Question Categories

Behavioral Questions#

Behavioral questions assess how you have handled real situations in the past. Altrixy coaches you using the STAR method (Situation, Task, Action, Result).

Example questions:
- "Tell me about a time you had to make a difficult prioritization decision."
- "Describe a situation where you disagreed with a stakeholder. How did you handle it?"
- "Walk me through a product failure you experienced and what you learned."

What the AI evaluates:
- Clear situation and context setting
- Specific actions you took (not the team)
- Quantified results and impact
- Genuine reflections and learnings

Frameworks the AI suggests:
- STAR (Situation, Task, Action, Result)
- CAR (Challenge, Action, Result)
- SOAR (Situation, Obstacle, Action, Result)

Product Sense Questions#

Product Sense questions test your ability to think about product design, improvement, and strategy.

Sub-categories:

Product Design: "Design a product for elderly people to stay connected with family."
- AI evaluates: user empathy, problem framing, creative solutions, trade-offs

Product Improvement: "How would you improve Instagram Stories?"
- AI evaluates: user segmentation, pain point identification, prioritization, metrics

Product Strategy: "Should Spotify launch a hardware product?"
- AI evaluates: market analysis, competitive positioning, business model, risk assessment

Frameworks the AI suggests:
- CIRCLES (Comprehend, Identify, Report, Cut, List, Evaluate, Summarize)
- Double Diamond (Discover, Define, Develop, Deliver)
- Jobs-to-be-Done

Technical Questions#

Technical questions assess your ability to work with engineering teams and understand system design concepts.

Sub-categories:

System Design: "Design the backend for a ride-sharing app."
- AI evaluates: architecture decisions, scalability considerations, trade-offs

Metrics & Analytics: "How would you measure the success of a new feature?"
- AI evaluates: metric selection, leading vs lagging indicators, counter-metrics

A/B Testing: "Design an experiment to test a new onboarding flow."
- AI evaluates: hypothesis formation, sample size, duration, success criteria, statistical rigor

SQL & Data: "How would you query to find the most active users?"
- AI evaluates: query logic, join understanding, aggregation, edge cases

Estimation Questions#

Estimation (Fermi) questions test your ability to break down ambiguous problems into solvable components.

Example questions:
- "How many piano tuners are in Chicago?"
- "Estimate the annual revenue of Starbucks in the US."
- "How many WhatsApp messages are sent per day globally?"

What the AI evaluates:
- Problem decomposition into manageable parts
- Reasonable assumptions with justification
- Correct mathematical logic
- Sanity checks on the final answer

Approach the AI teaches:
1. Clarify the question and define scope
2. Break down into sub-estimates
3. Make and state assumptions
4. Calculate bottom-up or top-down
5. Sanity check the result
6. Acknowledge uncertainty and range

Difficulty Levels#

Each category offers three difficulty levels:

The AI adjusts its evaluation criteria based on difficulty level. A good answer at Easy level might only score "adequate" at Hard level.

Recommended Practice Schedule#

For systematic interview preparation, follow this weekly schedule:

Timeline recommendations:
- 4 weeks out: Start with Easy, focus on frameworks
- 2 weeks out: Move to Medium, focus on depth and specifics
- 1 week out: Hard questions, focus on time management and polish
- Day before: Light warm-up with Easy questions for confidence