3.6 — Matching Retrieval to Data Shape and Query Pattern
CCAR-P Domain 3 · Task 3.6
What You Need to Know
Retrieval 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.
Data Shape Axis
| Shape | Native strategy |
|---|---|
| Live structured (DB, catalogues, accounts) | Query tool against system of record |
| Narrative documents (policies, manuals) | Semantic retrieval over chunked text |
| Code / rigid text | Structure-navigating retrieval |
| Small & stable | Cached prompt (no retrieval) |
Query-Pattern Axis
| Pattern | Cue | Native strategy |
|---|---|---|
| Exact lookup | Identifier (part #, error code) | Keyword / filtered search |
| Conceptual | “Summarise”, “what is our policy” | Semantic retrieval |
| Multi-hop / exploratory | Comparison, unknown path | Agentic retrieval |
| Recall-critical | “Must not miss a document” | Hybrid + reranking |
Selection Method
- Name the data shape
- Name the query pattern
- Name the failure that matters most
- Pick the cheapest strategy whose failure mode is acceptable
One system can combine multiple strategies. Hybrid is a design answer, not a compromise.
Exam Traps
- Embedding live operational data into a vector store
- Applying one retrieval approach to every data shape
- Deploying agentic multi-hop on a simple latency-budgeted lookup
- Choosing precision/latency-first where no relevant document may be missed
Check your understanding
Practice Scenario
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Sources
- Contextual retrieval in AI systems, Anthropic
- Embeddings, Claude Platform Docs
- Effective context engineering for AI agents, Anthropic