These skills do not affect the main grade but show the breadth of your profile.
Agile Methods
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Understands the fundamentals of SAFe Framework. Applies basic practices in daily work. Follows recommendations from the team and documentation.
Actively participates in SAFe ceremonies: PI Planning, System Demo, Inspect & Adapt. Coordinates product backlog with ART backlog. Manages features and enablers considering technical dependencies and architectural runway.
Shapes SAFe implementation strategy for the division. Defines Value Streams and ARTs with product-centric lens. Introduces Lean Portfolio Management. Trains TPMs on working in SAFe environments.
AI Coding Assistants
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Knows ChatGPT and Claude capabilities for product work. Uses AI assistants for idea generation, specification writing and data analysis. Understands LLM limitations in the context of technical tasks.
Applies ChatGPT/Claude for accelerating product work: competitor analysis, user story generation, specification code review. Creates effective prompts for technical tasks. Evaluates AI-generated content quality.
Shapes AI tool usage strategy for the product division. Defines guidelines for quality and security of AI-generated content. Introduces AI copilot practices for the TPM team.
Knows GitHub Copilot capabilities for accelerating development. Understands how AI code assistants affect team productivity. Can evaluate potential ROI from Copilot adoption for their team.
Evaluates GitHub Copilot impact on feature delivery speed and code quality. Analyzes adoption metrics — acceptance rate, time saved, code quality impact. Formulates recommendations for the team on effective usage.
Shapes AI coding tool usage policy for the division. Defines guidelines for security, IP and compliance for Copilot/Codeium. Evaluates aggregate impact on engineering productivity and quality.
Algorithms & Data Structures
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Understands basic algorithm complexity concepts O(n), O(n²) for evaluating impact on user experience. Can assess when a slow feature is an algorithm problem rather than an infrastructure issue.
Uses understanding of algorithmic complexity for prioritizing optimizations — which features scale with data growth, where bottlenecks occur as product user base grows.
Embeds algorithmic complexity analysis into the product decision-making process. Ensures technical constraints are considered at discovery stage rather than during development.
Understands main data structures — arrays, objects, trees — at a level sufficient for reading technical documentation. Can discuss product data model choices with developers.
Understands data structures well enough to evaluate team technical proposals — impact of storage choices on performance, memory volume and feature implementation speed.
Participates in architectural discussions on equal terms with tech leads, justifying product requirements considering data structure constraints. Translates business needs into technical specifications.
API Management
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Understands the importance of API documentation for internal and external consumers. Knows OpenAPI/Swagger formats and can read specifications. Can identify documentation gaps during review.
Independently defines API documentation requirements for developers. Reviews OpenAPI specifications for endpoint, error and example completeness. Defines developer experience standards for public APIs.
Defines API documentation standards for the entire product division. Introduces auto-generation of documentation from code with CI/CD pipeline integration. Trains teams on developer-facing documentation best practices.
Shapes enterprise developer relations strategy through API documentation. Defines documentation quality metrics at the organizational level, integrates API catalog and developer portal into the overall product ecosystem.
Application Security
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Knows main OWASP Top 10 vulnerability types and understands their potential impact on the product and users. Can include security requirements in user stories.
Considers OWASP recommendations when designing features — secure authentication, user data protection, input validation. Prioritizes security tasks in the product backlog.
Defines product security strategy — compliance requirements, personal data processing policy, incident response process. Communicates risks to stakeholders.
CI/CD
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Understands the CI/CD concept and how GitHub Actions automates the product delivery process. Knows main pipeline stages — build, testing, deploy — and their impact on release speed.
Uses GitHub Actions capabilities for improving the product process — automatic preview environment deployment, build status notifications, integration with project boards and issue tracking.
Defines CI/CD strategy for the product team — deployment frequency, change failure rate, lead time. Ensures the pipeline supports the required iteration speed.
Clean Code & Refactoring
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Understands the importance of code quality for product delivery speed. Knows basic metrics — test coverage, cyclomatic complexity — and can interpret SonarQube reports.
Considers code quality metrics when planning sprints — allocates time for refactoring, tracks technical debt trends. Uses data to justify quality investments.
Defines code quality policy for the product team — acceptance standards, SLA for critical defect resolution, technical debt budget. Communicates quality value to stakeholders.
Cloud Providers
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Understands main AWS services and their role in product infrastructure. Knows that EC2, S3, RDS are used for hosting, storage and databases, affecting cost and scalability.
Evaluates cloud architecture impact on product cost and performance. Participates in AWS service selection — Lambda vs ECS, DynamoDB vs RDS — from business requirements perspective.
Defines cloud strategy for the product team. Manages AWS budget, makes decisions on reserved instances vs on-demand, ensures compliance and cost optimization.
Code Review
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Understands the code review process and its importance for product quality. Can read pull requests and understand changes at a high level. Participates in PR discussions from the perspective of product requirements.
Reviews pull requests focusing on product requirements compliance and API contracts. Understands change impact on user experience and performance. Checks for feature flags and A/B test configurations.
Defines standards for TPM participation in code review for the division. Introduces automated checks for product requirements in CI pipeline. Trains TPMs on technical review skills.
Concurrency & Parallelism
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Understands the asynchrony concept and its impact on user experience — data loading without blocking UI, background operations. Knows basic terminology for communicating with the team.
Considers async patterns when designing features — optimistic updates, background processing, task queues. Understands the impact of asynchrony on UX and designs loading states.
Defines standards for async operation handling in the product — UX patterns for long-running tasks, notification strategy, processing priorities. Ensures consistent user experience.
Containerization
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Understands the containerization concept and why Docker is used in product development. Can launch a local development environment from docker-compose for feature testing.
Uses Docker for reproducing bugs and testing features in isolated environments. Understands how containerization affects the deployment process and product update delivery speed.
Defines Docker usage standards in the product process — preview environments for stakeholders, automated testing in CI, UAT environments. Optimizes the delivery pipeline.
Delivery Management
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Understands the fundamentals of Process Improvement: Kaizen, Retrospectives. Applies basic practices in daily work. Follows recommendations from the team and documentation.
Independently analyzes delivery pipeline processes. Applies value stream mapping to identify waste in the development cycle. Implements targeted improvements with measurable results — cycle time, quality metrics.
Defines continuous improvement framework for the division. Introduces kaizen practices for engineering and product processes. Trains TPMs and Tech Leads on process improvement methodologies with data-driven approach.
Docs-as-Code
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Can read and create basic diagrams: flowcharts, sequence diagrams, user flows. Uses Miro, Lucidchart or draw.io for visualizing product processes. Understands UML notation at a basic level.
Creates technical diagrams for product specifications: sequence diagrams for API interactions, data flow diagrams, state machines. Uses C4 model for documenting architecture at different levels.
Defines diagram standards and templates for the product division. Introduces diagrams-as-code approach (Mermaid, PlantUML) with versioning. Trains teams on effective visual communication of architectural decisions.
Git & Workflows
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Understands basic Git advanced concepts for technical product management: branching strategies (GitFlow, trunk-based) for release planning, tag-based versioning for product releases, merge conflict resolution awareness for sprint planning. Follows team conventions for release branch management.
Confidently works with Git for tracking technical changes: reviews diffs, understands merge conflicts and branching strategies. Reads git log for velocity and change pattern analysis. Configures branch protection rules.
Shapes Git workflow standards for the division: trunk-based development, release branching, monorepo strategies. Introduces automated release notes generation. Defines change management process for critical systems.
Integration Testing
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Understands the role of integration testing for product stability. Knows what is verified at this level — component interactions, API contracts, data flow scenarios.
Considers integration testing when planning features — identifies critical integration points, allocates testing time in estimates. Tracks regressions between components.
Shapes integration testing policy for the product team. Ensures balance between testing thoroughness and delivery speed, introduces integration quality metrics.
Logging
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Understands the role of logging for diagnosing product issues. Knows how logs help identify bug causes, track user behavior and evaluate feature performance.
Uses logs for analyzing product metrics — conversion funnels, error frequency, key operation execution time. Formulates logging requirements for new features.
Defines logging and monitoring strategy for the product team. Ensures every feature ships with success metrics and dashboards for tracking business impact.
Metrics & Monitoring
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Understands basic Prometheus & Grafana for product management: reading product health dashboards (availability, latency), understanding SLI/SLO metrics for product reliability discussions, navigating Grafana panels for user-facing service metrics. Follows team conventions for product health monitoring.
Formulates product metric monitoring requirements — conversion, key operation latency, error rate. Creates Grafana dashboards for tracking business KPIs in real-time.
Defines monitoring strategy for the product team. Establishes SLOs for the product, ensures visibility for stakeholders and configures escalation process on SLA violations.
OOP & Design Patterns
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Knows main design patterns at a level sufficient to understand team technical discussions. Understands why patterns are important for product extensibility and maintainability.
Uses pattern knowledge for evaluating technical decisions — strategy for A/B tests, observer for notifications, factory for creating different content types in the product.
Evaluates team architectural decisions from a product strategy perspective. Ensures chosen patterns support planned functionality and product scaling.
Understands basic OOP principles at a level sufficient for reading technical specifications and UML diagrams. Can participate in product module architecture discussions with developers.
Uses OOP understanding for evaluating team technical decisions — code modularity, system extensibility, cost of adding new features. Understands when architecture slows product development.
Participates in architectural decisions, justifying product requirements for modularity and extensibility. Ensures architecture supports the planned roadmap 2-3 quarters ahead.
Product Delivery
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Understands the fundamentals of Go-to-Market Strategy. Applies basic practices in daily work. Follows recommendations from the team and documentation.
Independently plans GTM for technical features and API releases. Coordinates technical readiness with marketing launch: documentation, SDK, sandbox environment. Defines early adopter program for developer-facing products.
Defines GTM framework for the product division focused on technical products. Introduces repeatable launch playbook for API and platform products. Trains TPMs on technology-focused GTM practices.
Product Discovery
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Understands the Jobs-to-be-Done concept and its difference from persona-based approach. Knows how to apply JTBD framework for technical products and developer tools. Can formulate job statements for basic user tasks.
Independently conducts JTBD research for technical users: developers, DevOps, architects. Formulates job maps with functional, emotional and social dimensions. Identifies unmet needs in developer experience.
Defines JTBD framework for the product division. Introduces outcome-driven innovation approach for portfolio-level decisions. Trains TPMs on JTBD interviews with technical users.
Understands the fundamentals of User Research. Applies basic practices in daily work. Follows recommendations from the team and documentation.
Independently conducts user research for a technical product. Conducts developer interviews focused on DX (developer experience). Analyzes quantitative data from analytics and qualitative feedback from support channels.
Defines user research framework for the division. Introduces continuous discovery practices with technical users. Shapes research operations: participant recruitment, insight repository. Trains TPMs on research skills.
Shapes enterprise user research strategy for technical products. Defines organizational research practice. Builds insight-driven culture with systematic knowledge sharing. Coordinates cross-product research initiatives.
Product Strategy
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Conducts technical market research: evaluates competing APIs and platforms, analyzes developer experience trends, and benchmarks technical capabilities. Maps findings to engineering feasibility.
Independently conducts competitive analysis with technical depth: API capabilities, architecture patterns, pricing models. Analyzes developer community trends through GitHub stars, Stack Overflow, developer surveys.
Defines market research framework for the division focused on technology trends. Introduces systematic competitor tracking with technical benchmarking. Shapes technology radar for strategic decision-making.
Project Planning
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Understands the fundamentals of Risk Management. Applies basic practices in daily work. Follows recommendations from the team and documentation.
Independently conducts risk assessment for product initiatives with technical depth. Evaluates technical risks: scalability, security, data integrity. Defines mitigation strategies and contingency plans for each risk.
Defines risk management framework for the division. Introduces portfolio-level risk visibility with cross-team dependency risks. Shapes risk governance: escalation, review cadence, decision authority. Trains TPMs.
Shapes enterprise risk management strategy for the technical portfolio. Defines organizational risk appetite for technology investments. Coordinates technology risk reporting for C-level and board. Integrates with compliance.
Prompt Engineering
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Uses AI tools for technical specification drafting and architecture documentation. Formulates prompts that bridge business requirements and technical implementation details. Leverages AI for API design reviews and technical debt assessment.
Applies advanced prompt engineering techniques: chain-of-thought, structured output, system prompts. Creates prompts for technical tasks: specification generation, architecture analysis, code review guidance.
Shapes prompt engineering standards for the division. Introduces prompt testing and evaluation framework. Defines best practices for AI-assisted product management. Trains TPMs on effective LLM usage.
Relational Databases
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Understands basic PostgreSQL concepts for product management: database performance impact on product SLAs, migration planning for feature releases, recognizing data model constraints in feature discussions. Follows team conventions for database-related product decision documentation.
Works with PostgreSQL for product data analysis — writes queries for analytics, understands database schema impact on feature performance. Considers constraints when designing the product.
Defines data storage strategy for the product team. Coordinates database schema migrations with product roadmap, ensures backward compatibility and downtime planning.
System Design
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Understands the capacity planning concept at team and infrastructure levels. Knows main metrics: velocity, throughput, utilization. Participates in sprint planning considering developer availability.
Independently plans team capacity for a quarter considering technical debt and on-call rotation. Accounts for infrastructure capacity when planning load-heavy features. Works with system performance data.
Defines capacity planning standards for the division, including team and infrastructure capacity. Introduces forecasting models considering user base growth and technical complexity. Optimizes cloud costs.
Shapes enterprise capacity planning strategy linking business growth with technical investments. Defines FinOps approaches, forecasts infrastructure needs 2-3 years ahead, coordinates hiring plan.
Unit Testing
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Understands the value of unit testing for product quality and development speed. Knows how test coverage affects release stability and team confidence when changing code.
Considers testing when planning sprints — allocates time for test writing, tracks coverage of critical business scenarios. Justifies test investments through defect metrics.
Defines testing policy for the product team — minimum coverage for release, testing strategy for new features vs legacy code. Balances delivery speed with reliability.
User Documentation
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Understands the importance of structured knowledge management for a technical product. Can create and maintain documents in Confluence, Notion or similar tools. Knows principles of knowledge base organization for a technical team.
Independently designs knowledge base structure for the product: architecture docs, runbooks, decision logs. Defines information architecture for different audiences — developers, TPMs, stakeholders. Maintains freshness.
Defines knowledge management standards for the division. Introduces cross-team knowledge sharing practices. Shapes information architecture for 10+ products. Evaluates knowledge base health metrics.
Understands the role of user documentation for a technical product. Knows documentation types: quickstart guides, tutorials, reference docs, FAQs. Can review documentation for accuracy and completeness.
Defines user documentation requirements for a technical product. Coordinates documentation creation for developer and end-user audiences. Reviews documentation for technical accuracy and user-friendliness.
Defines documentation standards for the division. Introduces docs-as-product approach with user research and iteration. Shapes documentation team structure and processes. Measures documentation quality with customer feedback.