apply two opposing entries in the same request.
- When retrieval is unavailable or the store is empty, the assistant must still answer normally without memory rather than failing or apologising for missing context.
- Deleting an account or workspace must remove its memories along with everything else, and an export of personal data must include them.
Definition of done
9
Definition of done
9- Only durable, non-sensitive facts and preferences are stored, and entries expire after a defined period of disuse.
- Users can view, edit, and delete every remembered item and disable memory entirely.
- Memories are scoped by user, workspace, and assistant, and the scope is enforced on retrieval.
- No entry is written from a model inference without user confirmation.
- Only a bounded, relevant subset is retrieved per conversation, and the applied entries are shown.
- Conflicting entries resolve to the most recent and are surfaced to the user.
- The assistant functions normally when the memory store is empty or unavailable.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
AI Chat Attachments
AI Chat Attachments
Attach files to a conversation and let the assistant use what it is allowed to read.
What it does
File upload on an AI conversation, with parsing, retrieval of relevant sections, and per-conversation access scoping.
How it works
- 1 Reuse the app's existing upload, storage, and virus-scanning path rather than adding a second one, and declare an explicit list of accepted file types and a size ceiling per file and per conversation.
- 2 Parse each attachment into text and structure in a background job, store the result, and show the attachment as pending until parsing succeeds so the user is never told the assistant has read something it has not.
- 3 Retrieve and send only the sections relevant to the current question. Sending whole documents on every turn burns the context window and the budget for no gain.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-chat-attachments
AI Suggested Support Answers
AI Suggested Support Answers
Give support agents a grounded first draft instead of a blank reply box.
What it does
A draft reply composed for the agent from the ticket, the customer's account state, and the approved internal knowledge, with sources attached and no ability to send itself.
How it works
- 1 Ground every draft in retrieved material: the ticket thread, the account's real state, and articles from the approved knowledge set. Attach the sources used to the draft so the agent can open and check each one.
- 2 Load the draft into the agent's normal reply editor, unsent and fully editable. There is no path in this feature that sends a message to a customer without an agent pressing send.
- 3 Define the commitments the app is not allowed to make in a draft — refunds, credits, delivery dates, guarantees of a fix — and strip or refuse any draft containing them, leaving that part for the agent to write.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-suggested-support-answers
AI Conversation Branching
AI Conversation Branching
Explore an alternate path from an earlier message without losing the original.
What it does
A message graph that lets a conversation fork at any point, with each branch keeping its own history and active state.
How it works
- 1 Change the conversation's storage from an ordered list to a graph where every message names its parent, and migrate existing conversations into that shape as single-path graphs.
- 2 Define the active branch as a stored pointer to a leaf message, and derive everything rendered from the path between the root and that pointer.
- 3 Give each branch its own summary, memory, and derived context. Carrying one summary across siblings leaks the abandoned path back into the new one.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-conversation-branching
How it works
-
1
Copy the link
Grab the Markdown instruction URL for this feature.
-
2
Give it to your AI
Paste it into Claude Code, Cursor, v0, Lovable — whatever you build with.
-
3
It inspects, then implements
Your agent reads your existing app first, then adds the feature to fit it.
Works with your stack
These instructions are written to adapt. They tell the agent to detect your framework, match your existing design system, and reuse what you already have — rather than assuming a particular stack.
Need it tighter than that? Customize the feature and tell it exactly what you're running.