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1. What is the single most important idea behind building a personal AI operating system for professional work?
A) Using AI consistently across many sessions, so it accumulates familiarity with your work over time. B) The operating system around the model — context, connections, skills, automations, and memory, tied together by a weekly audit — is what makes AI valuable, not the model itself. C) Selecting the most capable underlying AI model, since more powerful models produce better product management outputs. D) Connecting the AI to as many tools and integrations as possible, since more connections create more intelligence.
2. What is the key difference between identity.md and context.md in the Context layer?
A) Merging identity.md and context.md into a single file reduces maintenance without losing anything important. B) identity.md holds durable information like writing style, principles, and non-negotiables, but should be refreshed every quarter just like context.md. C) identity.md holds durable information — writing style, principles, and non-negotiables — that travels between jobs, while context.md holds the current operating environment — company, priorities, and open questions — and should be refreshed quarterly. D) context.md holds durable personal principles and banned phrases, while identity.md tracks the current quarter's company priorities.
3. What is the role of the Router (CLAUDE.md) in the Context layer?
A) CLAUDE.md is a comprehensive file containing all identity and context details in one place, replacing the need for identity.md and context.md. B) CLAUDE.md's main job is to define global operating rules; it has no role in pointing to other context files. C) CLAUDE.md is a router that lists which files exist, but carries no operating rules of its own — those live only in identity.md. D) CLAUDE.md is a lightweight index that points to the relevant files, like identity.md and context.md, and defines global operating rules.
4. How should the Connections layer document the tools available to the AI?
A) Connections should describe each tool by the purpose it serves — for example, "where specs live" — rather than by brand name, so the AI can combine information across systems. B) Connections should list both the tool's brand name and its function, giving equal weight to identifying the tool and what it's used for. C) Documenting login details and access permissions for each tool matters most; the tool's purpose is secondary. D) The more tools and integrations connected to the AI, the more intelligent it becomes.
5. What is the Third-Use Rule for turning a prompt into a Skill?
A) Recognize repetition on the first use and convert it into a skill on the second use, skipping the need to ever write a raw prompt. B) Any prompt used more than once should eventually become a skill, though the framework doesn't specify a particular trigger point. C) Skills should be created upfront, before a prompt has ever been used manually, to save time later. D) First use, write the prompt; second use, recognize the repetition; third use, convert it into a reusable skill.
6. What makes a good Skill more than just an output generator?
A) A good skill validates required inputs — like a target user and customer evidence — before generating output, and refuses to run without them; refusal is a feature, not a bug. B) A good skill enforces a consistent output structure, such as requiring specific sections in a PRD, without needing to check whether the right inputs were provided. C) A good skill should always generate output, even with incomplete inputs, to keep the workflow moving quickly. D) A good skill validates inputs and can refuse to run, but that refusal is a workaround for weaknesses that should eventually be removed as the skill matures.
7. What must every Automation have, according to the Core Rule?
A) Automations should be as comprehensive and detailed as possible so users get the full picture every time. B) Every automation must have a hard constraint — like exactly 5 bullets, a maximum word count, or a rule that every number cites a source — otherwise outputs get too long and users stop reading. C) Automations should be reviewed in the Weekly OS Audit rather than constrained at creation time. D) Automations benefit from constraints like bullet limits, but these are optional refinements rather than a hard requirement.
8. What scale of Automations does the framework recommend?
A) Start with 1–3 automations, with no upper limit as the system matures. B) Start with as many automations as possible — the more coverage, the more valuable the system. C) Start with 1–3 automations, and cap active automations at a maximum of 5. D) There's no specific recommended number; teams should add automations whenever they think of a new one.
9. How should Memory be structured and saved?
A) Memory should capture USER and FEEDBACK information; temporary project facts and reference locations don't need to be tracked separately. B) Memory is organized into four types — USER, FEEDBACK, PROJECT, REFERENCE — and should never be saved automatically; every memory must be approved, typed, justified, and dated if temporary. C) The AI should save everything discussed automatically across conversations, since more memory means more personalization over time. D) Memory uses the four types — USER, FEEDBACK, PROJECT, REFERENCE — but can be saved automatically as long as it's periodically reviewed for accuracy.
10. What is the role of the Weekly OS Audit in the five-layer framework?
A) The Weekly OS Audit is the keystone of the framework — without it, the five layers don't self-maintain; as the documents put it, "five layers without the loop is just a stack." B) Once the five layers are built, no ongoing review is needed — the system runs itself indefinitely. C) The maturity model says to improve every layer equally each week, rather than focusing on any one weak point. D) A periodic review helps catch stale content, but it's an optional add-on rather than the most important concept in the framework.
