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Are Right, A Lot: Amazon Interview Questions and Answers

Are Right, A Lot is the most misread of Amazon's 16 leadership principles. Candidates hear the name and prepare a story about being correct. Interviewers are listening for something else: how you make decisions with incomplete information, and what you do when the evidence says you were wrong.

This guide covers the official wording, what the principle actually tests, examples of good judgment from engineering, product, data and business roles, 14 interview questions, a sample STAR answer, and the follow-up questions that separate a prepared story from real judgment.

The official wording from Amazon

Leaders are right a lot. They have strong judgment and good instincts.

That is how the principle opens on Amazon's leadership principles page. The sentence that follows is the one that matters in an interview: leaders seek diverse perspectives and work to disconfirm their own beliefs. In other words, Amazon's definition of being right a lot is a process, not a track record. People who are right a lot are usually the people who look hardest for reasons they might be wrong, and change their mind fastest when they find one.

What Are Right, A Lot means in practice

  • You make calls with around 70 percent of the information rather than waiting for all of it, and you can say what you knew and did not know at the time.
  • Before committing to a position you ask the person most likely to disagree with it, and you take their argument seriously.
  • You look for the cheap test that would prove your idea wrong, and you run it before the expensive build.
  • You separate your ego from your ideas: when the data moves, you move with it, in public, without defending the old position.
  • You keep a record of your own calls, so your sense of your judgment is based on evidence rather than memory.

Are Right, A Lot examples at work

An engineering lead has to choose between two database designs for a new service with the launch date fixed. She writes down the three assumptions each design depends on, spends two days load-testing the one assumption she is least sure about, and picks the design that survives. Six months later, one of her other assumptions turns out wrong, and because she wrote them down, the team knows exactly what to revisit.

A product manager is convinced a pricing page redesign will lift conversion. Instead of shipping it, he asks the analyst who has argued against it to design the A/B test. The redesign loses by a small margin. He kills it, writes up what he got wrong, and the next redesign, built on the analyst's objection, wins.

A data scientist's model says a marketing channel is unprofitable; the channel owner insists it works. Rather than pick a side, she digs into why the two views differ and finds the model is missing a 30-day attribution window. With the correction, the channel is marginal rather than unprofitable. Both sides were partly right; the judgment was in finding out why they disagreed.

A sales director forecasts the quarter at 110 percent of target based on instinct, then checks his own last eight forecasts and finds he averages 12 percent optimistic. He submits 98 percent. The quarter closes at 99.

Are Right, A Lot interview questions

Direct questions

  • Tell me about a decision you made with incomplete information. How did you decide?
  • Describe a time you were convinced you were right and turned out to be wrong.
  • How do you seek out perspectives that challenge your own? Give a real example.
  • Tell me about a time you changed your mind because of data or a colleague's argument.
  • Describe your most difficult judgment call of the last year.
  • Tell me about a time you disagreed with the data. What did you do?
  • When did you make a high-impact decision quickly? Would you make it again?

Questions that test it indirectly

  • Tell me about a time you had to choose between two good options.
  • Describe a decision you made that others thought was risky. How did you know it was not?
  • Tell me about a time your instinct and the evidence pointed in different directions.
  • How do you know when you have enough information to decide?
  • Tell me about a time you deliberately looked for evidence against your own plan.
  • Describe a time a junior colleague changed your mind.
  • What is a decision you got right that you could not have justified at the time?

A sample STAR answer

Question: "Describe a time you were convinced you were right and turned out to be wrong."

Situation: As tech lead on a mobile app, I was certain our crash rate on older Android devices was caused by a third-party analytics library. I had seen similar issues at a previous company and the stack traces looked familiar.

Task: I needed to decide whether to spend the sprint replacing the library, which meant delaying a feature the business was counting on.

Action: Before committing the sprint, I did two things I now do by habit. I asked the engineer who had argued against my theory in standup to spend a day trying to prove me wrong, and I pulled crash data by device model rather than by OS version. Her investigation and the data told the same story: the crashes clustered on two device models with a known memory bug, and the library was a bystander. I dropped my plan in the same meeting, said so plainly to the team, and we shipped a targeted memory fix for those devices in three days instead of a sprint.

Result: Crash rate on the affected devices fell by about 80 percent, the feature shipped on time, and I kept the library. The bigger result was the habit: I now write down what would have to be true for my theory to be right before I ask anyone to act on it.

Why this answer works

  • The candidate was wrong and says so without excuses, which is the point of the question.
  • The disconfirmation step is concrete: a named colleague, a day of effort, a different cut of the data.
  • The result includes the process change, which shows judgment improving rather than a one-off save.

What the interviewer probes next

  • "What did you know at the time, and what did you not know?" Separate the two cleanly.
  • "Who disagreed with you, and what did you do with their view?" If nobody disagreed, the interviewer will wonder whether you asked.
  • "How quickly did you change course once the evidence came in?" Days is good; a quarter is a red flag.
  • "What is your track record on calls like this?" Have a rough honest number. Nobody is right every time.
  • "What would you do differently?" For a good call, name the part that was luck.

Common mistakes

  • Answering as if you are never wrong. This is the fastest way to fail the principle.
  • Bringing an "I was wrong" story where the mistake was trivial or someone else's.
  • Describing a decision with no account of the alternatives you rejected.
  • Treating "seek diverse perspectives" as a meeting you held rather than an argument you took seriously.
  • Confusing being decisive with being right. Amazon rewards speed on reversible decisions, not stubbornness on irreversible ones.

Related leadership principles

  • Dive Deep: the device-level data cut in the sample answer is Dive Deep in service of judgment. Expect the same story to be scored against both.
  • Have Backbone; Disagree and Commit: Are Right, A Lot is about forming the right view; Backbone is about arguing for it, then committing when you lose.
  • Bias for Action: deciding at 70 percent information is where these two principles meet.

All 16 principles, with questions for each, are in the Amazon leadership principles guide.

Pair one good call and one honest miss in your story bank, tighten both with the STAR method, then get matched with a coach who will push on your judgment the way an Amazon interviewer does.