Strategy question
You can only fund one new first-party app experience in the next half. How would you choose what to build inside ChatGPT or Codex so it solves a real user workflow, showcases the ecosystem's value to third-party developers, and works for both consumer and enterprise users? Walk through your prioritization framework, inputs, and key tradeoffs.
- OpenAI
- Strategy
- Hard
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What this question tests
Strategic prioritization across consumer and enterprise needs, and the ability to justify an ecosystem signaling investment, not just a feature choice.
How to approach it
- Define the evaluation criteria upfront: real workflow value, ecosystem signal to third party developers, and dual applicability to consumer and enterprise users.
- Generate candidate experiences grounded in known usage patterns, for example a research or coding adjacent workflow already showing organic demand inside ChatGPT or Codex.
- Score each candidate against the three criteria, being explicit that an experience with no ecosystem signaling value is a weaker platform bet even if it drives short term engagement.
- Check technical and safety feasibility given current model capability, since an ambitious idea the model cannot reliably support is not truly worth a half's investment.
- Pick one and justify it with the criteria, naming what made it beat the runner up.
- Define the v1 scope and the metric that would prove it justified the investment.
What a strong answer includes
- Names concrete candidate experiences rather than staying abstract, and explains why the chosen one beat the alternatives.
- Explicitly addresses the ecosystem signaling criterion, not just user value, since this is a stated requirement.
- Shows dual audience thinking, naming what makes the experience work for both a consumer and an enterprise user.
- Defines a success metric that would validate the bet, such as third party integration volume or workflow completion rate.
Common mistakes
- Picking a feature purely on consumer appeal and ignoring the ecosystem signaling requirement.
- Staying abstract instead of naming a real candidate experience and why it won.
Likely follow-up questions
- What would you cut from the v1 scope if engineering capacity were halved?
- How would you know within the first month if this bet was working?
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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