How I Work - Development Methodology

Before writing any code, I clarify the 'why' behind every project. I understand business objectives and user problems, identify stakeholders and their expectations (clients, product owners, designers, QA), read and reformulate needs into clear and testable User Stories, and determine technical and functional KPIs (performance, stability, error rates).

Once the vision is clear, I structure the solution. This involves choosing the architecture (monolith, microservices, event-driven, serverless), defining project structure (modules, folders, layers), writing a concise Tech Design Doc (TDD), defining interfaces and API/GraphQL/service contracts, and identifying technical risks with mitigation plans.

I divide features into unit tasks (independent, estimable, testable), define acceptance criteria for each task, evaluate complexity (T-shirt sizing or Story points), and prioritize according to impact and technical dependencies.

This is where the real development flow begins, heavily accelerated by Agentic AI. I read the ticket to understand the need and write a mini implementation plan. Then, I leverage Cursor (AI IDE) alongside Claude for code generation and system design. I use Antigravity for automated coding tasks and Stitch for seamless AI integration. I code with rigor following SOLID, KISS, DRY principles, make small logical commits (often assisted by Cursor's git features), refactor before pushing, and write unit/integration tests with AI assistance.

I write tests at multiple levels: unit tests for pure logic, integration tests for module interactions, end-to-end tests for user flows (Playwright, Cypress), performance and load tests (Lighthouse, Artillery), and manual QA on staging. The goal is 100% feature validation before merge.

I configure GitHub Actions/GitLab CI with Build → Lint → Test → Deploy pipelines, set up automatic quality checks (SonarQube, ESLint), deploy to staging/production (Vercel, Docker, Cloud Run), and automate migrations, seeds, and rollback plans. Best practices include secrets in Vault/encrypted env vars and branch protection rules with mandatory code review.

I maintain technical documentation in Markdown or Docusaurus, keep README.md up to date for each module, use automatic generation with Cursor (JSDoc), maintain a clear changelog, and enrich the team Knowledge Base (Notion, Confluence).

I verify code readability, simplicity, and consistency, ensure respect for conventions and security, check that tests are present and clear, and provide constructive, precise feedback. I also use Cursor to pre-analyze MRs before manual review.

I analyze technical debt each sprint, set up metrics (Lead Time, Bug Rate, Test Coverage), deploy regular audits (SonarQube, Lighthouse), and train the team through mini workshops, pair programming, and mentoring.