Product design question
How would you improve Microsoft OneNote?
- Microsoft
- Product design
- Easy
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What this question tests
Product sense for a legacy productivity tool competing against more modern, integrated alternatives.
How to approach it
- Pick a segment, for example students taking class notes versus professionals organizing meeting notes and research.
- Identify a pain point: notes become disorganized and hard to search across as the volume of notebooks grows over time.
- Prioritize search and retrieval over new note taking formats, since finding old notes is the more common daily frustration.
- Propose AI powered semantic search that finds notes by meaning, not just exact keyword match, plus auto tagging of note content.
- Add cross device sync reliability improvements, since a known pain point for OneNote users is inconsistent sync across devices.
- Define success as search success rate (finding the intended note on the first try) and reduction in reported sync conflicts.
What a strong answer includes
- Targets a specific, well known frustration, difficulty finding old notes, rather than proposing an unrelated new feature.
- Proposes a concrete technical mechanism, semantic search and auto tagging, rather than a vague 'better search' statement.
- Gives an illustrative number, e.g. assumes current keyword search finds the right note only 50 percent of the time, targeting 80 percent with semantic search.
- Addresses a second real, commonly reported issue, sync reliability, showing depth beyond a single surface level fix.
Common mistakes
- Proposing flashy new formatting features while ignoring the core search and retrieval frustration.
- Not naming a specific segment, treating all OneNote users as having identical needs.
- No metric tied to whether search or sync actually improved.
Likely follow-up questions
- How would semantic search work technically?
- How would you validate sync reliability actually improved?
- How does this compete with tools like Notion or Evernote?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop