Product design question
A ministry outside the U.S. asks Scale to build a bespoke GenAI application on top of its proprietary data, but end users cannot clearly explain where the workflow is breaking today. How would you run the first client workshops to uncover the real job-to-be-done, select the highest-value use case, define an MVP, and align the client with Scale’s engineering, MLE, and ops teams on scope?
- Scale AI
- Product design
- Hard
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What this question tests
Discovery skill in a genuinely ambiguous environment: can you run workshops that surface the real job-to-be-done when end users cannot articulate it, and align a multi-functional internal team on scope.
How to approach it
- Start workshops with observation and specific scenario walkthroughs rather than open questions, since users who cannot explain the breakdown can often show it when walked through a recent real task.
- Use a small set of structured prompts, like the last time something went wrong here and what happened next, to surface the actual friction points instead of abstract pain points.
- Map the candidate use cases that emerge and score them on value (time or cost saved), feasibility given the proprietary data available, and how clearly it maps to Scale's engineering and MLE strengths.
- Define the MVP narrowly around the single highest-scoring use case, explicitly excluding adjacent asks that emerged but did not score as highly.
- Align the client with Scale's engineering, MLE, and ops teams by presenting the MVP scope and the evidence behind it in one shared workshop readout, so internal teams commit to the same scope the client agreed to.
What a strong answer includes
- Uses concrete elicitation techniques, scenario walkthroughs and recent-incident prompts, instead of assuming users can just describe their pain abstractly.
- Scores candidate use cases on explicit criteria (value, feasibility, data readiness) rather than picking based on client enthusiasm alone.
- Closes the loop by aligning both the client and Scale's internal teams on the same scoped MVP in one readout, avoiding drift later.
Common mistakes
- Relies on open-ended interview questions alone when the prompt states users cannot clearly explain the problem.
- Scopes the MVP broadly to avoid disappointing stakeholders, instead of committing to one use case.
Likely follow-up questions
- What would you do if the highest-scoring use case requires data the ministry cannot actually provide.
- How would you handle disagreement between client stakeholders on which use case matters most.
More product design questions
- You're asked to deliver an enterprise GenAI application on Scale’s platform in 10 weeks for a customer with ambiguous requirements, strict security/compliance review, and multiple stakeholder groups. How would you scope the v1, convert discovery into clear requirements, run testing and pilot rollout, and decide what to cut versus what must ship for launch?Scale AI · Product design · Hard
- Scale forward deploys to understand real workflows before building. If future end-users in a government agency have different needs from the senior sponsor who is funding the project, how would you gather the right feedback, separate core pain points from feature requests, and turn that into a prioritized roadmap for the first release?Scale AI · Product design · Medium
- A ministry outside the U.S. has several candidate workflows for a bespoke AI solution, but its leadership team is not aligned on which problem is highest priority. How would you run discovery and design workshops to identify the best workflow to target, define a measurable success outcome, and decide whether Scale should build an AI application on top of existing models or invest in a custom LLM?Scale AI · Product design · Hard
- A prospective customer wants an agentic or RL data solution but can only describe the desired outcome, not the tasks, feedback signals, or delivery constraints. How would you run discovery, separate must-have from nice-to-have requirements, and turn the conversation into a concrete plan for product, operations, and next customer validation?Scale AI · Product design · Medium
- You need to ship the first agentic workflow product for defense analysts on a controlled network where internet access, model updates, and human review are tightly constrained. What is the MVP, which user/job would you target first, and what tradeoffs would you make among agent autonomy, user experience speed, and security/risk controls?Scale AI · Product design · Hard
- A defense customer asks for "an AI assistant for analysts" but cannot clearly describe the day-to-day workflow or failure modes. How would you work with engineers and ML teammates to turn that vague request into a concrete v1 product, including the user task you would target, the human-in-the-loop design, and what you would explicitly leave out?Scale AI · Product design · Hard
More questions from Scale AI
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