🔍 Read the full analysis: What To Explore First When Using AI On An Existing Codebase on ThorstenMeyerAI.com
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TL;DR
A ThorstenMeyerAI.com article dated Oct. 19, 2026, describes how to use the open-source Reverse Engineer Anything (REA) toolkit with coding agents to investigate existing software. Its guidance is to ask a narrow, decision-focused question, confirm the agent is actually using REA, and distinguish observed behavior from inference and unknowns. The article cites a QuickBooks case study, but its claims about matching accounting results are based on the project author’s account.
ThorstenMeyerAI.com published a guide on October 19 to using the open-source Reverse Engineer Anything (REA) toolkit with AI coding agents to inspect existing programs. The article’s central advice is to investigate one specific behavior at a time, verify the agent is connected to REA, and ask it to separate observed evidence from inference and unknowns—an approach intended to reduce reliance on plausible but unverified explanations when building or changing software.
REA is described as a local Model Context Protocol (MCP) server, a command-line tool and an agent skill. It can connect with agents including Claude Code, Codex, Cursor and Gemini CLI. The article says its analysis tools cover native applications, Electron and JavaScript programs, .NET and Android apps, firmware, saved network traffic, WebAssembly and SQLite databases. For websites, it can observe activity in a browser the user controls.
The guide recommends framing an investigation around a behavior and the decision it will inform. Rather than asking an agent to “figure out how this program works,” it suggests questions such as how a partial invoice payment changes a balance and which account receives the posting. The agent should explain stored data, calculations and conditions that affect the result, then walk through a complete example with inputs and outputs.
The source says REA 6.7.0 was released October 18 and requires Node.js 22.19 or newer. Native analysis may also require tools such as Ghidra and Java, or licensed software such as Hopper or IDA. After setup, the article advises checking prerequisites and confirming the live connection inside the agent. It warns that a diagnostic command checks files and prerequisites, not whether the agent can actually call REA.
Infographic 01 · Reverse Engineer Anything
Five places to point REA first, and how to tell when the answer is wrong.
REA gives coding agents such as Claude Code and Codex tools to inspect programs, apps and browser sessions. Each investigation needs a finishable question and a check.
npx rea-agents@latest setupThe five investigations
What to ask, and the check that catches a wrong answer.
- 1
Ask a question you can finish
One behaviour, one decision it informs. Example: how a partial payment changes an invoice balance.
It’s wrong ifThe agent can't walk through one concrete example with real inputs and outputs. - 2
Get REA connected and confirmed
Run the guided setup, then doctor, then call binary_session inside the agent before any real target.
It’s wrong ifAnswers arrive without a single REA tool call: you're reading the model's guesses. - 3
Turn a business rule into a spec
Inputs, stored fields, formula, edge cases, plus test cases checked against the original's own output.
It’s wrong ifYour version and the original disagree on a test case, even by one cent. - 4
See what has to survive a copy
Find what an app writes to the clipboard and what it keeps locally, then design your own copy and paste.
It’s wrong ifThe explanation doesn't predict what lands in a plain text editor, an email and your app. - 5
Your own app, your equipment, an old program
Start with software you own or rely on. Ask what it sends, stores or calculates when you do one thing.
It’s wrong ifIt only works for the example you watched. Test with a new file or a read-only command first.
Sources: REA on GitHub (stars via GitHub API, 19 Oct 2026); REA installation guide; REA security policy.
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From Software Behavior to Testable Rules
Existing software often contains rules that are not obvious from its interface: how a balance is calculated, what happens when a record changes, or which conditions alter a report. The guide argues that inspecting these mechanisms before implementing a similar feature can turn a user’s experience into explicit business rules that developers can test.
The article points to Ledger Reborn, a local accounting application whose author reportedly used REA to examine QuickBooks Desktop for Mac 2024. According to the source, the project’s profit-and-loss statement, balance sheet and trial balance matched the original program’s results for Intuit’s sample company, account by account and to the cent. That is a case-study claim reported by the article, not an independently verified benchmark. Still, it illustrates why evidence about calculations may be more useful than reproducing a familiar screen.
The approach also addresses a practical risk in AI-assisted development: an agent can produce a confident explanation without having inspected the target. Checking tool use and demanding a concrete example gives developers ways to identify unsupported answers before they shape a design or implementation.
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How REA Fits Into an Agent Workflow
REA is identified as an MIT-licensed open-source project hosted on GitHub under the name morluto/rea. The source reports that it had about 325,000 stars and 82,000 forks on October 19, 2026, following a period on GitHub’s trending page in early October. Those are dated project statistics; the article does not give a comparison baseline, so they do not establish a rate of growth.
The workflow described starts with setup, then checks that the agent can access REA’s tools, and finally opens an investigation into a program the user owns or is authorized to inspect. The source notes that analysis runs locally, but results are passed to the AI agent and may also reach its model provider under that provider’s data policy. It also quotes the project’s warning: “This is not a sandbox.” Running analysis tools on an unknown program can expose the user’s machine to the risks of handling any untrusted file.
“REA supplied evidence and imperf”
— Thorsten Meyer, describing the Ledger Reborn case study
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Evidence, Privacy and Safety Limits
The supplied article does not include the complete account of the Ledger Reborn investigation. It says the project’s results matched QuickBooks for Intuit’s sample company, but does not provide the underlying test data or an independent assessment. The claim should therefore remain attributed to the case study as reported, rather than treated as proof that REA can reproduce other programs’ behavior.
REA’s local analysis does not mean all information stays on the user’s device: the source says findings are sent to the connected agent and may be handled by the model provider under its own data policy. The article does not specify how each provider handles those results. It also does not establish whether every supported program or analysis engine will work equally well, or how complete an agent’s findings will be. Users should treat unknown binaries as untrusted and verify conclusions against concrete program behavior.
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Verify the Connection Before Investigating
The source describes no scheduled product announcement or independent review. Its practical next step for readers is to set up REA, restart the coding agent, check prerequisites, and confirm that the agent can call an REA tool before relying on its explanation. Begin with a harmless program the user owns, then pose a narrow question with a clear decision in mind.
For each investigation, ask the agent to label statements as observed, inferred or unknown, and require one complete example that can be checked. If it only describes screens or answers without calling REA, the guide says the result may be a model guess rather than an inspection. Further evaluation of the QuickBooks case study and the tool’s behavior across other software remains open.
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Key Questions
What is REA?
Reverse Engineer Anything is an open-source toolkit that connects coding agents to software-analysis tools through an MCP server, command-line utility and agent skill.
What should I ask an AI agent to investigate first?
Choose one behavior tied to a specific decision, such as how a partial payment changes an invoice balance. Ask for the stored data, calculation and conditions, then request a concrete example.
How can I tell whether the agent is using REA?
Check that the agent actually calls an REA tool. The source says the setup diagnostic checks files and prerequisites, but does not verify the live agent connection.
Does local analysis mean my results stay private?
No. The source says REA runs locally, but findings go to the connected agent and may also reach its model provider under that provider’s data policy. The handling depends on the provider.
Is the QuickBooks result independently verified?
The source reports that Ledger Reborn matched specified QuickBooks accounting reports for Intuit’s sample company. The supplied material does not include independent verification, so the result should be treated as a case-study claim.
Source: ThorstenMeyerAI.com
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