I Tested The Viral Github Repo That Reverse Engineers Anything

Summary

The video examines Reverse Engineer Anything (REA), an MCP that lets AI agents use reverse-engineering tools to analyze software and attempt to recreate its features.

How REA works

• A user asks an AI agent to inspect and recreate an app or feature.
• REA connects the agent to tools such as Ghidra, Hopper, and IDA. It can also use browser developer tools to gather information.
• These tools provide analysis—often pseudocode and descriptions rather than original source code. The agent uses those findings in an iterative process to build a recreation.

Hands-on test

The presenter asked Claude to recreate the Mac Preview app with REA, while another Claude session attempted the same task without it. The REA version used Ghidra and eventually reproduced several visible functions, including zooming, sharing, rotating, and annotating images.

However, the version without REA finished first. The REA process took longer and involved repeated testing. The presenter judged the results broadly similar, suggesting that a general-purpose agent can achieve a reasonable recreation without REA.

Assessment and implications

• REA’s novelty is mainly its convenient connection between AI agents and established reverse-engineering tools. The tools themselves have existed for years.
• The presenter argues that online attention and GitHub-star growth may be running ahead of the demonstrated practical value. He views many viral examples as impressive experiments or “meme” demos rather than proof of a major new breakthrough.
• AI agents are increasingly able to inspect and reproduce software through screenshots and other built-in capabilities, even without a specialized reverse-engineering library. Dedicated tools may speed up the work, but some of their functions could become less necessary as models improve.
• The broader trend may make software features easier to reproduce and lower the barrier to combining existing ideas. However, copying commercial apps can raise intellectual-property issues, and the presenter cautions that this does not automatically create a viable business.
• He expects general AI agents to absorb more of these capabilities over time.

Guides, tutorials, and examples mentioned

• Setup: Ask an AI agent to download and install REA, then request that it inspect and recreate a target application.
• Demo: Recreating Mac Preview with and without REA.
• Other examples discussed: An Apple TV remote recreation, a proposed Photoshop recreation, and game concepts combining elements from existing games. These are cited as examples, not independently verified results.

Main speaker and sources

• Main speaker: Nick Saraev.
• People cited: Matthew Berman; Amjad, identified as Replit’s CEO; and Jaden Williams.
• Tools discussed: REA, Ghidra, Hopper, IDA, Chrome developer tools, Claude, and Orca.