WINDSURF TRAINING : CODE FASTER WITH AI ASSISTANCE

We start at the beginning: install Windsurf, understand the interface, set up your first workspace. You'll see how it differs from VS Code and why Cascade AI makes it powerful.

You'll migrate your existing VS Code configuration, import extensions, customize themes and keybindings, and set up your development environment exactly how you like it.

We'll explore the Cascade panel, understand AI context windows, and learn how to frame requests so the AI actually helps instead of generating garbage code.

You'll configure Git integration, connect to remote repositories, set up SSH keys, and prepare your workflow for AI-assisted development.

At the end of this module, you have Windsurf installed and configured. You understand the basics and you're ready to write your first AI-assisted code.

This is where Windsurf shines. You'll learn to use Cascade flows to generate complete functions, refactor existing code, and handle multi-file changes with intelligent context awareness.

You'll discover how to provide effective context through chat, reference specific files and functions, and guide the AI to produce exactly what you need without endless back-and-forth.

We'll cover code generation patterns: creating new features from scratch, implementing APIs, building UI components, and writing tests—all with AI assistance that understands your project structure.

You'll learn to review AI suggestions critically, validate generated code, fix edge cases, and maintain quality standards while moving fast.

At the end of this module, you can leverage Cascade to write production code. You understand when to trust AI suggestions and when to intervene.

Debugging becomes faster when AI understands your stack traces. You'll learn to use Windsurf to identify bugs, analyze error messages, and implement fixes with context-aware suggestions.

You'll master refactoring techniques: extracting functions, renaming variables across files, restructuring modules, and improving code architecture with AI assistance that tracks dependencies.

We'll cover performance optimization: identifying bottlenecks, optimizing algorithms, refactoring inefficient code, and implementing best practices with AI recommendations.

You'll learn to handle technical debt: documenting legacy code, adding type annotations, improving test coverage, and modernizing codebases with intelligent automation.

At the end of this module, you can maintain and improve existing code efficiently. You know how to use AI for debugging and refactoring without breaking things.

Windsurf doesn't work in isolation. You'll learn to connect it with Docker containers, manage environments, run services locally, and develop full-stack applications with AI assistance.

You'll integrate with databases: connect to PostgreSQL, MongoDB, Redis, write queries, manage migrations, and build data models with intelligent schema suggestions.

We'll cover API development: building REST endpoints, implementing GraphQL resolvers, handling authentication, and integrating third-party APIs with AI-generated boilerplate.

You'll set up CI/CD workflows: configure GitHub Actions, automate testing, deploy to production, and use Windsurf to write pipeline configurations and infrastructure code.

At the end of this module, you can build complete applications with Windsurf. You know how to integrate all the tools in your stack and automate your development workflow.

Now we go deeper. You'll learn advanced Cascade techniques: chaining multiple AI requests, maintaining context across sessions, and handling complex refactoring that spans dozens of files.

You'll discover prompt engineering for developers: how to structure requests for optimal results, provide effective context, and get AI to follow your coding standards and architecture patterns.

We'll cover team collaboration: establishing AI-assisted workflows, code review practices when using AI, maintaining consistency across team members, and measuring productivity improvements.

You'll explore Windsurf extensions and customization: building custom AI commands, integrating with language servers, and extending Windsurf for your specific tech stack.

At the end of this module, you're an advanced Windsurf user. You can leverage AI to handle enterprise-scale projects and train your team on AI-assisted development.

Theory is done. You'll work on complete projects: building a SaaS application from scratch, implementing authentication and payments, creating admin dashboards, and deploying to production—all with Windsurf.

We'll analyze real case studies from Hack'celeration clients: how we used Windsurf to build MVPs in weeks, refactor legacy codebases, implement complex features, and accelerate development cycles.

You'll learn migration strategies: moving from other IDEs to Windsurf, training teams, measuring ROI, and establishing AI-assisted development as your standard workflow.

We'll cover common pitfalls: when AI suggestions go wrong, how to maintain code quality, avoiding over-reliance on AI, and keeping your skills sharp while using assistance.

At the end of this module, you have battle-tested experience. You've built real projects with Windsurf and you know exactly how to apply it in your company or personal work.