← Anthropic Interview Insights
I pulled from a real situation where I had to cut scope and reprioritize without much guidance from above.
Start by clarifying the constraints and aligning on the highest-impact goal, then describe how you ruthlessly prioritize and creatively use available resources. Emphasize communication, incremental delivery, and learning loops to keep momentum despite limitations.
Pro tip: Show that you proactively re-scope or simplify the problem rather than just working harder with less—this demonstrates strategic thinking and prevents burnout. At Anthropic, highlight how you balance speed with safety and quality, even under resource constraints.
Quickly identify what resources are missing (time, people, compute) and what the single most important outcome is. Align with stakeholders on what 'moving forward' means in this context.
Use a framework like MoSCoW or impact/effort to cut non-essential work. Focus on the smallest deliverable that provides value or learning.
Reuse code, tools, or knowledge from past projects. Automate repetitive tasks to free up time. Consider open-source or internal solutions instead of building from scratch.
Keep stakeholders informed about trade-offs and progress. Be transparent about risks and ask for help or reprioritization when needed.
Ship small, testable increments to gather feedback early. Use learnings to refine the plan and maintain momentum.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Brought up using Claude to streamline some workflow stuff, which felt relevant given the company.
Emphasize that engineers can and should give product feedback by grounding it in user impact, data, and technical feasibility, while respecting the PM's ownership of prioritization. Describe a structured process: understand the product context, gather evidence, frame feedback constructively, and collaborate through the right channels.
Pro tip: Frame feedback as questions or hypotheses rather than directives—e.g., 'I noticed X; could this be an issue for users who do Y?'—which invites collaboration instead of defensiveness. Also, tie your feedback to business or user metrics the PM cares about.
Before giving feedback, ensure you understand the product goals, target users, and success metrics. This allows you to frame feedback in terms of user impact and business value, not just personal preference.
Collect concrete examples, user reports, analytics, or technical constraints that support your observation. Evidence makes feedback objective and actionable.
Present your feedback as observations and questions, focusing on the problem rather than the solution. Acknowledge the PM's expertise and the trade-offs they manage.
Use appropriate forums: direct 1:1 for sensitive topics, team channels for broader discussion, or design reviews for structured critique. Avoid ambushing or public criticism.
Offer to help validate or prototype solutions if relevant. Follow up to see how feedback was received and whether it led to changes, showing you care about outcomes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.