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1. What distinguishes a “Trigger” in automation workflows?
A) A post-run summary that explains why an automation failed. B) The condition or event that starts a workflow (e.g., app event, schedule, or manual input). C) A branch that splits a workflow into parallel paths. D) A transformation step that cleans or reshapes data.
2. Within “Actions,” where do filters, paths, and transforms fit?
A) They’re part of Change History and only appear after a run completes. B) They’re optional debug helpers attached to webhooks. C) They define how triggers are scheduled weekly or monthly. D) They’re logic steps inside Actions that refine flow (filter), branch (paths), and reshape data (transform).
3. “Automation” vs “AI workflow” vs “AI Agent”: which framing aligns?
A) They’re synonyms; the course uses them interchangeably. B) Automations are for B2B; agents are for B2C; AI workflows are internal only. C) Automations run predefined logic; AI workflows add AI steps; AI Agents combine instructions, tools, memory/knowledge, and cooperation for adaptive behavior. D) AI Agents are only a UI layer on top of Change History.
4. When a flow “mysteriously” changes behavior after edits, what’s the first artifact to review to see configuration changes over time?
A) Change History. B) Trigger schedules. C) Path conditions inside Actions. D) External API rate limits.
5. What’s the recommended high-level order of thinking?
A) Start with Actions, then guess a Trigger, then document later. B) Begin with system limitations, then write prompts, then add webhooks. C) Identify the Trigger → outline Actions (including filters/paths/transform) → test and iterate. D) Skip testing; rely on Change History to fix issues post-launch.
6. What role do webhooks play in connecting systems that don’t integrate natively?
A) They’re a visual canvas for mapping processes only. B) They accept incoming HTTP calls to trigger workflows with payload data, bridging otherwise disconnected apps. C) They provide a nightly export of Change History. D) They are a replacement for APIs in all cases.
7. Why use Process Mapping / Canvas before building complex workflows?
A) To visualize triggers, actions, branches, and data flow so complexity is clear before implementation. B) To schedule all triggers on the same minute for easier logs. C) To replace webhooks with diagrams. D) To bypass testing since the map guarantees correctness.
8. Which set correctly lists core AI Agent components!
A) Schedules, actions, transforms, API keys. B) Embeddings, spreadsheets, CRON, CSS. C) Instructions, abilities, tools, knowledge, memory, and cooperation. D) Change History, retries, webhooks, filters.
9. The course stresses “Test, test, test; iterate, iterate, iterate.” Practically, what does this imply for building AI-infused workflows/agents?
A) Most issues can be deferred to Change History reviews after go-live. B) One prompt and a single path is enough if the trigger is reliable. C) Prompts shouldn’t change once an agent ships. D) Rapid, repeated validation of logic, prompts, and edge cases, refining after each run.
10. In the “AI Product Mindset” framework, what distinguishes building with AI from building AI products?
A) Building with AI means integrating AI into product management tools, while building AI products means working only on infrastructure models. B) They’re identical approaches focused mainly on replacing manual work with LLMs. C) Building with AI always requires coding; building AI products does not. D) Building with AI means using AI as a lever to enhance workflows or creativity, whereas building AI products means the AI capability itself is the product’s core value.
