Tana Fundamentals 02 - Intro to Supertags
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Super tags turn notes into typed entities by attaching field templates and defining relationships, making workspace content more machine- and AI-readable.
Briefing
Tana’s super tags are built to turn ordinary notes into structured, relationship-aware “things”—and that structure is what makes both automation and AI work reliably. Instead of tagging as a loose label (like “productivity” or “history”), super tags define a semantic role for a note, such as “task,” and then attach a template of fields that consistently describe that role. A note tagged as a task automatically carries fields like status, due date, and a related project, making it easy to read and easy for AI to interpret across an entire workspace.
Super tags also create a semantic graph through a simple convention: “has” and “is” relationships. A task “has” a related project, and that related project is itself a note with a “project” super tag. Fields then link to other notes that match the expected relationship type—so the workspace becomes a network of typed connections rather than a pile of unrelated pages. This graph is the foundation for deeper understanding now, and it’s positioned to become even more powerful as AI starts operating on the structure of that network.
Beyond the built-in task super tag, Tana supports creating new super tags in two ways: by typing a hashtag plus the tag name (which triggers an auto-filtering dropdown and creates the tag if it doesn’t exist), or by creating a note named after the tag and converting it into a super tag. Each super tag includes a template of fields that gets applied every time the tag is used. Fields can be added to templates after the fact (“add to template”), and their types can be changed—ranging from text to dates, numbers, URLs, emails, and checkboxes. Option fields become dropdowns; for example, the task status field can be configured with values like “to-do,” “done,” “canceled,” or “dropped.”
A key productivity feature is auto-initialization for relationship fields. When a note is indented under a parent note that has a relevant super tag, Tana can automatically fill fields like “related project” based on the ancestor context—so users don’t have to manually set the relationship each time.
Super tags are also composable. Adding multiple super tags to a note merges their field templates, and colors indicate which super tag each field comes from. Even more powerful, one super tag can inherit from another (“extend from”), so a “design task” can automatically include all “task” fields plus extra ones like a Figma URL. That inheritance means searches for “task” can still surface “design task” items without requiring users to apply multiple tags.
For AI readiness, super tags can be assigned a base type from Tana’s built-in categories, helping AI understand what the tag is for. Fields can be configured as AI-enhanced option fields that use AI to infer and populate values—such as identifying the topic of a quote and linking it to an existing “topic” note (or creating one if needed). Tana also supports AI instructions per super tag and voice-driven workflows via audio-enabled super tags, where recorded audio is transcribed into a child note and summarized back into the tagged note. The result is a system where structure, relationships, and AI automation reinforce each other rather than competing for attention.
Cornell Notes
Super tags in Tana turn notes into typed “things” by attaching a field template and defining relationships between notes. A task super tag, for instance, adds fields like status, due date, and a related project, and those fields link to notes that carry the expected super tags. This creates a semantic graph that supports both consistent organization and deeper AI understanding. Super tags can be composed (multiple tags merge fields) and inherited (a design task can extend task, so it automatically counts as a task in searches). With AI-enhanced fields and base types, Tana can infer values like a quote’s topic and link to existing topic notes, while audio-enabled super tags enable voice capture and transcription.
How do super tags differ from ordinary tagging in Tana, and why does that matter for AI?
What is the “has/is” relationship idea, and how does it show up in fields?
How does Tana reduce manual work when setting relationship fields?
What does it mean for super tags to be composable and inheritable?
How does Tana make super tags and fields “AI ready”?
How do audio-enabled super tags work in practice?
Review Questions
- Explain how a task super tag’s fields connect to other notes and what that implies for workspace structure.
- Describe the difference between composing super tags on a note versus inheriting one super tag from another.
- Give an example of how AI-enhanced fields could reduce manual tagging or linking in a Tana workspace.
Key Points
- 1
Super tags turn notes into typed entities by attaching field templates and defining relationships, making workspace content more machine- and AI-readable.
- 2
Tana’s “has/is” relationship approach links fields to other notes based on expected super tags, forming a semantic graph.
- 3
Super tags can be created via hashtag naming or by converting a note into a super tag, and they can include typed fields like option dropdowns, URLs, and dates.
- 4
Relationship fields can auto-initialize from ancestor context, reducing repetitive manual linking when notes are indented under parent items.
- 5
Super tags are composable (multiple tags merge fields) and inheritable (one tag can extend another), enabling systems like “design task” that automatically behave as “task.”
- 6
AI readiness comes from setting super tag base types and configuring fields as AI-enhanced option fields that can infer and link values from note content.
- 7
Audio-enabled super tags streamline capture by transcribing recorded speech into child notes and summarizing it back into the tagged note.