In this tutorial, Mitch takes us through our new Projects feature.
What's inside a Project
A Project bundles four things. System instructions define the persona and rules. Prompts and workflows give you reusable, multi-step operations you can run on demand. MCP connectors plug in external tools like Asana, Linear, or your own services. Knowledge bases hold reference material the model reads from and output folders where the model writes results.
How conversations work
Every chat starts with the Project's context loaded. Use @ mentions to point the model at a specific prompt, workflow, knowledge base, or connector. Toggle "Run in background" to queue a task asynchronously, then return to the completed conversation whenever you want.
How Projects compound
Assign a folder as reference (the model reads from it) or as output (the model writes results to it). On the next run, the model reuses prior outputs and reference material instead of starting from zero. Share the Project with your team and everyone works with AI through the same tools and instructions.
What you can use Projects for: customer research, code review, sales prospecting, content production, ops runbooks, and anything else where the context is stable but the questions change.