Career Tracks Intermediate English Premium Track

Become a 10X Developer

Make AI coding tools your default workflow and ship 5–10x faster.

Designed & taught byDinesh Kushwaha FormatLive cohort, tailored to the group

Duration: 7 modules + capstone
Taught in: English

What you'll walk away with

Ship features 5–10x faster with AI coding tools
Confidence across Copilot, Cursor, Claude Code and Windsurf
Debug and refactor unfamiliar codebases with AI
A portfolio-ready deployed project

Who it's for

Developers, students and builders who want to multiply their output with AI-native coding workflows.

Curriculum

Ship production software much faster by making AI coding tools your default workflow instead of an occasional trick. You will develop, debug and deploy real applications with GitHub Copilot, Cursor, Claude Code and more.

Module 01 · The Vibe Coding Mindset

Prompt-first development, thinking in specs and intents instead of syntax, and the generate → run → refine loop that makes AI coding reliable.

From spec to working code
When to trust AI output and when to verify it
The iterative generate, run, refine loop

Hands-on project: Turn a one-paragraph app idea into a working scaffold in under 15 minutes.

Module 02 · Your AI Pair-Programming Toolkit

Hands-on setup and comparison of the tools AI-native developers use today.

GitHub Copilot: completions, chat and workspace edits
Cursor: codebase-aware chat and multi-file edits
Claude Code: agentic terminal-based development
Windsurf & Cody: when to reach for them

Hands-on project: Configure a personal AI dev environment tuned to your stack.

Module 03 · Rapid Prototyping & Scaffolding

Generate full app skeletons, UI components and API endpoints from natural language, and make safe multi-file edits.

Frontend, backend and database from one prompt chain
UI components from a design brief
Consistent codebase-aware edits

Hands-on project: Scaffold a complete CRUD application from a single prompt chain.

Module 04 · AI-Assisted Debugging & Refactoring

Feed stack traces and logs to AI, find root causes fast, and safely refactor code you didn't write.

Explaining unfamiliar codebases
Root-causing bugs from traces and logs
Refactoring legacy code safely

Hands-on project: Diagnose and fix a deliberately broken real-world codebase.

Module 05 · Testing & Code Quality With AI

Generate meaningful tests, run AI code review, and catch security issues before they are committed.

Unit and integration tests from existing code
AI-assisted code review
Security scanning in your daily workflow

Hands-on project: Take a project from 0% to meaningful test coverage.

Module 06 · AI-Native Git & Deployment Workflows

AI-written commit messages and PR summaries, automated review bots, and CI/CD scaffolded with AI.

Commit messages and PR summaries
Automated review bots
CI/CD pipelines and one-click deploys

Hands-on project: Ship a change through a full AI-assisted Git → CI → deploy pipeline.

Module 07 · Capstone: Build & Ship a Real Product

Take an idea all the way to a live, deployed product using the whole AI toolchain.

Hands-on project: A fully working, deployed application for your portfolio.

Tools & technologies

GitHub CopilotCursorClaude CodeWindsurfCodyGitCI/CD

Your instructor

Dinesh Kushwaha

Founder, Dinesh AI Academy · Principal Software Engineer & Application Architect

Dinesh has spent 18+ years architecting and delivering 50+ enterprise-scale platforms and has coached more than 1,000 engineers. He teaches AI the way he builds it: practical, secure, and focused on what works in production.

Read Dinesh's story

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