A learning path is a structured, end-to-end development route for a single job family — the ordered set of learning a person moves through to grow from newcomer to expert in that family. Where learning recommendations answer what should this one person do next about this one gap?, a learning path answers what does the whole journey look like for this kind of role?
The four ascending stages
Every path is built from the same four stages, in ascending order, each mapped to a band of the Saudi National Qualifications Framework (NQF):
- Awareness (NQF 2–3, Knowledge) — foundational courses that build awareness of the field and its tools.
- Breadth (NQF 4–5, Competency) — sibling-competency topics around the core: stakeholders, communication, resources.
- Certification (NQF 6–7, Competency) — specialised professional certifications from an accredited body.
- Mastery (NQF 7–8, Values) — passing knowledge on through mentoring, review, and delivering courses.
The stages are the client's development model; the NQF bands and the knowledge/competency/values dimension on each badge are derived consistently in code, not typed in per path, so every path reads the same way. Each stage holds a handful of items — a course, a competency, a certification, or a mentoring activity.
Where to find it
/{slug}/app/grow/learning-paths → open a path, or create a new one.
Job-family-first, then AI
A path always starts from a job family — you pick the family before anything else, and that choice is locked for the life of the path (it defines which competencies the items are allowed to reference). From there you can:
- Generate with AI. The assistant drafts all four stages for the chosen family in sequence, proposing items stage by stage. Where it suggests a course that isn't in your workspace catalogue, it proposes the course name and flags it as an AI suggestion rather than inventing a catalogue entry.
- Edit freely. Every AI draft is a starting point — nothing is written until you save. Add, remove, reorder, and retag items by hand.
Per-item competency tags and contribution strength
Each item can be tagged with the competencies it builds. A tag carries a contribution strength from 0 to 100 — a relevance signal, not a percentage that has to sum to anything: how strongly this item moves that competency. Tags are constrained to the competencies selected for the path's job family, so a path can only ever claim to build competencies that actually belong to the family.
Coverage summary
Rolling those tags up against the job family's selected competencies gives the coverage summary at the foot of the path: a single ratio and progress bar — how many of the family's competencies the path addresses at all (binary — addressed or not) out of the total. Expand it and the blind spots come first: the family competencies no item in the path builds yet, so you can see at a glance where a path is thin before you hand it to a person. It sits below the stages because the stages are the path — coverage is the quick completeness check on top.
Next
Learning recommendations — the per-person, per-gap lens that complements these family-wide paths — is covered next.