Frontend Delivery Craft

How I craft and ship interfaces

This page describes how I take interface work from design handoff to delivery — craft, implementation quality, performance, and multilingual readiness — not a systems or architecture catalog. Tools appear in the steps where they support that craft. Hardware lives under My Setup at the end.

Design Handoff

Flow:Figma → requirements → responsive states

Read approved Figma designs for interface fidelity and responsive states before writing production UI.

  • Figma

    Used to review designs, inspect interface details, understand responsive layouts and states, extract design values, and transform approved interfaces into code.

Implementation

Flow:Components → pages → API integration

Craft reusable components into pages and wire API-backed interfaces with clear task coordination.

  • Cursor

    My primary AI-assisted code editor for implementation, refactoring, code exploration, and working across frontend repositories.

  • Visual Studio Code

    A code editor used for general-purpose editing, extensions, and lightweight project work.

  • Node.js

    Used to run frontend tooling, package managers, development servers, build processes, and the Vue and Nuxt ecosystem.

  • ClickUp

    Used to follow assigned tasks, deadlines, delivery priorities, and project progress.

  • Toggl

    Used to track work time across projects and tasks.

  • Slack

    Used for team communication, project discussions, and implementation follow-up.

  • WhatsApp

    Used for direct operational communication and fast coordination when required.

Version Control

Flow:Issue → branch → commits → PR

Keep changes reviewable and traceable from issue through merge.

  • Git

    Used for branching, commits, local history, and organized change management.

  • GitHub

    Used for private repositories, pull requests, issue tracking, code history, and collaboration.

Quality Review

Flow:ESLint → TypeScript → CodeRabbit → manual review

Catch consistency, type, and review issues before performance and delivery checks.

  • ESLint

    Used to maintain code consistency and detect common implementation problems.

  • TypeScript Checks

    Used to identify type errors and improve implementation reliability.

  • CodeRabbit

    Used as an additional code-review layer for pull requests.

  • Manual Testing

    Used to review responsive behavior, visual implementation, forms, interactions, devices, browsers, and screen sizes.

Performance

Flow:Lighthouse → PageSpeed → GTmetrix

Measure loading behavior and identify frontend optimization opportunities before handoff.

  • Lighthouse

    Used to review performance, accessibility, best practices, and SEO.

  • Google PageSpeed Insights

    Used to evaluate loading performance and identify frontend optimization opportunities.

  • GTmetrix

    Used as an additional reference for loading behavior and performance review.

Delivery

Flow:Responsive → browsers → RTL/LTR → final review

Before handoff, I verify responsive behavior across breakpoints, check major browsers, confirm Arabic RTL and English LTR layouts, and do a final review of interactions, polish, and content readiness. Delivery is copy-led here — no fake tool logins or integration CTAs.

AI-Assisted Engineering

Flow:Cursor / Codex / Claude Code / CodeRabbit

Use AI coding agents and assistants to move faster without skipping human validation.

  • Cursor

    Used to support implementation, refactoring, repository exploration, and faster technical problem solving.

  • Codex

    An AI coding agent used for repository-aware implementation support and coding assistance.

  • Claude Code

    An AI coding agent used for repository-aware assistance during implementation and review tasks.

  • CodeRabbit

    Used as an additional code-review layer for pull requests.

  • ChatGPT

    A general-purpose AI assistant used for drafting, research support, and problem exploration.

AI output is reviewed and validated before integration. Recommendations are not applied automatically.

My Setup

My Setup

  • Lenovo Legion Pro 7

    Primary development laptop for local builds, editors, browsers, and concurrent frontend engineering workloads.

  • LG UltraGear 34″ 2K

    Ultrawide display used for multi-pane coding, design review, documentation, and parallel application windows.

  • Ubuntu

    The Linux environment I use for development tools, commands, package management, and project workflows.