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Chatbot

Conversation Tags & Labels

Label chats with tags or folders for topic, project, or status. History becomes filterable instead of one flat chronological dump.

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Overview

How might we design conversation tags & labels so people can trust and act on AI output?

When to use

  • Perfect for professionals, researchers, and teams managing multiple projects or topics who need flexible conversation organization.

When to skip

  • Users with only a handful of chats.
  • Workspaces that already organize via projects or channels exclusively.
  • Forced tagging before the first message (add friction later).

Rules

  • Tags that cannot be renamed or merged.

  • AI auto-tags with no user override.

  • Filters that hide chats with no way to clear filters.

  • Personal tags leaking across shared workspaces.

Evidence

ProductImplementation
GmailLabels for organizing threads.
NotionTags and databases for AI and doc sessions.
ObsidianTags across notes and AI-assisted writes.
ChatGPTProjects and organization affordances for chats.

FAQ

Should AI suggest conversation tags?

Yes as suggestions the user can accept or edit. Silent auto-filing surprises people.

Tags vs folders?

Tags allow multiple membership; folders imply one place. Many products offer both.

How does this relate to conversation search?

Tags narrow the set; search finds text inside it. They work best together.

What tags are useful by default?

Project, status (active/done), and sensitivity. Let teams add their own taxonomy.