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Domain 2 – Claude Models, Prompting & Context Engineering (13%)

5 lessons, each ending with a practice scenario (Pro)

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  1. ✓2.1 — Selecting Claude Models on Trade-OffsModel selection = which model clears this task’s quality bar at the lowest cost that meets the latency budget. Never “which model is best”.Scenario: Pro
  2. ✓2.2 — System Prompts, Templates, and GuardrailsSystem prompt = standing contract (role, audience, policy, output format). User turns carry per-request data. Template = prompt with named slots. Guardrail = limit on what the model receives or returns.Scenario: Pro
  3. ✓2.3 — Zero-Shot, Few-Shot, and Chain-of-ThoughtDiagnose before adding anything. Instruction quality is the first, free fix. Matching Technique to Failure: Output format wrong/drifting, Inconsistent classification at boundaries, Wrong answers on multi-step reasoning, Stated rules ignored, Any of the above.Scenario: Pro
  4. ✓2.4 — Optimising Context Windows and Token UsageContext window = everything Claude sees in one request (system, history + tool results, tool definitions, output + thinking). Every token is billed every time it appears.Scenario: Pro
  5. ✓2.5 — Prompt Reuse: Caching, Modular Prompts, and SkillsThree mechanisms for three reuse questions: Prompt caching, Modular prompts, Skills; Prefix Mechanics: Order: tools → system → messages. Front-load stability: static system/policy/examples first, dynamic content last. A timestamp early in the prompt defeats the entire cache.Scenario: Pro
Domain recapQuick overview of all lessons
  • Model selection on capability / cost / latency / context-window trade-offs
  • System prompt design, templates, and guardrails
  • Zero-shot, few-shot, chain-of-thought (and when each helps)
  • Context-window optimisation and token budgeting
  • Prompt reuse: caching, modular prompts, Skills
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Domain 3: Integration →