Tech Leadership & Management Roadmap

Explain the relationship between artificial intelligence, machine learning, and deep learning.

Describe how a neural network processes data to make predictions.

Distinguish between supervised, unsupervised, and reinforcement learning with relevant examples.

Explain the training process of a supervised machine learning model, including data, loss functions, and optimization.

Explain how large language models generate text using token prediction.

Identify the capabilities and limitations of current AI models, including hallucinations, bias, and context windows.

Use AI-powered code assistants like GitHub Copilot to accelerate code writing and refactoring.

Write effective prompts to get accurate and useful responses from LLMs for development tasks.

Use AI tools to generate unit tests and documentation for existing code.

Integrate an LLM API into a Spring Boot backend to power an AI-driven application feature.

Explain the concept of LLM function calling and its role in creating agentic workflows.

Diagram a simple agentic workflow that uses function calling to access an external data source to answer a user query.

Identify key considerations for safely deploying AI-powered features, including cost, latency, and hallucination mitigation.

Apply cognitive reframing techniques to transform self-limiting thoughts into growth-oriented statements.

Shift from an external to an internal locus of control by identifying specific, actionable problems you can solve.

Implement time blocking with dedicated deep work sessions to minimize context switching and maximize focus.

Build a personal knowledge management system using tools like Notion or Obsidian to document solutions and reduce cognitive load.

Maintain a structured 'brag document' that records weekly problems solved, contributions made, and impact delivered.

Establish a weekly review protocol to plan and prioritize technical and personal development goals.

Define a professional developer niche and craft a personal brand statement that highlights your unique value.

Optimize a LinkedIn profile with a keyword-rich headline, about section, and experience to maximize recruiter visibility.

Structure LinkedIn posts using a 'build-in-public' content strategy to demonstrate technical depth and consistency.

Engage strategically with senior developers and industry leaders through insightful commenting to expand your professional network.

Identify common forms of unconscious bias and microaggressions in tech workplace settings.

Apply a framework for responding to microaggressions in real-time.

Negotiate for promotions, raises, or project assignments using evidence-based arguments from your brag document.

Structure professional emails for clarity, tone, and actionability.

Write a clear pull request description that includes business context, technical approach, and testing instructions.

Write a concise technical summary of a complex concept for a non-technical audience.

Explain a technical concept or blocker to a non-technical stakeholder using simplified language.

Apply the STAR method to structure verbal explanations of past projects in interviews and meetings.

Use appropriate vocabulary for disagreeing, persuading, and negotiating in professional discussions.

Adapt communication style and vocabulary based on audience context, from the technical team to executive leadership.

Explain the testing pyramid and the role of unit, integration, and end-to-end (E2E) tests.

Design test cases using boundary value analysis and equivalence partitioning techniques.

Write unit tests for Java methods using JUnit and for React components using React Testing Library.

Write integration tests for Spring Boot REST API endpoints using Mockito to mock dependencies.

Write E2E tests for a user flow using Cypress.

Apply test-driven development (TDD) by writing a failing test before implementing the corresponding feature.

Configure a CI pipeline using GitHub Actions to automatically run the test suite on every code push.

Explain the principles behind the Agile Manifesto and contrast Agile with Waterfall methodologies.

Analyze the purpose of Scrum roles, events, and artifacts and map them to your current team's workflow.

Write well-structured user stories with acceptance criteria using the INVEST format.

Estimate work effort using story points and planning poker techniques.

Deliver concise and effective updates during daily standups that communicate progress, plans, and blockers.

Track project progress using burndown charts and velocity metrics.

Identify project risks, document them in a risk register, and define mitigation strategies.

Identify common code smells and anti-patterns that indicate tightly-coupled components in a legacy system.

Apply SOLID principles to refactor tightly coupled code into modular components.

Apply creational design patterns (Singleton, Factory) and structural patterns (Adapter, Facade) to improve code structure.

Apply behavioral design patterns (Strategy, Observer) to create flexible and event-driven architectures.

Write characterization tests for legacy code to enable safe refactoring.

Apply the Strangler Fig pattern to incrementally modernize functionality in a legacy system.

Conduct a constructive code review by focusing on correctness, design, and maintainability.

Apply a systematic 'divide and conquer' protocol for debugging complex issues.

Explain the differences between monolithic and microservices architectures, including their trade-offs.

Design RESTful API resources and endpoints with proper error handling and versioning.

Explain how relational and NoSQL databases differ and select the appropriate type for a given use case.

Describe how message queues (e.g., Kafka, RabbitMQ) enable asynchronous communication between services.

Explain caching strategies, including in-memory, CDN, and database-level caching, with their trade-offs.

Explain horizontal versus vertical scaling strategies and their trade-offs.

Describe the role of a load balancer in distributing traffic across servers.

Apply first-principles thinking to decompose complex business problems into fundamental technical requirements.

Translate a business problem into a set of functional and non-functional requirements for a system.

Propose a high-level architectural approach that satisfies a given set of business requirements.

Design a high-level system architecture diagram for a multi-tier web application.

Explain the difference between authentication and authorization and describe an OAuth 2.0 flow for securing services.

Evaluate trade-offs between consistency, availability, and partition tolerance using the CAP theorem.

Design for fault tolerance using patterns like circuit breakers, redundancy, and graceful degradation.

Present and justify architectural decisions to both technical and non-technical stakeholders.