The question most Microsoft candidates get wrong
Most people preparing for a Microsoft interview spend the bulk of their time on LeetCode and system design. The behavioral questions feel like a checkbox. And within the behavioral prep, the Growth Mindset question feels like the easiest one: just say you are working on something, mention a course, move on.
The data from live Microsoft interviews does not support that approach.
Final Round AI analyzed 4,921 live interview sessions at Microsoft Corporation captured through Interview Copilot, its real-time AI assistance tool used during actual job interviews, not practice runs. The most frequently repeated specific question across all roles and seniority levels was: "What have you identified as your greatest improvement areas, and what have you done to improve them?"
That question averaged 51.7 out of 100. The overall Microsoft average is 57.8. The Growth Mindset question is both the most common and the most underperformed specific question in the dataset.
Why behavioral questions score higher than technical ones at Microsoft
Here is the counterintuitive finding from 4,921 sessions: behavioral STAR questions averaged 64.8 out of 100 at Microsoft. Technical knowledge questions, which made up 4,361 of the 4,921 sessions analyzed, averaged 57.3. System design averaged 61.5 across 105 sessions. Culture and motivation questions, the lowest category, averaged 50.0 across 21 sessions.
Most candidates assume technical questions are the safer territory because they feel more objectively measurable. The data suggests the opposite. Candidates who apply the STAR format to behavioral questions produce more complete, structured answers than they do for open-ended technical questions, which often lack a clear completion point. When a technical question asks "what are the principles of REST API design?" there is no natural endpoint to a strong answer. When a behavioral question asks "tell me about a time you had to convince a skeptical stakeholder," the STAR structure closes naturally.
The practical implication is that candidates arriving at a Microsoft loop are better prepared for behavioral questions than for the depth of technical follow-up that Microsoft engineers actually probe. The 7.5-point gap between behavioral (64.8) and technical (57.3) scores points directly to where preparation time is being allocated and where it is not.
The Growth Mindset question requires a different kind of answer
The "greatest improvement areas" question is not a standard weakness question and should not be prepared like one. A weakness question asks you to name something and reassure the interviewer you are managing it. The Growth Mindset version asks you to demonstrate that you have an active relationship with your own development, that you diagnose gaps systematically, and that you build learning plans rather than just acknowledging that you are imperfect.
Answers that score in the 30 to 45 range at Microsoft tend to name a soft skill in vague terms: "I can be a perfectionist," "I am still developing my public speaking," "I sometimes take on too much." There is no evidence of active development, no specific learning activity, no measurement of progress.
Answers that score in the 60 to 75 range name a specific technical or professional capability, explain why the candidate identified it as a gap (usually a concrete situation that revealed it), describe the specific steps taken to address it (a course, a mentoring relationship, a side project, a deliberate change in workflow), and note how progress is being measured. The key word in Microsoft's phrasing is "what have you done" (past tense, evidence required, not future intent).
This is where Microsoft diverges meaningfully from Amazon. Amazon's Leadership Principles questions use STAR format and ask for past behavior as evidence of future behavior. Microsoft's Growth Mindset question asks directly about self-awareness and active development trajectory. Candidates who only prep STAR stories may find themselves struggling with a question that is not asking for a story. It is asking for a current state of development.
The specific behavioral questions that appear most often at Microsoft
Beyond the Growth Mindset question, a set of behavioral questions appeared repeatedly across different Microsoft sessions in the dataset. "Tell me about a time when you had to make a decision in a lot of ambiguity" averaged 60.0 across 7 sessions. "Describe a situation when you disagreed with someone at work and how you resolved it" averaged 55.0 across 7 sessions. "Tell me about a time you experienced a conflict with a team member and how you resolved it" averaged 65.0 across 7 sessions.
The pattern in these scores is consistent with what Microsoft interviewers describe as their evaluation framework: they are looking for candidates who can navigate ambiguity, manage conflict collaboratively, and demonstrate growth from difficult situations. Questions about project ownership and deadline management scored the highest of any specific behavioral cluster, averaging 72.0 to 80.0 across the sessions where they appeared. Candidates with concrete delivery timelines and quantified outcomes in their stories outperform those who describe what they did without specifying what resulted from it.
Where Microsoft sits in the difficulty ranking
Across 4,921 sessions, Microsoft averaged 57.8 out of 100. That places it slightly above Amazon at 57.5, below Netflix at 59.2, and materially above Meta at 55.5. A lower average means harder conditions for candidates, so Microsoft sits in the middle of the six major tech companies in this dataset.
The year-over-year trend matters for candidates preparing now. Microsoft difficulty was 61.3 in 2023 across a small sample of 84 sessions. It dropped to 57.5 in 2024 as the dataset grew to 4,018 sessions and became more representative of the broader candidate population. In the first portion of 2025, across 819 sessions, it sits at 58.8.
That stability from 2024 to mid-2025 is notable because Amazon and Google both hardened over the same period. Amazon dropped from 58.5 in 2024 to 55.2 in mid-2025, a 3.3-point shift. Google dropped from 56.9 to 55.8, a 1.1-point shift. Both represent harder conditions for candidates relative to 12 months ago. Microsoft has held roughly flat, which means candidates with experience in a 2024 Microsoft loop are not facing a materially different bar in 2025.
Role-level differences at Microsoft
Among roles with 50 or more sessions in the dataset, Software Engineer averaged 54.2 across 1,141 sessions, the lowest of the major roles. This is consistent with the nature of the SWE loop: heavy emphasis on technical knowledge questions across LeetCode algorithms, system design, and cloud architecture.
Cloud Solution Architect Data Platform and AI averaged 69.0 across 427 sessions, the highest of the major roles. The format of these interviews tends to be more conversational and architecture-focused, which plays to candidates who can explain complex systems clearly rather than solve algorithmic puzzles from a standing start. Data Engineer averaged 66.8 across 175 sessions, also materially above the SWE benchmark. DevOps Engineer averaged 58.2 across 175 sessions, close to the overall Microsoft average.
The variance across roles matters because generic Microsoft interview preparation resources treat the loop as uniform. The data shows it is not. A Software Engineer preparing the same way as a Cloud Solution Architect candidate is either over-preparing on algorithms or under-preparing on system and cloud architecture, depending on the direction.
What this means for preparation
For Software Engineer candidates, the 54.2 average across 1,141 sessions signals that the technical portion of the loop is where the most preparation gap exists. Microsoft SWE questions span a wide range: LeetCode algorithms, system design, cloud architecture, and Azure-specific scenarios. Candidates who practice specific question categories separately will out-prepare those who rely on undifferentiated LeetCode volume.
For all Microsoft roles, the Growth Mindset question demands specific preparation that most candidates do not give it. Building one specific, evidence-backed answer for "what are your greatest improvement areas" will produce a higher score impact than three additional hours of LeetCode across sessions where this question appears. The question appeared in more sessions than any other specific question in the 4,921-session dataset. That is not an accident. It is a deliberate part of the loop.
The full breakdown, including question type distribution charts, year-over-year difficulty trends, and the complete role-by-role score breakdown, is in Final Round AI's research at https://www.finalroundai.com/blog/microsoft-interview-questions-live-session-data
How Microsoft compares to other companies on specific question types
One finding worth noting beyond the aggregate difficulty numbers: Microsoft's approach to behavioral questions is different from Meta and Google in the specific competencies it prioritizes. Meta interviews probe "impact and scale" heavily, which means behavioral stories without quantified business results tend to score lower. Google's behavioral questions emphasize problem decomposition and structured reasoning, which rewards candidates who can break down ambiguous situations methodically.
Microsoft's competency framework centers on growth mindset, customer obsession, and inclusive collaboration. The behavioral questions in the dataset reflect this: conflict resolution with teammates, decision-making under ambiguity, and proactive identification of customer impact appear far more often at Microsoft than questions about quantitative impact or algorithmic decomposition. This means candidates who are building a single behavioral story bank for multiple tech companies need to weight their Microsoft stories differently from their Meta or Google stories.
For Microsoft specifically: a strong story about a project where you actively sought feedback, changed your approach based on what you learned, and measured the improvement afterward will score better on the Growth Mindset question than any story that is only about external success. Microsoft wants to see the internal learning process, not just the outcome.
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