Windsurf Case Study: Solo Developer Migrates Legacy jQuery E-Commerce Site to Next.js in 5 Days

From jQuery Spaghetti to Next.js in Five Days: A Solo Developer’s Windsurf Migration Story

When freelance developer Marcus Chen landed a contract to modernize a six-year-old jQuery e-commerce platform with 80+ components, 14,000 lines of JavaScript, and zero TypeScript coverage, the client expected a three-week timeline. Using Windsurf’s AI-powered IDE, he delivered in five days. This case study breaks down exactly how.

The Legacy Codebase: What We Started With

  • Framework: jQuery 3.3.1 with Handlebars templates- Components: 83 loosely coupled UI modules- Lines of code: ~14,200 JS, ~6,800 HTML/CSS- Build system: Gulp with manual concatenation- Pain points: No type safety, global state mutations, inline event handlers, mixed concerns

Why Windsurf Was the Right Tool

Unlike traditional AI code assistants that operate on single files, Windsurf’s Cascade mode understands entire codebases. For a migration this size, three capabilities proved essential:

  • Codebase-wide understanding — Windsurf indexed all 83 components and mapped their dependency graph before suggesting any changes.- Multi-file refactoring flows — A single prompt could refactor a jQuery plugin into a React component, update all imports, and adjust parent components simultaneously.- Cascade auto-resolution — After the initial conversion, 217 TypeScript errors appeared. Cascade resolved 203 of them automatically in a single pass.

Day-by-Day Migration Workflow

Day 1: Setup and Codebase Indexing

Install Windsurf and initialize the project: # Install Windsurf IDE (macOS/Linux) curl -fsSL https://windsurf.com/install.sh | sh

Or download from windsurf.com for Windows

Launch and open your project directory

windsurf ~/projects/legacy-ecommerce

Initialize Next.js alongside the legacy code

npx create-next-app@latest next-ecommerce —typescript —tailwind —app cd next-ecommerce npm install

Open Windsurf’s Cascade panel (Cmd+Shift+P → “Cascade: Open”) and let it index the legacy codebase: # In Cascade prompt: Analyze the ../legacy-ecommerce directory. Map all jQuery components, their dependencies, shared utilities, and global state patterns. Create a migration plan prioritized by dependency depth.

Windsurf produced a dependency graph and a suggested migration order — leaf components first, layout shells last.

Day 2: Core Component Conversion

Using multi-file refactoring, Marcus converted the product catalog module — the largest single piece at 1,400 lines: # Cascade prompt: Convert legacy-ecommerce/src/js/product-catalog.js and its Handlebars template product-catalog.hbs into a Next.js App Router page at app/products/page.tsx. Replace jQuery AJAX calls with Server Actions. Preserve all filtering logic. Use TypeScript strict mode.

Windsurf generated five files in one pass: app/products/page.tsx — Server Component with data fetching app/products/ProductGrid.tsx — Client Component for interactive grid lib/types/product.ts — TypeScript interfaces lib/actions/products.ts — Server Actions replacing $.ajax app/products/loading.tsx — Streaming skeleton UI

Here is the converted Server Action replacing the original jQuery AJAX call: // lib/actions/products.ts ‘use server’

import { Product, FilterParams } from ’@/lib/types/product’

export async function fetchProducts(filters: FilterParams): Promise<Product[]> { const params = new URLSearchParams() if (filters.category) params.set(‘category’, filters.category) if (filters.minPrice) params.set(‘min_price’, String(filters.minPrice)) if (filters.maxPrice) params.set(‘max_price’, String(filters.maxPrice)) params.set(‘page’, String(filters.page || 1)) params.set(‘limit’, String(filters.limit || 24))

const res = await fetch( ${process.env.API_BASE_URL}/products?${params}, { headers: { ‘Authorization’: Bearer ${process.env.API_KEY} }, next: { revalidate: 60 } } )

if (!res.ok) throw new Error(‘Failed to fetch products’) return res.json() }

The corresponding ProductGrid client component: // app/products/ProductGrid.tsx ‘use client’

import { useState, useTransition } from ‘react’ import { fetchProducts } from ’@/lib/actions/products’ import type { Product, FilterParams } from ’@/lib/types/product’

export default function ProductGrid({ initial }: { initial: Product[] }) { const [products, setProducts] = useState(initial) const [isPending, startTransition] = useTransition()

function handleFilter(filters: FilterParams) { startTransition(async () => { const results = await fetchProducts(filters) setProducts(results) }) }

return (

  {isPending && Loading...}
  {products.map((p) => (
    
      

{p.name}

${p.price.toFixed(2)}

  ))}

) }

Day 3: Batch Conversion of Remaining Components

Marcus grouped the remaining 78 components into batches by feature area and ran Cascade prompts for each group: # Cascade prompt (batch mode): Convert these 12 cart-related jQuery modules to React components:

  • cart-drawer.js, cart-item.js, cart-summary.js, cart-upsell.js, cart-discount.js, mini-cart.js, cart-shipping.js, cart-tax.js, cart-empty.js, cart-counter.js, cart-note.js, cart-gift.js Use Zustand for cart state instead of window.cartState global. Place output in components/cart/ with proper TypeScript types.

Day 4: TypeScript Error Resolution with Cascade

After converting all components, running npx tsc --noEmit revealed 217 TypeScript errors. Marcus triggered Cascade auto-resolution: # Cascade prompt: Run TypeScript compiler and fix all errors across the codebase. Prefer strict typing over 'any'. Add missing interface properties. Fix event handler types for React synthetic events. Resolve module resolution issues.

Results after a single Cascade pass:

MetricBefore CascadeAfter Cascade
Total TS errors21714
Auto-resolved203 (93.5%)
Manual fixes needed14
Files modified64
Time elapsed~8 minutes
The remaining 14 errors were ambiguous business logic cases requiring human judgment — exactly where a developer's expertise matters most.

Day 5: Testing, Optimization, and Deployment

# Generate test stubs with Windsurf

Cascade prompt:

Generate Jest + React Testing Library tests for all components in components/cart/. Cover add-to-cart, remove, quantity update, and discount application flows.

Run the full suite

npm run test — —coverage

Build and deploy

npm run build vercel deploy —prod

Pro Tips for Power Users

  • Use Cascade context pinning: Pin critical files like your type definitions and API client so every Cascade prompt has consistent context without re-specifying them.- Batch by dependency layer: Convert leaf components first, then work upward. This prevents cascading breakage during migration.- Set .windsurfrules: Create a .windsurfrules file in your project root with project conventions so Cascade output stays consistent:
    # .windsurfrules
    framework: next.js 14 app router
    style: tailwind css
    state: zustand for client state, server actions for mutations
    types: strict typescript, no ‘any’
    components: functional only, named exports
    testing: jest + react testing library
    - Incremental verification: After each batch conversion, run npx tsc —noEmit before moving on. Catching errors early keeps Cascade resolution efficient.- Leverage Cascade memory: Windsurf remembers prior refactoring decisions within a session. Early corrections propagate automatically to later conversions.

Troubleshooting Common Issues

ErrorCauseSolution
Cannot find module '@/lib/types'tsconfig paths not configuredEnsure tsconfig.json includes "paths": {"@/*": ["./src/*"]} matching your project structure
Cascade suggests any typesInsufficient context about data shapesPin your API response type files before running conversion prompts
Event handler type mismatchesjQuery events vs React SyntheticEventPrompt Cascade specifically: "Use React.MouseEvent and React.ChangeEvent, not DOM Event types"
Hydration mismatch errorsServer/client rendering differencesAdd 'use client' directive to components using browser APIs or state. Use dynamic(() => import(...), { ssr: false }) for jQuery widget wrappers during incremental migration
Cascade modifies unrelated filesOver-broad prompt scopeBe specific about which files to modify. Use file path references in prompts rather than general descriptions
## Results Summary
MetricBefore (jQuery)After (Next.js)
Lighthouse Performance3894
First Contentful Paint4.2s0.8s
Bundle size (gzipped)412 KB127 KB
Type safety coverage0%98.4%
Development timeEst. 15-20 days manual5 days with Windsurf
## Frequently Asked Questions

Can Windsurf handle migrations from frameworks other than jQuery?

Yes. Windsurf's codebase understanding works with any JavaScript or TypeScript project. Developers have documented successful migrations from AngularJS, Backbone.js, Ember, and vanilla JavaScript to modern frameworks like Next.js, Nuxt, and SvelteKit. The key is providing clear Cascade prompts that specify the source and target patterns.

How does Windsurf’s Cascade mode differ from using ChatGPT or Copilot for large refactors?

Cascade maintains awareness of your entire project simultaneously. While single-file AI assistants require you to manually copy context between files, Cascade tracks cross-file dependencies, shared types, import chains, and state management patterns. This is why it could resolve 203 TypeScript errors in one pass — it understood how changes in one file would ripple across 64 others.

Is Windsurf suitable for team projects or only solo developers?

Windsurf works for teams of any size. The .windsurfrules configuration file can be committed to version control so all team members get consistent AI behavior. For larger teams, Cascade’s multi-file awareness becomes even more valuable since it respects existing code conventions across a broader contributor base. The solo developer scenario in this case study simply highlights the productivity multiplier effect most dramatically.

Explore More Tools

Grok Best Practices for Academic Research and Literature Discovery: Leveraging X/Twitter for Scholarly Intelligence Best Practices Grok Best Practices for Content Strategy: Identify Trending Topics Before They Peak and Create Content That Captures Demand Best Practices Grok Case Study: How a DTC Beauty Brand Used Real-Time Social Listening to Save Their Product Launch Case Study Grok Case Study: How a Pharma Company Tracked Patient Sentiment During a Drug Launch and Caught a Safety Signal 48 Hours Before the FDA Case Study Grok Case Study: How a Disaster Relief Nonprofit Used Real-Time X/Twitter Monitoring to Coordinate Emergency Response 3x Faster Case Study Grok Case Study: How a Political Campaign Used X/Twitter Sentiment Analysis to Reshape Messaging and Win a Swing District Case Study How to Use Grok for Competitive Intelligence: Track Product Launches, Pricing Changes, and Market Positioning in Real Time How-To Grok vs Perplexity vs ChatGPT Search for Real-Time Information: Which AI Search Tool Is Most Accurate in 2026? Comparison How to Use Grok for Crisis Communication Monitoring: Detect, Assess, and Respond to PR Emergencies in Real Time How-To How to Use Grok for Product Improvement: Extract Customer Feedback Signals from X/Twitter That Your Support Team Misses How-To How to Use Grok for Conference Live Monitoring: Extract Event Insights and Identify Networking Opportunities in Real Time How-To How to Use Grok for Influencer Marketing: Discover, Vet, and Track Influencer Partnerships Using Real X/Twitter Data How-To How to Use Grok for Job Market Analysis: Track Industry Hiring Trends, Layoff Signals, and Salary Discussions on X/Twitter How-To How to Use Grok for Investor Relations: Track Earnings Sentiment, Analyst Reactions, and Shareholder Concerns in Real Time How-To How to Use Grok for Recruitment and Talent Intelligence: Identifying Hiring Signals from X/Twitter Data How-To How to Use Grok for Startup Fundraising Intelligence: Track Investor Sentiment, VC Activity, and Funding Trends on X/Twitter How-To How to Use Grok for Regulatory Compliance Monitoring: Real-Time Policy Tracking Across Industries How-To NotebookLM Best Practices for Financial Analysts: Due Diligence, Investment Research & Risk Factor Analysis Across SEC Filings Best Practices NotebookLM Best Practices for Teachers: Build Curriculum-Aligned Lesson Plans, Study Guides, and Assessment Materials from Your Own Resources Best Practices NotebookLM Case Study: How an Insurance Company Built a Claims Processing Training System That Cut Errors by 35% Case Study