Sessions and objectives
A Learning Path is a list of sessions. Users complete them in sequence: session 3 cannot be opened until session 2 is complete. Each session holds a set of objectives, defined as the observable actions a user must demonstrate before the AI Fellow marks the session as complete.
Add a session
Click Add Session.
Optionally add admin notes. Only Admin users see them; users never do. They define how the AI Fellow runs the session in the background.
Define the session objectives (next).
Define objectives
The AI Fellow validates objectives in real time during the conversation, based on what the user states or demonstrates on the shared screen. Each objective is recorded as either met or pending.
Write the objective in clear, specific language. For example, "The user names at least three customer pain points the product addresses."
Repeat for every objective the session requires. The number of objectives per session is not capped.
Make objectives observable. "Understands the product" is hard for an AI Fellow to confirm. "Explains the three main features without checking the docs" is clear: either it happens in the conversation or it does not.
Info screen
Each session can show an optional welcome modal before the user starts the conversation. Use it to provide context, share a short briefing video, or frame the session.
The session info screen has the same fields as the
AI Fellow Info screen: title, optional
subtitle, optional video URL (Vimeo, YouTube, or a direct .mp4 link),
and optional body text. Leave the title empty to hide the modal. The
modal opens whenever the user enters that session, not only on the first
visit.
Edit these fields from the session panel in the Learning Path editor, alongside the session name, description, and admin notes.
Session knowledge
Each session can carry up to two reference files that the AI Fellow reads only while the user is in that session. Upload them from the session panel in the editor. For material that should apply to every session in the path, use the path-level upload area instead. See Learning Path knowledge.
Add an AI Simulation between sessions
An existing AI Simulation can be placed into a Learning Path as a step between sessions. It joins the same ordered sequence: it unlocks when the previous session is complete, and the user starting a conversation with it unlocks the next session.
In the Sessions area, click Add AI Simulation next to Add New Session.
Pick a simulation from the list. Only Active AI Simulations in the workspace are selectable. When none exist, the button stays disabled and the list reads No active AI Simulations available in this workspace.
The simulation is added as a step and can be moved into position with the arrow controls, the same way as a session. Click Save.
A simulation step carries an AI Simulation tag on the user's Journey and opens the role-play conversation directly. It has no objectives of its own to define here; the simulation's success criteria drive the assessment. To change those, edit the simulation itself from AI Simulations.
A simulation has to exist and be set to Active before it can be added. Build one from Frontierz Studio → AI Fellows → New AI Fellow → AI Simulation. See AI Simulations.
Add a SCORM lesson
The Sessions area also has an Import SCORM button. Use it to add an existing SCORM package (for example, an e-learning module exported from an authoring tool) as a step in the sequence. It unlocks when the previous step is complete and gates the next step until the package reports completion. See Import a SCORM package.
Why sessions are sequential
Sessions open in order because each one assumes the competencies built in the previous ones. For a non-sequential library of content where the user selects what to read, a Learning Path is not the right format. A single AI Fellow with a broad Knowledge Base would fit better.