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Complete Skill Assessment and Gap Analysis Tools

🎯 Comprehensive Competency Assessment Framework

360-Degree Assessment System

This comprehensive assessment framework provides detailed competency matrices, progress tracking, gap analysis tools, and readiness validation specifically designed for Amazon L6/L7 engineering manager interviews.

📊 Multi-Dimensional Competency Matrix

Core Assessment Dimensions

1. Technical Competency (40% of overall readiness) - System Design Architecture (15%) - Coding Proficiency (15%) - AWS and Cloud Knowledge (10%)

2. Leadership Competency (35% of overall readiness) - People Management (15%) - Strategic Leadership (10%) - Cross-functional Collaboration (10%)

3. Behavioral Leadership (25% of overall readiness) - Amazon Leadership Principles (20%) - Cultural Fit and Values (5%)

🏗️ Technical Competency Assessment

System Design Competency Matrix

L6 Engineering Manager Expectations:

Architecture Design (Score: 1-5)

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Component_Level_Systems:
  api_design: 
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design RESTful APIs with proper versioning, authentication, rate limiting"
    gap_areas: []

  database_design:
    current_level: ___/5
    target_level: 4/5
    evidence: "Understands SQL/NoSQL trade-offs, indexing strategies, normalization"
    gap_areas: []

  caching_strategies:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design multi-level caching with appropriate invalidation"
    gap_areas: []

  microservices_architecture:
    current_level: ___/5
    target_level: 3/5
    evidence: "Understands service boundaries, communication patterns, data consistency"
    gap_areas: []

Assessment Questions for System Design: 1. API Design: "Design the API for a social media platform. How would you handle authentication, rate limiting, and versioning?" 2. Database Architecture: "You have a read-heavy application with 10M users. How would you design the data layer?" 3. Caching Strategy: "Design a caching strategy for an e-commerce product catalog with frequent updates." 4. Scaling Challenges: "Your system needs to handle 10x more traffic. What are your scaling strategies?" 5. Trade-off Analysis: "Compare the trade-offs between microservices and monolithic architecture for a startup."

Scale and Performance (Score: 1-5)

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Performance_Optimization:
  load_balancing:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design load balancing strategies for different traffic patterns"
    gap_areas: []

  database_scaling:
    current_level: ___/5
    target_level: 4/5
    evidence: "Understands sharding, replication, read replicas"
    gap_areas: []

  cdn_and_edge:
    current_level: ___/5
    target_level: 3/5
    evidence: "Can design CDN strategy for global content delivery"
    gap_areas: []

  monitoring_observability:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design comprehensive monitoring and alerting systems"
    gap_areas: []

L7 Senior Engineering Manager Additional Expectations:

Platform Architecture (Score: 1-5)

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Platform_Level_Systems:
  multi_tenant_architecture:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design platforms serving multiple teams/organizations"
    gap_areas: []

  developer_platforms:
    current_level: ___/5
    target_level: 4/5
    evidence: "Understands platform-as-a-service design patterns"
    gap_areas: []

  distributed_systems:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can design consensus algorithms, distributed state management"
    gap_areas: []

  ecosystem_thinking:
    current_level: ___/5
    target_level: 4/5
    evidence: "Designs systems with extensibility and partner integration"
    gap_areas: []

Coding Competency Matrix

Algorithm Implementation (Score: 1-5)

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Core_Algorithms:
  arrays_strings:
    current_level: ___/5
    target_level: 4/5 # L6 target
    assessment: "Can solve 80% of medium array/string problems in 30 minutes"
    recent_problems_solved: ___
    time_efficiency: ___/5

  trees_graphs:
    current_level: ___/5
    target_level: 4/5
    assessment: "Comfortable with DFS, BFS, tree traversals"
    recent_problems_solved: ___
    time_efficiency: ___/5

  dynamic_programming:
    current_level: ___/5
    target_level: 3/5 # L6 target, 4/5 for L7
    assessment: "Can identify DP patterns and implement solutions"
    recent_problems_solved: ___
    time_efficiency: ___/5

  system_design_coding:
    current_level: ___/5
    target_level: 4/5
    assessment: "Can implement LRU cache, rate limiter, etc."
    recent_problems_solved: ___
    time_efficiency: ___/5

Code Quality Assessment (Score: 1-5)

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Production_Readiness:
  clean_code:
    current_level: ___/5
    target_level: 4/5
    evidence: "Code is readable, well-structured, properly commented"
    peer_review_feedback: []

  error_handling:
    current_level: ___/5
    target_level: 4/5
    evidence: "Handles edge cases, input validation, graceful failures"
    examples: []

  testing_mindset:
    current_level: ___/5
    target_level: 4/5
    evidence: "Writes testable code, considers unit test cases"
    examples: []

  scalability_awareness:
    current_level: ___/5
    target_level: 4/5
    evidence: "Considers performance implications, memory usage"
    examples: []

AWS and Cloud Knowledge Assessment

Core AWS Services (Score: 1-5)

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Essential_Services:
  compute_services:
    ec2: ___/5
    lambda: ___/5
    ecs_fargate: ___/5
    target_average: 4/5

  storage_services:
    s3: ___/5
    ebs: ___/5
    rds: ___/5
    dynamodb: ___/5
    target_average: 4/5

  networking_services:
    vpc: ___/5
    cloudfront: ___/5
    route53: ___/5
    elb: ___/5
    target_average: 3/5

  security_services:
    iam: ___/5
    kms: ___/5
    secrets_manager: ___/5
    target_average: 3/5

👥 Leadership Competency Assessment

People Management Matrix

Direct Report Management (Score: 1-5)

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Team_Leadership:
  one_on_ones:
    current_level: ___/5
    target_level: 4/5
    evidence: "Conducts effective 1:1s with clear outcomes and follow-up"
    team_feedback: []

  performance_management:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can handle performance issues, improvement plans, coaching"
    examples: []

  career_development:
    current_level: ___/5
    target_level: 4/5
    evidence: "Actively develops team members' careers and skills"
    promotion_success_rate: ___

  hiring_and_recruiting:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can attract, assess, and onboard quality candidates"
    hiring_success_rate: ___

Team Culture and Environment (Score: 1-5)

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Culture_Building:
  psychological_safety:
    current_level: ___/5
    target_level: 4/5
    evidence: "Creates environment where team feels safe to take risks"
    team_survey_scores: ___

  diversity_inclusion:
    current_level: ___/5
    target_level: 4/5
    evidence: "Builds diverse teams and inclusive practices"
    team_diversity_metrics: ___

  feedback_culture:
    current_level: ___/5
    target_level: 4/5
    evidence: "Establishes culture of continuous feedback and improvement"
    360_feedback_scores: ___

  team_productivity:
    current_level: ___/5
    target_level: 4/5
    evidence: "Team consistently delivers high-quality work on time"
    delivery_metrics: ___

Strategic Leadership Matrix

Cross-Functional Leadership (Score: 1-5)

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Stakeholder_Management:
  product_collaboration:
    current_level: ___/5
    target_level: 4/5
    evidence: "Effective partnership with product management"
    examples: []

  executive_communication:
    current_level: ___/5
    target_level: 3/5 # L6 target, 4/5 for L7
    evidence: "Can communicate technical concepts to senior leadership"
    examples: []

  cross_team_influence:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can influence decisions across organizational boundaries"
    examples: []

  conflict_resolution:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can resolve conflicts between teams and stakeholders"
    examples: []

Technical Strategy (Score: 1-5)

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Strategic_Planning:
  technical_roadmaps:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can create and execute technical roadmaps aligned with business"
    examples: []

  architecture_decisions:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can make strategic architecture decisions with long-term impact"
    examples: []

  technology_evaluation:
    current_level: ___/5
    target_level: 4/5
    evidence: "Can evaluate and adopt new technologies strategically"
    examples: []

  innovation_leadership:
    current_level: ___/5
    target_level: 3/5 # L6 target, 4/5 for L7
    evidence: "Can drive innovation and technical excellence"
    examples: []

🎭 Behavioral Leadership Assessment

Amazon Leadership Principles Matrix

Customer-Centric Leadership (Score: 1-5)

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Customer_Focus:
  customer_obsession:
    story_quality: ___/5
    story_quantity: ___/3 # Target: 3 strong stories
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  ownership:
    story_quality: ___/5
    story_quantity: ___/3
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

Innovation and Excellence (Score: 1-5)

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Innovation_Excellence:
  invent_and_simplify:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  are_right_a_lot:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  learn_and_be_curious:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  insist_on_highest_standards:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

People and Results Leadership (Score: 1-5)

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People_Results:
  hire_and_develop:
    story_quality: ___/5
    story_quantity: ___/3
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  think_big:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  bias_for_action:
    story_quality: ___/5
    story_quantity: ___/2
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

  deliver_results:
    story_quality: ___/5
    story_quantity: ___/3
    target_quality: 4/5
    recent_examples: []
    improvement_areas: []

📈 Comprehensive Assessment Checkpoints

Monthly Deep Assessment Protocol

Month 1 Assessment (Foundation)

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Technical_Foundations:
  system_design_basics:
    problems_completed: ___/10 # Target: 10 basic problems
    average_completion_time: ___ minutes
    average_quality_score: ___/5
    target_quality: 3.5/5

  coding_fundamentals:
    problems_completed: ___/30 # Target: 30 problems (mix of easy/medium)
    success_rate: ___% # Target: 70%
    average_time: ___ minutes per problem
    target_time: 35 minutes for medium problems

  aws_knowledge:
    services_familiar_with: ___/20 # Target: 20 core services
    hands_on_experience: ___/10 # Target: 10 services used in practice

Behavioral_Foundations:
  story_development:
    total_stories_outlined: ___/30 # Target: 30 story outlines
    complete_star_stories: ___/15 # Target: 15 fully developed
    leadership_principles_covered: ___/16 # Target: All 16 covered

  delivery_quality:
    average_story_length: ___ minutes # Target: 3-4 minutes
    star_structure_completeness: ___% # Target: 90%
    specific_metrics_included: ___% # Target: 80%

Month 2 Assessment (Development)

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Technical_Development:
  system_design_advancement:
    complex_problems_completed: ___/8 # Target: 8 intermediate problems
    time_management: ___% within time limits # Target: 80%
    trade_off_analysis_quality: ___/5 # Target: 4/5

  coding_advancement:
    medium_problems_success: ___% # Target: 80%
    hard_problems_attempted: ___/5 # Target: 5 attempts
    code_quality_improvement: ___/5 # Target: 4/5

  aws_practical_application:
    architecture_designs_using_aws: ___/5 # Target: 5 designs
    cost_optimization_understanding: ___/5 # Target: 3/5

Behavioral_Development:
  story_refinement:
    stories_with_strong_metrics: ___/20 # Target: 20 quantified stories
    stories_showing_growth: ___/15 # Target: 15 showing learning/growth
    multi_lp_stories: ___/10 # Target: 10 stories covering multiple LPs

  mock_interview_performance:
    behavioral_mocks_completed: ___/4 # Target: 4 mocks
    average_mock_score: ___/5 # Target: 3.5/5
    improvement_trend: ___/5 # Target: 4/5

Month 3+ Assessment (Mastery)

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Technical_Mastery:
  system_design_mastery:
    l6_problems_success_rate: ___% # Target: 90%
    l7_problems_attempted: ___/3 # Target: 3 if going for L7
    innovation_in_solutions: ___/5 # Target: 4/5

  coding_mastery:
    consistent_medium_success: ___% # Target: 95%
    time_efficiency: ___% under target time # Target: 80%
    teaching_ability: ___/5 # Target: 4/5

  aws_expertise:
    well_architected_understanding: ___/5 # Target: 4/5
    cost_optimization_expertise: ___/5 # Target: 4/5
    security_best_practices: ___/5 # Target: 4/5

Behavioral_Mastery:
  interview_readiness:
    full_loop_mock_success: ___% # Target: 90%
    behavioral_consistency: ___/5 # Target: 4.5/5
    cultural_alignment_demonstrated: ___/5 # Target: 4.5/5

  leadership_demonstration:
    authentic_leadership_examples: ___/16 # Target: All LPs covered authentically
    strategic_thinking_evidence: ___/5 # Target: 4/5
    organizational_impact_examples: ___/5 # Target: 4/5

🔍 Gap Analysis Framework

Automated Gap Identification

Technical Gaps Analysis

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System_Design_Gaps:
  identified_weak_areas:
    - area: "Database scaling strategies"
      current_score: 2/5
      target_score: 4/5
      gap_severity: "High"
      improvement_plan: "Study sharding patterns, practice database design problems"
      timeline: "4 weeks"
      resources: ["System Design Primer", "Database Internals book"]

  coding_gaps:
    - area: "Dynamic programming problems"
      current_score: 2/5
      target_score: 4/5
      gap_severity: "Medium"
      improvement_plan: "Practice 20 DP problems, study common patterns"
      timeline: "3 weeks"
      resources: ["LeetCode DP study plan", "DP pattern guide"]

Leadership Gaps Analysis

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Leadership_Gaps:
  people_management_gaps:
    - area: "Performance management"
      current_score: 2/5
      target_score: 4/5
      gap_severity: "High"
      improvement_plan: "Develop more examples of coaching underperformers"
      timeline: "2 weeks"
      resources: ["High Output Management", "Coaching experience reflection"]

  behavioral_story_gaps:
    - leadership_principle: "Think Big"
      story_count: 1/3
      story_quality: 2/5
      gap_severity: "High"
      improvement_plan: "Develop 2 additional strategic vision examples"
      timeline: "1 week"
      resources: ["Experience mining", "Story structure templates"]

Priority Gap Matrix

High Impact, High Effort (Strategic Projects): - Develop L7-level system design capabilities - Build comprehensive behavioral story bank - Gain hands-on AWS experience

High Impact, Low Effort (Quick Wins): - Improve STAR story structure - Practice common coding patterns - Develop consistent mock interview routine

Low Impact, High Effort (Avoid or Defer): - Learning obscure AWS services not relevant to role - Practicing very hard algorithm problems beyond interview scope - Over-optimizing stories that already score well

Low Impact, Low Effort (Fill Time): - Light reading of AWS documentation - Easy coding problems for confidence building - Industry trend research

📊 Progress Tracking Dashboard

Weekly Progress Metrics

Technical Progress Tracking

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Week_N_Technical_Progress:
  system_design:
    problems_attempted: ___
    problems_completed_successfully: ___
    average_time_per_problem: ___ minutes
    quality_score_trend: [week1: ___, week2: ___, week3: ___]

  coding_practice:
    easy_problems_success_rate: ___%
    medium_problems_success_rate: ___%
    hard_problems_attempted: ___
    time_efficiency_trend: [week1: ___, week2: ___, week3: ___]

  aws_learning:
    new_services_learned: ___
    hands_on_labs_completed: ___
    architecture_designs_created: ___

Leadership Progress Tracking

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Week_N_Leadership_Progress:
  story_development:
    new_stories_created: ___
    stories_refined: ___
    stories_with_strong_metrics: ___
    leadership_principles_improved: []

  mock_interview_performance:
    mocks_completed: ___
    average_behavioral_score: ___/5
    average_technical_score: ___/5
    improvement_areas_identified: []

  feedback_integration:
    feedback_items_received: ___
    feedback_items_addressed: ___
    behavioral_improvements_demonstrated: []

Monthly Competency Heatmap

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Competency_Heatmap_Month_N:
  Technical_Skills:
    system_design_l6: ___/5 # Color: Red <3, Yellow 3-4, Green >4
    coding_algorithms: ___/5
    aws_knowledge: ___/5
    production_mindset: ___/5

  Leadership_Skills:
    people_management: ___/5
    strategic_thinking: ___/5
    cross_functional_collaboration: ___/5
    technical_strategy: ___/5

  Behavioral_Readiness:
    customer_obsession: ___/5
    ownership: ___/5
    invent_simplify: ___/5
    think_big: ___/5
    deliver_results: ___/5
    hire_develop: ___/5

  Interview_Performance:
    mock_interview_consistency: ___/5
    time_management: ___/5
    communication_clarity: ___/5
    pressure_handling: ___/5

✅ Readiness Validation Framework

Final Interview Readiness Assessment

Technical Readiness Validation (Must Score 4+ in all areas)

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Technical_Validation:
  system_design_readiness:
    l6_problems_consistency: ___/5 # Must be 4+
    time_management: ___/5 # Must be 4+
    trade_off_analysis: ___/5 # Must be 4+
    communication_clarity: ___/5 # Must be 4+

  coding_readiness:
    medium_problem_success_rate: __% # Must be 85%+
    time_efficiency: ___/5 # Must be 4+
    code_quality: ___/5 # Must be 4+
    explanation_ability: ___/5 # Must be 4+

  aws_readiness:
    service_knowledge_breadth: ___/5 # Must be 4+
    architecture_design_capability: ___/5 # Must be 4+
    cost_optimization_awareness: ___/5 # Must be 3+

Leadership Readiness Validation

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Leadership_Validation:
  people_management_readiness:
    coaching_examples: ___/3 # Must have 3+ strong examples
    performance_management: ___/5 # Must be 4+
    team_building: ___/5 # Must be 4+
    hiring_development: ___/5 # Must be 4+

  strategic_leadership_readiness:
    cross_functional_influence: ___/5 # Must be 4+
    technical_strategy: ___/5 # Must be 4+
    change_management: ___/5 # Must be 3+
    executive_communication: ___/5 # Must be 3+ (L6), 4+ (L7)

Behavioral Readiness Validation

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Behavioral_Validation:
  story_bank_completeness:
    total_strong_stories: ___/30 # Must have 30+ stories
    stories_per_lp_average: ___/2 # Must average 2+ per LP
    stories_with_metrics: ___/25 # Must have 25+ quantified stories
    recent_examples: ___/15 # Must have 15+ examples from last 2 years

  delivery_consistency:
    star_structure_adherence: __% # Must be 95%+
    time_management: ___/5 # Must be 4+
    authenticity: ___/5 # Must be 5/5
    leadership_demonstration: ___/5 # Must be 4+

  mock_interview_performance:
    full_loop_success_rate: __% # Must be 90%+
    behavioral_consistency: ___/5 # Must be 4.5+
    pressure_handling: ___/5 # Must be 4+
    improvement_trajectory: ___/5 # Must be 4+

Pre-Interview Final Checklist

Technical Preparation Complete: - [ ] Can complete L6 system design problems in 45 minutes with high quality - [ ] 90%+ success rate on LeetCode medium problems in target time - [ ] Can design AWS architectures for common use cases with cost considerations - [ ] Can explain technical concepts clearly to both technical and non-technical audiences

Leadership Preparation Complete: - [ ] Have documented examples of managing 5+ person teams with clear outcomes - [ ] Can demonstrate strategic thinking and cross-functional influence - [ ] Have multiple examples of hiring, developing, and promoting team members - [ ] Can show measurable organizational impact from leadership initiatives

Behavioral Preparation Complete: - [ ] Have 2+ strong STAR stories for each of the 16 Leadership Principles - [ ] All stories include specific, quantified results and personal learning - [ ] Can deliver any story naturally in 3-4 minutes with authentic emotion - [ ] Have practiced responses to common follow-up questions and variations

Mock Interview Validation: - [ ] Completed 3+ full-loop mock interviews with 4+ average score - [ ] Received positive feedback on authenticity and leadership demonstration - [ ] Can handle pressure and unexpected questions with composure - [ ] Interview performance is consistent across different interviewers and sessions

Confidence and Mindset: - [ ] Feel confident about technical abilities and can code/design under pressure - [ ] Excited to talk about leadership experiences and lessons learned - [ ] Understand Amazon's culture and values at a deep level - [ ] Ready to contribute from day one and grow with the company

🚀 Getting Started with Assessment

Week 1: Complete Initial Assessment

  1. Technical Baseline (Day 1-2):
  2. Complete system design assessment with 3 problems
  3. Solve 10 coding problems across different categories

  4. Take AWS knowledge quiz

  5. Leadership Baseline (Day 3-4):

  6. Complete people management scenarios assessment
  7. Evaluate strategic leadership examples

  8. Document current team impact metrics

  9. Behavioral Baseline (Day 5-7):

  10. Map existing experiences to all 16 Leadership Principles
  11. Develop initial STAR stories for top 5 LPs
  12. Conduct first mock behavioral interview

Week 2: Create Improvement Plan

  1. Gap Analysis (Day 1-2):
  2. Identify top 3 technical gaps with improvement plans
  3. Identify top 3 leadership gaps with development strategies

  4. Identify top 3 behavioral story gaps with experience mining

  5. Resource Planning (Day 3-4):

  6. Gather learning resources for identified gaps
  7. Schedule practice sessions and mock interviews

  8. Set up progress tracking systems

  9. Implementation Start (Day 5-7):

  10. Begin systematic practice routine
  11. Start weekly assessment check-ins
  12. Establish accountability partnerships

Monthly Review Process

  1. Progress Assessment: Complete comprehensive assessment
  2. Gap Analysis Update: Identify new gaps and close completed ones
  3. Plan Adjustment: Modify practice plan based on progress
  4. Goal Setting: Set specific goals for next month
  5. Resource Optimization: Adjust resources and methods based on effectiveness

Assessment Success Formula

Honest Self-Assessment (accurate baseline) + Systematic Gap Analysis (targeted improvement) + Regular Progress Tracking (consistent measurement) + Iterative Plan Adjustment (continuous optimization) = Interview Readiness

Use this assessment framework in conjunction with all other practice components: Mock Interviews, System Design Problems, Behavioral Questions, and Coding Practice.

This completes your comprehensive practice framework for Amazon L6/L7 engineering manager interview success.