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Domain 3 – Integration (19%) – Highest weight
8 lessons, each ending with a practice scenario (Pro)
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- ✓3.1 — Capability Bloat and Least-Privilege ConfigurationLeast privilege = agent gets only the tools its role needs. Capability bloat = every tool beyond that. Removal beats mitigation every time.Scenario: Pro
- ✓3.2 — Authentication, Authorisation, and the Gaps BetweenAuthentication = who is calling. Authorisation = what may they do. A security gap exists wherever effective privilege exceeds the requesting user’s legitimate need.Scenario: Pro
- ✓3.3 — Accuracy–Latency Trade-offsEvery integration has a latency requirement (e.g. p95) and a quality requirement. The skill is holding both at once.Scenario: Pro
- ✓3.4 — Observability and Monitoring at ScaleLLM systems break anecdote debugging: non-deterministic, so a single re-run proves nothing. A green uptime dashboard says nothing about answer quality.Scenario: Pro
- ✓3.5 — RAG Pipeline Design: Chunking and IndexingRAG stages: ingest → chunk → embed → index → retrieve → (rerank) → generate. Generation quality is capped by retrieval quality.Scenario: Pro
- ✓3.6 — Matching Retrieval to Data Shape and Query PatternRetrieval strategy rests on two axes: data shape and query pattern. Then name the failure that matters most and pick the cheapest strategy whose failure mode is acceptable.Scenario: Pro
- ✓3.7 — Choosing the Integration MechanismFour mechanisms connect Claude to surrounding systems: MCP server, Direct API/SDK, Headless (SDK/CLI), Agent-to-agent.Scenario: Pro
- ✓3.8 — Progressive Discovery vs Monolithic ContextTwo ways to load tools, procedures and knowledge: Monolithic — load everything upfront (simplest; best for small stable surfaces; cacheable); Progressive discovery — load each piece on demand (Skills, deferred tool loading, agentic retrieval).Scenario: Pro
Domain recapQuick overview of all lessons
- Detect and prevent capability / tool bloat
- Authentication & authorisation gap analysis
- Accuracy vs latency configuration decisions
- Observability strategies at enterprise scale
- RAG pipeline design (chunking, indexing, retrieval strategy matched to data shape)
- Connection protocol selection: MCP vs direct API/CLI vs agent-to-agent
- Progressive discovery vs monolithic context loading
Domain 4: Evaluation, testing & optimisation →