🎮 Retro Hangman '95 Using KIRO

Source: Dev.to

Project Overview

• Game: Classic Hangman with intelligent adaptive features
• Tech Stack: HTML5, CSS3, JavaScript
• Live Demo:

Retro Revival Implementation

Classic Game Recreation ✅

• Base Game: Traditional Hangman word‑guessing mechanics
• Retro UI: Authentic Windows 95‑style interface with CRT effects
• Nostalgic Elements: Neon colors, pixel fonts, and 90s aesthetics

Modern AI Twist 🤖

• Intelligent Word Selection: AI‑driven difficulty progression based on player performance
• Smart Hint System: Context‑aware hints that adapt to player skill level
• Dynamic Category Matching: AI selects optimal word categories based on success patterns
• Adaptive Scoring: Machine‑learning‑inspired scoring that adjusts to player behavior

Technical Highlights

• State Management: Multi‑layered game state with persistent player profiles
• Algorithm Design: Progressive difficulty engine with performance analytics
• Pattern Recognition: Player behavior analysis for personalized experience
• Data Structures: Efficient word database with categorized difficulty tiers

Key Features

• 6 visual themes with authentic retro styling
• Smart category system (Animals, Nature, Technology, Fantasy)
• Performance tracking with adaptive difficulty
• Zero dependencies – pure vanilla JavaScript

Learning Focus: Complex Logic

This project demonstrates complex‑logic skills through:

• Adaptive AI Systems: Dynamic difficulty adjustment based on player performance
• State Management: Complex game state handling with persistence
• Algorithm Implementation: Smart word selection and hint generation
• Data Analysis: Player pattern recognition and behavior adaptation

Results

• Performance: <100 KB, instant loading
• Compatibility: All modern browsers
• User Experience: Seamless retro gaming with intelligent features
• Code Quality: Clean, maintainable architecture

🚀 PLAY LIVE DEMO

Successfully recreated classic Hangman with modern AI intelligence while maintaining authentic 90s retro aesthetics.