Minification makes JavaScript hard to read but doesn't provide security. Claude Code has demonstrated that large language models (LLMs) can decode minified code with surprising efficiency. By using abstract syntax trees (ASTs), which represent code as tree structures, these models can process and analyze minified files much faster than traditional methods. The author shares an experiment where they compared two versions of a popular npm package, utilizing LLMs to generate ASTs and synthesize findings. This approach revealed features, logging details, and architecture information that would typically remain hidden in minified code. The article highlights a significant shift in how software engineers should approach code security. With agents capable of quickly reverse-engineering frontend code, nearly any React-based web application is vulnerable. Users can recreate the complete source code of these applications without authentication, exposing sensitive information like internal features and testing frameworks. The author stresses that while obfuscation was once a barrier to accessing code, the effort required has drastically decreased with modern tools. To protect sensitive intellectual property, the author recommends rethinking deployment strategies. This includes securing code chunks so only authenticated users can access them and potentially moving sensitive logic to the backend. The landscape of web application security is changing rapidly, and developers need to adapt to prevent unauthorized access to their frontend code and sensitive business information.