Web Application Generation

This field studies how AI can build websites and web applications from prompts, screenshots, design references, and videos. Common approaches use large language and vision-language models to generate code, with agents that plan, edit, render, and test applications; reinforcement learning can also use browser-execution feedback as a training signal. Benchmarks increasingly test visual fidelity, requirement coverage, and multi-step browser interactions, alongside harder settings such as evolving applications and full-stack development. Models can produce usable interfaces, but visual quality does not guarantee correct behavior, and reliable state handling, integration, security, and long-horizon changes remain difficult.