Product design question
How would you help users trust Lindy Autopilot to act inside their apps (Gmail, HubSpot)?
- Lindy
- Product design
- Hard
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What this question tests
Tests product design for trust when an AI agent takes autonomous actions inside a user's real accounts and data.
How to approach it
- Identify the core fear: a user worries Autopilot will send a wrong email, delete a record, or take an irreversible action inside Gmail or HubSpot without oversight.
- Segment actions by risk: read only actions like checking a calendar are low risk, while sending an email or updating a CRM record externally are higher risk.
- Design a graduated autonomy model: start new agents in a review and approve mode, and only grant full autopilot after a track record of correct suggestions.
- Make every autonomous action visible and reversible where possible, with a clear activity log and an undo path for actions like a sent draft that can still be recalled.
- Add a permission model scoped to exactly what each agent needs, so a lead follow up agent cannot touch unrelated HubSpot records it was never meant to access.
- Confirm with the interviewer whether the priority use case is Gmail, HubSpot, or a broader integration set, since risk profiles differ by system.
What a strong answer includes
- Proposes a graduated trust model, starting supervised and earning autonomy over time, rather than asking users to trust the agent fully from day one.
- Makes agent actions auditable with a clear log, so a user can see exactly what Autopilot did and when, building confidence through transparency.
- Scopes permissions tightly per agent rather than granting broad account access, limiting the blast radius of any single mistake.
- Distinguishes reversible actions from irreversible ones and gates only the irreversible ones behind explicit confirmation.
Common mistakes
- Proposing full autonomy from the start, which ignores the real trust barrier for actions inside a user's email or CRM.
- No audit trail or visibility into what the agent actually did, leaving users unable to verify correct behavior.
- Granting broad account permissions instead of scoping access to what each specific agent needs.
Likely follow-up questions
- How would you decide when an agent has earned full autopilot status?
- What would you do if a user's trust was broken by one bad autonomous action?
- How would you handle a HubSpot record an agent should never touch?
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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