CCA-F Certification Prep · lesson 3 of 10
Domain 1 — Agentic Architecture & Orchestration (27%)
The largest domain. Tests whether you can pick the right architecture for a given problem.
Topics
1.1 Workflow vs Agent
From Anthropic's Building Effective Agents:
- Workflow: "LLMs and tools are orchestrated through predefined code paths."
- Agent: "LLMs dynamically direct their own processes and tool usage."
Default to workflow unless dynamism is required. "Agentic systems often trade latency and cost for better task performance."
Test your scenario: can you predetermine the sequence of steps? If yes → workflow. If you need open-ended reasoning across N+ steps with ground truth checks at each step → agent.
1.2 The five patterns (memorize trade-offs)
| Pattern | When | Cost | Latency | Predictability |
|---|---|---|---|---|
| Prompt chaining | Steps known in advance | Low | Predictable | High |
| Routing | Multiple specialized handlers | Low | Low (1 classify + 1 handler) | High |
| Parallelization | Independent subtasks OR consensus | Mid | Low (parallel) | Mid |
| Orchestrator-workers | Dynamic decomposition | High | Variable | Low |
| Evaluator-optimizer | Quality matters > speed | High | High (iterative) | Mid |
See agentic-patterns for full details.
1.3 Multi-agent coordination
- Orchestrator holds the plan and the goal. Larger model usually.
- Workers are focused, smaller, often Haiku.
- Provenance flows up — each worker tags results with source IDs.
- Shared mutable state is an anti-pattern between workers; pass results up via orchestrator.
1.4 Task decomposition
- Break by independence when parallelizing.
- Break by dependency chain when sequencing.
- Break by expertise when routing (different tool sets per worker).
- Tag every subtask with: input contract, output contract, allowed tools.
1.5 Session state management
- Application owns conversation state — the API is stateless.
- State object pattern beats replay for long-running flows.
- Subagents should not share state; each gets a self-contained brief.
- Use IDs (request_id, conversation_id, task_id) to thread observability.
1.6 Human-in-the-loop
- Confirmation gates before destructive ops.
- Escalation paths when confidence is low or tools fail.
- "I don't know" is a valid agent action — better than hallucinating.
1.7 Reliability primitives
- Capped iterations (avoid infinite loops).
- Retry policies for transient tool errors.
- Fallback to a simpler model or hand-off to a human.
- Audit log of every tool call.
1.8 The three agent principles (from the source)
- Simplicity — minimum viable pattern.
- Transparency — surface planning steps to the user.
- Tool documentation and testing — invest in the agent-computer interface (ACI). Anthropic's SWE-bench team "spent more time optimizing our tools than the overall prompt." Small tool-interface changes (e.g., requiring absolute paths) often beat prompt tweaks.
Common question shapes
- "Given this multi-step workflow, which pattern is most appropriate?" → Match dynamism to pattern.
- "Orchestrator made a bad plan. Most likely cause?" → Vague subtask briefs, missing tool descriptions, too many tools.
- "Two subagents need to share data — how?" → They don't directly; the orchestrator integrates.
- "How do you bound an agent's runaway behavior?" → Iteration cap + permission denies + human gate for destructive ops.
Cheatsheet
- Simplest pattern that works. Don't reach for agents when a workflow suffices.
- Specialize workers, generalize the orchestrator.
- Stateless tools, state-aware app.
- Confirm before destruction.