AI Conversation Branching
Explore an alternate path from an earlier message without losing the original.
What it adds
A message graph that lets a conversation fork at any point, with each branch keeping its own history and active state.
What your agent is told to do
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What your agent is told to do
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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.
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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.
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Give each branch its own summary, memory, and derived context. Carrying one summary across siblings leaks the abandoned path back into the new one.
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Show the user, at the fork point, that alternatives exist, which one is active, and how to move between them, without turning the transcript into a diagram.
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AI Message Editing owns editing an ancestor message and invalidating what follows. This entry owns the graph and navigation. Editing should create a branch through this model rather than mutating history in place.
Edge cases it handles
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Edge cases it handles
8- Every message must carry an unambiguous parent, including the first. A graph where the parent is inferred from timestamps will scramble under concurrent writes.
- Summaries, retrieved context, and remembered facts are branch-scoped. Reusing the parent conversation's memory in a new branch reintroduces exactly the content the user branched away from.
- Branching from a point after a tool call must reuse the recorded result rather than re-running the tool, because re-running it repeats side effects such as sending, charging, or writing.
- Without a visible indicator of which branch is active and a way back, users lose work they believe they can find again. Show the alternatives count at the fork and keep navigation reversible.
- Editing a message that has descendants must not corrupt them. Fork at the edited message rather than rewriting it, so the original subtree stays intact and reachable.
- Deleting a message must have a defined effect on its descendants, and deleting a fork point must not orphan the branches hanging from it.
- Sharing or exporting a branched conversation needs a defined scope: the active path by default, with any other choice made explicit to the person receiving it.
- Usage and cost accounting must attribute each run to its branch, or a heavily explored conversation becomes impossible to explain on a bill.
Definition of done
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Definition of done
9- Conversations are stored as a parent-child message graph and existing linear conversations are migrated into it.
- The active branch is an explicit stored pointer, and the rendered transcript is derived from the root-to-pointer path.
- Summaries, memory, and retrieved context are scoped per branch and do not leak across siblings.
- Branching past a tool call reuses the recorded result and never re-executes the action.
- The interface shows where forks exist, which branch is active, and how to return to the others.
- Editing an ancestor forks the graph and leaves the original subtree intact and reachable.
- Runs are attributed to the branch they belong to for usage and cost reporting.
- 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.
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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.
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No account needed
Add this feature to my app:
https://addthisfeature.com/x/ai-suggested-support-answers
Streaming AI Responses
Streaming AI Responses
Show AI output as it is generated so long answers do not look frozen.
What it does
Incremental rendering of model output as it arrives, with a persisted authoritative copy once the stream closes.
How it works
- 1 Find the AI surfaces where the user waits on a long response and stream those. Short classification or extraction calls do not benefit and should stay as plain requests.
- 2 Buffer incoming bytes until they form complete characters and complete structural units before rendering, so partial output never appears as broken glyphs or half-open markup.
- 3 Treat the streamed text as provisional. When the stream closes, persist the provider's final message as the authoritative record and reconcile what is on screen against it.
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No account needed
Add this feature to my app:
https://addthisfeature.com/x/streaming-ai-responses
How it works
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Copy the link
Grab the Markdown instruction URL for this feature.
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Give it to your AI
Paste it into Claude Code, Cursor, v0, Lovable — whatever you build with.
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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.