Learn · Path · 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.
Audience
Newcomer to AI model selection
Difficulty
beginner
Estimated time
45 min · 7 steps
What you walk away with
What you will learn
- How to frame an AI model selection workflow before opening the catalogue.
- What a verified context window guarantees — and what it does not.
- What active / preview / deprecated / retired lifecycle states actually mean.
- Why the catalogue records data gaps as the unverified-data label rather than guessing.
What you will build
- A /select URL that opens your shortlist for any teammate.
- A /compare/build URL that renders verified context fields side by side.
- A Markdown decision brief paste-ready for a PR or design doc.
- A freshness checklist scoped to the citations you depend on.
Evidence artifacts
- Shortlist URL
- Comparison URL
- Markdown evidence brief
- Source freshness checklist
Tools used
Learn hub →
Concept lessons that explain each verified field.
Exercises →
Practical workflows that end with evidence artifacts.
Selection workspace →
Filter the catalogue by use case, lifecycle, verification.
Comparison builder →
Render verified fields side by side for 2–4 models.
Decision brief builder →
Export a Markdown or JSON evidence brief.
Citation registry →
Every primary-source URL the catalogue references.
Reverification queue →
Sources due for manual re-check with retrievedAt dates.
Prerequisites
No prior catalogue knowledge required.
Timeline
7 steps
Open each step in the order shown. The route on every step is the canonical workspace or lesson — no parallel UI.
- lesson5 min
How to choose an AI model
Frame the decision workflow before opening the catalogue.
- lesson5 min
Context windows explained
Understand the verified field most beginners over-weight.
- lesson5 min
Model lifecycle: active, deprecated, retired
Treat lifecycle as a hard gate, not a footnote.
- exercise8 min
Build your first source-backed shortlist
End with a /select URL that captures your filter choices.
- exercise7 min
Compare context windows without ranking models
End with a /compare/build URL that renders verified context fields side by side.
- exercise10 min
Create a decision evidence brief
End with a paste-ready Markdown evidence brief.
- exercise5 min
Check source freshness and reverification state
End with a freshness checklist for the citations you depend on.
Start next
Step 1 of 7: How to choose an AI model
Frame the decision workflow before opening the catalogue.
What this path does not promise
- Picking which model is best for your workload.
- A completion certificate, badge, or score.
- A substitute for your own workload-specific testing.
How to use this path
- Open each route in the order shown. The path is a sequenced reading + practice plan, nothing more.
- Keep the artifacts you produce — the shortlist URL, comparison URL, Markdown brief, freshness checklist, or test plan.
- There is no login surface, no progress state, and no completion certificate.
- External workload-specific testing remains your team's responsibility — the catalogue surfaces evidence, not verdicts.
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.