1.3 — Selecting Architectural Patterns
CCAR-P Domain 1 · Task 1.3
What You Need to Know
Three Tiers (Anthropic)
| Tier | Description | When |
|---|---|---|
| Augmented LLM | Single model call + retrieval/tools/memory | Default for most problems |
| Workflow | Predefined code paths orchestrate LLMs + tools | Steps known; need predictability, auditability |
| Agent | Model dynamically directs its own processes/tools | Path cannot be scripted |
Five Workflow Patterns
| Pattern | Selection cue |
|---|---|
| Prompt chaining | Task decomposes into fixed sequential subtasks |
| Routing | Distinct input categories better handled separately |
| Parallelisation | Independent subtasks or multiple perspectives (sectioning / voting) |
| Orchestrator-workers | Subtasks cannot be predicted in advance |
| Evaluator-optimizer | Clear evaluation criteria exist and iteration helps |
Decision Rule
Find the simplest solution that meets requirements; add complexity only when it demonstrably improves outcomes. Escalate tier only when the simpler tier cannot meet a named requirement.
Key Concept: Workflows beat agents when steps are known. Agents earn cost when the path cannot be scripted.
Exam Traps
- Deploying an autonomous agent for a fixed, well-specified pipeline
- Choosing chaining when the scenario describes distinct categories (want routing)
- Choosing evaluator-optimizer with no clear evaluation criteria
- One monolithic prompt for a task that needs staged quality gates
Check your understanding
Practice Scenario
Support tickets are classified into five categories and then answered or escalated. Each category has its own rules, and changing one category must not alter the others. Volume is high, latency matters, and handling must be consistent and auditable. What is the best architecture?
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Sources
- Building effective AI agents, Anthropic
- Features overview, Claude Platform Docs
- How we built our multi-agent research system, Anthropic