Building a modern web application from scratch used to require weeks of setup: configuring framework dependencies, setting up bundlers, writing CSS utility classes, and manually coding core algorithms. With the advent of advanced AI coding assistants, that development paradigm has fundamentally shifted.
When building Tyspingo (`https://tyspingo.in/`)—a free online typing practice and speed test platform—the goal was to build a blazingly fast, zero-dependency web app using lightweight Vanilla JavaScript, semantic HTML5, and custom CSS3.
In this case study, we outline the technical architecture behind Tyspingo, detail how AI pair-programming accelerated development, and share practical lessons for web developers building AI-assisted web apps.
1. Architectural Vision & Zero-Dependency Tech Stack
When planning Tyspingo, performance and load speed were non-negotiable. Many modern web apps suffer from heavy framework bloat—loading megabytes of JavaScript before rendering a simple text box.
We chose a Zero-Dependency Vanilla Stack:
- Markup: Semantic HTML5 with accessibility (a11y) ARIA attributes.
- Styling: Custom Vanilla CSS3 utilizing CSS variables, Glassmorphism backdrop-filters, and CSS Grid/Flexbox layouts.
- Logic: Modular ES6+ Vanilla JavaScript managing DOM state, keydown event listeners, and timers.
- Hosting: High-speed global CDN deployment via Netlify.
2. The Core Typing Engine: Real-Time State Management
The heart of Tyspingo is its real-time typing engine. Unlike simple input fields, a professional typing tool must track keystrokes at a millisecond level:
| Engine Component | Technical Function | AI Acceleration Role |
|---|---|---|
| Keydown Event Handler | Captures physical key presses, handles Backspace penalties & Space bar. | Generated clean event delegation patterns. |
| WPM & Accuracy Calculator | Computes $(\text{Characters} / 5) / \text{Minutes}$ and Net WPM in real-time. | Prototyped mathematical formulas & error tracking. |
| DOM Character Renderer | Dynamically updates character spans with .correct or .incorrect classes. |
Optimized DOM reflows and class toggles. |
| Custom Text Parser | Sanitizes uploaded .txt documents and pastes. |
Wrote regex string sanitization pipelines. |
3. Building Arcade Games with requestAnimationFrame
To build Falling Words and Monkey Jump without external game libraries (like Phaser or PixiJS), we utilized native requestAnimationFrame() loops.
This ensured smooth 60fps rendering across desktop monitors while keeping game logic tight: tracking target position vectors, collision detection against danger lines, and target locking.
4. Crafting the Responsive CSS Design System
A website must wows users visually while maintaining high contrast for readability. We created a curated dark-mode design system in css/style.css and css/blog.css:
- Color Palette: Deep slate backgrounds (
#0f172a), glowing cyan accents (#38bdf8), and vibrant purple gradients (#7c4dff). - Glassmorphism UI: Dynamic
backdrop-filter: blur(18px)card containers. - Responsive Grid: Fluid layouts that adapt seamlessly from mobile screens (320px) to ultra-wide desktop displays (2560px).
5. The Human-AI Development Workflow
The build process followed a structured collaboration model:
- Human Director: Defined application architecture, user experience requirements, and game design rules.
- AI Code Generator: Produced modular JavaScript functions, CSS variable setups, and boilerplate HTML structures.
- Human Engineer: Conducted edge-case testing, resolved event listener memory leaks, tuned touch screen controls, and audited technical SEO.
6. Key Lessons for Web Developers
- AI is a Force Multiplier, Not a Replacer: AI excels at rapid coding, but human oversight is mandatory for architecture, state sync, and user empathy.
- Vanilla Web Standards Are Timeless: Building with native HTML/CSS/JS delivers instant page loads and zero dependency breaking changes over time.
Want to learn more about the specific AI tools used? Read our detailed comparison on ChatGPT, Codex, and Antigravity in Web Production, explore our case study on Can AI Build a Website Alone?, or try the final result by taking a Free Typing Speed Test on Tyspingo.
Frequently Asked Questions
How was Tyspingo built using AI?
Tyspingo was developed using AI coding tools for rapid prototyping, algorithm generation, and architectural planning, combined with human testing, UI design refinement, and manual code review.
What tech stack powers Tyspingo?
Tyspingo is built using lightweight Vanilla JavaScript (ES6+), semantic HTML5, custom responsive CSS3, and standard requestAnimationFrame game loops for zero external dependency overhead.
Did AI write 100% of Tyspingo's codebase?
No. While AI accelerated boilerplate generation and bug diagnostics, human engineering was required for DOM synchronization, state machine logic, touch event handling, and SEO content optimization.
Experience Tyspingo Live
Test the high-performance Vanilla JS typing engine built with AI collaboration!
Take a Free Typing Speed Test