Strategy question
How would you drive adoption of Glean Agents beyond search?
- Glean
- Strategy
- Hard
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What this question tests
Product-led expansion strategy: moving users from a passive search habit to actively adopting a newer, more complex agent capability.
How to approach it
- Clarify the gap: search is a low-effort, familiar habit; Agents require users to configure or trust an automated workflow, a bigger behavioral leap.
- Identify the bridge: surface agent suggestions directly inside search results, where a user's repeated query pattern suggests a task that could be automated.
- Lower the setup barrier with pre-built agent templates for common cross-team tasks, like summarizing weekly project updates or triaging support tickets.
- Target power users first, such as ops or program managers doing repetitive cross-tool tasks, who have the clearest ROI and can become internal champions.
- Build trust incrementally, letting an agent run in a suggest-and-approve mode before fully autonomous mode, similar to how other AI agent products build confidence.
- Define success as percentage of active searchers who create or use at least one agent monthly, and time saved per agent run as the core value metric.
What a strong answer includes
- Identifies the real adoption barrier (behavioral leap from passive search to active automation) instead of assuming agents will be adopted automatically.
- Proposes a concrete bridge (surfacing agent suggestions inside existing search behavior) rather than a separate, disconnected feature launch.
- Targets a specific power-user segment with clear ROI as the initial wedge, a realistic adoption strategy.
- Uses a suggest-and-approve trust ramp, consistent with how autonomy-building works across other AI agent products.
- Defines a funnel metric (search users converting to agent users) that directly measures the expansion being asked about.
Common mistakes
- Assuming agent adoption will follow automatically from search popularity without a specific conversion strategy.
- Ignoring the trust-building step needed before users hand off tasks to an autonomous agent.
Likely follow-up questions
- Which team or persona would you target first for agent adoption?
- How would you measure trust in the agent over time?
- What would you do if agent adoption stalled after initial trials?
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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