Feedback and Continuous Improvement Questions

This topic assesses a candidate's approach to receiving and acting on feedback, learning from mistakes, and driving iterative improvements. Interviewers will look for examples of critical feedback received from managers peers or code reviews and how the candidate responded without defensiveness. Candidates should demonstrate a growth mindset by describing concrete changes they implemented following feedback and the measurable results of those changes. The scope also includes handling correction during live challenges incorporating revision requests quickly and managing disagreements or design conflicts while maintaining professional relationships and advocating for sound decisions. Emphasis should be placed on resilience adaptability communication and a commitment to ongoing personal and team improvement.

MediumTechnical

0 practiced

How do you mentor a junior engineer who becomes defensive when receiving feedback during reviews? Provide a three-step coaching plan with language examples, activities over a 90-day timeline, and measurable indicators of improvement.

MediumTechnical

0 practiced

You implemented a change after receiving feedback but later metrics did not improve. Describe a step-by-step diagnostic approach to determine whether the change was implemented correctly, whether the metric selection is inappropriate, or whether external factors caused the lack of improvement.

EasyTechnical

0 practiced

List three effective ways to ask for feedback after a sprint retrospective or pull request, include example phrasing for each, and explain why each approach tends to produce actionable responses instead of vague commentary.

EasyTechnical

0 practiced

During a pair-programming session your partner suggests switching algorithms mid-session. How do you respond to that feedback in the moment while keeping the session collaborative and productive? Provide the in-the-moment steps you would take and how you'd evaluate the approach afterwards.

MediumTechnical

0 practiced

Design a simple Python script (describe algorithm and inputs/outputs; full code not required) that consumes PR comments or git logs and outputs the top five most common feedback themes (e.g., naming, tests, performance). State assumptions, key steps, and edge cases you would handle for noisy data.

Unlock Full Question Bank

Get access to hundreds of Feedback and Continuous Improvement interview questions and detailed answers.

Join thousands of developers preparing for their dream job.