1.1 — Translating Business Problems into Claude Solutions

CCAR-P Domain 1 · Task 1.1

What You Need to Know

Translating a business problem into a Claude solution produces a measurable success criterion, a bounded scope, and a defensible boundary between the model and ordinary software.

Problem-First Design (before any pattern/model/prompt)

1. The job to be done — who, how long, cost, where it goes wrong
2. The constraint set — latency, cost, accuracy, risk, data sensitivity, regulatory
3. The success criterion — metric + baseline + target (defined before build)

Key Concept: Define measurement before implementation. Sequence: problem → constraints → success criterion → solution shape.

The Fit Test: Is This an LLM Problem?

Claude belongs where the task needs language understanding, synthesis, judgement over unstructured input, or flexible conversation. Deterministic rules → conventional software (cheaper, faster, exact, auditable). Most production solutions are hybrids.

Capability Mapping (task shapes)

Task shape	Architecture implication	Evaluation
Classification	Single call, constrained output	Accuracy vs labelled set
Extraction	Structured output + schema validation	Field-level precision/recall
Summarisation	Single call, grounding checks	Faithfulness / similarity
Generation	Draft-for-review, tone constraints	Rubric-graded quality
Conversation	Context management, session state	Multi-turn quality + safety
Agentic action	Tools, guardrails, observability	End-to-end task success rate

Scoping

Start with the narrowest workflow that delivers measurable value, prove it, then expand. Targeted workflow beats general-purpose assistant on every business-value pillar.

Exam Traps

• Proposing a general-purpose assistant when the case names one high-volume workflow
• Selecting architecture before capturing constraints and success criteria
• Routing a fully rule-specified sub-task through a model call