Use case

Folder vs Project: When to Use Each

Folders and projects serve different purposes in Motion’s hierarchy. Folders organize at a higher level; projects are where execution happens.

Use a folder when	Use a project when
You need a container for related projects.	You’re driving execution toward a specific goal.
Work is grouped by function, department, or theme (e.g., Marketing, Finance, Q4 Initiatives).	Work has a timeline, deliverables, and milestones (e.g., Website Redesign, Product Launch).
Access needs to be granted broadly — everyone in the folder can see the projects inside.	Access should be scoped more narrowly to a single initiative.
Metadata is descriptive: labels, owner, high-level scope.	Metadata is operational: due dates, status, tasks, dependencies.
The work inside will continue over time (a folder may hold multiple ongoing projects).	The work is time-bound — it ends when deliverables are complete.

Decision rule: 👉 If you’re organizing work thematically or structurally, use a Folder.

👉 If you’re planning and executing toward an outcome, use a Project.

Cross-Cutting Rules

No matter where you are in the hierarchy — from folders down to subtasks — a few practices apply everywhere. These rules make Motion scalable, searchable, and easier for both humans and AI to navigate.

• Naming conventions → Keep names short, consistent, and descriptive. Use patterns your team agrees on (e.g., Q4-Marketing-Website vs. Website Project). Consistent names improve searchability and AI relevance.

• Tagging and labels → Apply tags at the project and task level to group work across folders. Tags add a second dimension of organization beyond hierarchy.

• Searchability → Everything in Motion is searchable by title, tags, and metadata. The cleaner your naming and tagging, the faster teammates (and AI) find what they need.

• Metadata hygiene → Keep owners, due dates, and statuses up to date. Inaccurate metadata creates friction at every layer.

• AI alignment → Remember: hierarchy and metadata are what Motion’s AI uses to ground its outputs. Clean structure = better context = more accurate results.

Key principle: Hierarchy organizes the work, but cross-cutting rules keep it usable at scale.