I Tested The Viral Github Repo That Reverse Engineers Anything

TL;DR Reverse Engineering Anything (REA) is not a new technology but an interface for existing tools. AI agents can replicate software features without it, making the hype misleading.

REA uses old tools to automate reverse engineering

• The tool acts as an MCP (Model Context Protocol).
• It connects AI agents to legacy disassemblers like Ghidra and IDA.
• These tools are decades old and were released by agencies or companies long ago.
• The agent gathers data from browser dev tools and decompiles code.
• The output is pseudocode and a list of unknowns, not final source code.

The demo shows AI can build apps without special libraries

• The speaker rebuilt the macOS Preview app using Claude and Codecept.
• One session used REA, while another used standard AI coding agents.
• Both versions produced functional apps with similar features like zooming and sharing.
• The version without REA was faster and performed drawing functions better.
• This proves dedicated reverse engineering libraries are not strictly necessary.

Hype focuses on GitHub stars rather than technical value

• Viral videos highlight star counts instead of working demonstrations.
• The creator calls this a "memetic moment" rather than a technological breakthrough.
• Many demos create games or fun projects that lack commercial viability.
• Intellectual property laws prevent selling reversed software legally.
• The excitement is driven by social media trends, not practical utility.

General AI will replace specialized reverse engineering workflows

• Large language models like Claude and Codex can rebuild applications instantly.
• Front-end and back-end components will become generic and widely available.
• Wrapper apps providing extra visual features will merge into core models.
• Agents can use screenshots and reasoning to replicate functionality directly.
• Built-in model updates will handle these tasks within one or two months.

Next steps

• Prepare for a shift where general AI builds software directly.
• Focus on creating new ideas rather than copying existing apps.
• Understand that legal barriers remain for intellectual property theft.
• Monitor how built-in AI capabilities evolve to replace external tools.