Learn · Paths
Role-based learning paths
Each path sequences existing lessons, exercises, and workflow surfaces into an AI usage curriculum. Paths are guidance — not certifications — and every one ends with concrete evidence artifacts you can share with the rest of the team.
Choose your path
Five role-based paths
Pick the audience that fits your work. Every path uses the same underlying lessons, exercises, and workflows — only the sequence and emphasis change.
- beginner45 min· 7 steps
Newcomer to AI model selection
AI model basics for careful users
Three foundational readings + four practical exercises. Walks from a use case to a paste-ready evidence brief plus a freshness checklist. Built for readers new to the catalogue.
Shortlist URLComparison URLMarkdown evidence brief+1 moreStart path →
- intermediate112 min· 11 steps
Engineer preparing an integration
Technical model evaluation before integration
Four readings + three exercises + two pre-seeded workflows. Walks the verified fields a developer needs (hosted creator vs host, modality channels, structured generation, the testing framework) and ends with a comparison URL, an evidence brief, and a written external test plan.
Hosted-provider mapping noteVerified comparison URLDecision evidence brief+1 moreStart path →
- intermediate46 min· 8 steps
Product manager / technical buyer
Model selection for product use cases
Four readings + three exercises + one pre-seeded workflow. Walks use-case framing, pricing references, lifecycle gates, and benchmark limits so the team can align on a defensible review — ending with a use-case shortlist, a pricing-reference note, a lifecycle risk note, and the evidence brief.
Use-case shortlist URLPricing-reference noteLifecycle risk note+1 moreStart path →
- intermediate57 min· 10 steps
Governance / risk / compliance reviewer
AI model governance and source review
Four readings + three exercises + three audit workflows. Walks lifecycle, status, benchmark limits, pricing, and source freshness so a reviewer can sign off with a defensible evidence trail — never a certification claim.
Source freshness checklistLifecycle review noteData gap list+2 moreStart path →
- intermediate141 min· 14 steps
Automation builder / SEO operator / technical consultant
Safe AI model use for automation workflows
Five readings + four exercises + three pre-seeded workflows. Built for people wiring AI models into automations: structured outputs, prompt cost projections, regression test plans, and a brief that ships with the automation runbook. Never an automation marketing pitch.
Safe model-use checklistStructured-output inspection notePrompt testing plan+2 moreStart path →
What paths produce
Every path ends with concrete artifacts. Different paths emphasise different artifacts; nothing is invented and no path produces a recommendation.
- A /select URL that opens your shortlist
- A /compare/build URL that renders verified fields side by side
- A Markdown evidence brief
- A source freshness checklist
- A written external test plan
- A safe model-use checklist for automations
No progress, no accounts, no certificates
- No accounts — the catalogue does not have a login surface.
- No progress tracking — the catalogue does not store which pages you have visited.
- No certificates — the catalogue does not issue completion credentials, badges, or scores.
- Completion is the artifact you produce: a shortlist URL, a comparison URL, a Markdown brief, a freshness checklist, or a written test plan.