AI & Technical question
How would you measure whether Ramp's AI agents make better decisions than humans?
- Ramp
- AI & Technical
- Hard
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What this question tests
Tests AI evaluation design for a genuinely hard question: proving an AI agent's decisions are better than a human's, not just faster.
How to approach it
- Define better precisely for the decision type: for spend approval, better could mean fewer errors, faster processing, and equal or lower fraud rate than human review.
- Build a controlled comparison: run the agent and a human reviewer on the same set of real historical decisions, and compare outcomes on accuracy, consistency, and speed.
- Use ground truth where possible: for cases with a known correct answer, like a policy violation that was later confirmed, measure which decision maker got it right more often.
- Account for consistency, not just average accuracy: agents may be more consistent across similar cases than humans, who can vary by fatigue or individual judgment, and this consistency itself has value.
- Track downstream outcomes, not just decision correctness: for example, fraud caught, cost avoided, or employee satisfaction with how quickly requests were processed.
What a strong answer includes
- Uses a real historical decision set with ground truth outcomes for direct comparison, rather than relying on subjective impressions of which decision maker performed better.
- Explicitly values consistency as a distinct dimension from average accuracy, recognizing agents may reduce variance even without being more accurate on average.
- Measures downstream business outcomes, like fraud caught or cost avoided, connecting decision quality to real impact rather than treating correctness as abstract.
Common mistakes
- Comparing agent and human decisions without any ground truth, relying only on subjective judgment of which was better.
- Ignoring consistency as a distinct value from average accuracy.
Likely follow-up questions
- How would you handle decisions where there is no clear ground truth to compare against?
- What would you do if the agent was more consistent but slightly less accurate than human reviewers on average?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 1: Foundations: the model and the decisions it forces on you
- Chapter 8: Evals: define good and make the number defensible
- Chapter 6: Agents and agentic architecture