Strategy question
Glean supports enterprise customers and partners who may build mission-critical workflows on its APIs. Describe a decision framework for when you would allow a breaking API change versus preserving backward compatibility. What factors would you weigh, who would you involve, and what migration plan, versioning policy, and deprecation timeline would you put in place to minimize customer disruption?
- Glean
- Strategy
- Hard
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What this question tests
Tests building a governance framework for API breaking changes, balancing platform evolution against partner and customer disruption, with a concrete versioning and deprecation process.
How to approach it
- Set the default bias against breaking changes, treating backward compatibility as the norm, and requiring an explicit, documented justification, like a security fix or a fundamentally broken contract, to break it.
- Define the factors to weigh: number of integrations affected, migration effort for partners, severity of the reason for the change, and whether a non-breaking alternative, like additive fields, exists.
- Involve the right stakeholders before deciding: partner engineering leads for major integrations, customer success for accounts with heavy API usage, and internal platform engineering for technical feasibility of alternatives.
- Adopt a clear versioning policy, for example semantic versioning with a stated support window for each major version, so partners can plan migrations predictably.
- Set a deprecation timeline as policy, for example a minimum notice period and parallel support of old and new versions for a defined window, rather than deciding case by case.
- Build a migration plan for every breaking change: clear documentation, a migration guide, and direct outreach to the highest-usage affected partners before the deprecation clock starts.
What a strong answer includes
- Sets backward compatibility as the default with a high bar to override it, rather than treating breaking changes as routine engineering decisions.
- Proposes a standing versioning and deprecation policy, not ad hoc case-by-case decisions, giving partners predictability to plan around.
- Explicitly checks for a non-breaking alternative, like additive fields, before accepting a breaking change as necessary.
- Requires proactive outreach to the highest-usage affected partners, not just documentation, before the deprecation clock starts.
Common mistakes
- Deciding breaking changes case by case with no standing policy, leaving partners unable to plan.
- Skipping a check for non-breaking alternatives before committing to break compatibility.
- Publishing a deprecation notice without direct outreach to the partners most affected.
Likely follow-up questions
- How would you handle a partner who can't meet the migration deadline?
- What would justify breaking a stable, heavily used endpoint despite this bias against it?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop