🔍 Read the full analysis: A Step-by-Step Approach To Exploring Software With An AI Agent on ThorstenMeyerAI.com
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TL;DR
A ThorstenMeyerAI.com article dated October 19, 2026, describes how developers can use Reverse Engineer Anything (REA) with AI coding agents to investigate specific behaviors in existing software. It outlines a step-by-step workflow and reports a QuickBooks Desktop case study, while warning that agent answers need evidence checks and that local analysis does not keep data from reaching the model provider.
A October 19 guide from ThorstenMeyerAI.com sets out a step-by-step way to use the open-source tool Reverse Engineer Anything (REA) with AI coding agents to investigate how existing software behaves. The article centers on a reported QuickBooks Desktop project in which a developer used REA and Ghidra to examine accounting rules, then built a local application whose financial statements reportedly matched Intuit’s sample company account by account, to the cent.
The guide presents REA as a way to gather evidence about a program’s internal behavior, not as a shortcut for asking an agent to recreate an application from its screens. REA combines a local MCP server, a command-line utility and an agent skill. It can connect with agents including Claude Code, Codex, Cursor and Gemini CLI, and its listed analysis targets include native applications, Electron and JavaScript software, .NET and Android apps, firmware, databases and websites observed through a browser.
The recommended workflow starts with a bounded question tied to a practical decision. Rather than asking an agent to “figure out” an entire accounting program, the article suggests investigating a single behavior, such as how a partial invoice payment changes the balance and which account receives the posting. The agent should report stored data, calculations and conditions, and label findings as observed, inferred or unknown. A useful check is whether it can explain one complete example with inputs and outputs.
Setup is another verification point. The article says REA requires Node.js 22.19 or newer; native analysis may also require a disassembler such as Ghidra. Its installer can configure supported agents, and the project’s diagnostic command checks files and prerequisites. The guide cautions that this does not prove a live connection: users should confirm that the agent actually calls an REA tool before trusting its account of a target.
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
The approach matters to developers who need to understand an existing program before replacing, integrating with or documenting it. A user interface can show what a program displays without revealing how it stores records or calculates results. Investigating one behavior at a time can turn that hidden logic into a specification that developers can test against concrete cases.
The QuickBooks example is presented as a case study, not an independent evaluation of REA or a guarantee that another agent will reach the same result. The source says the developer examined inventory arithmetic, account-type effects on budget signs, reconciliation balances and cash-basis report paths. It reports that the resulting app’s profit-and-loss statement, balance sheet and trial balance matched the official sample company to the cent. If accurate, that illustrates how careful investigation could support software replacement; it does not establish that every feature or edge case was reproduced.
AI software reverse engineering toolkit
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REA’s Tools and Reported Case Study
According to the article, REA is an MIT-licensed open-source project hosted on GitHub under morluto/rea. The source reports that version 6.7.0 was released October 18, 2026, and describes the project as having roughly 325,000 stars and 82,000 forks at the time of publication. Those figures are dated observations reported by the source, not measures of software accuracy or adoption.
The QuickBooks work described in the article used REA 6.4.0 and Ghidra to examine a trial of QuickBooks Desktop for Mac 2024. Its stated focus was selected accounting behaviors rather than a general audit of the product. The source frames REA as a tool for collecting evidence that a developer can use to make implementation decisions, not as a system that independently certifies a reconstruction.
“REA helps your agent find out.”
— ThorstenMeyerAI.com, describing REA’s role
disassembler software for software analysis
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Limits, Safety and Independent Checks
The reported QuickBooks result comes from the source article’s account of the developer’s project; the supplied material does not include an independent audit, a full test suite or enough detail to establish how broadly the match was tested. The article also refers to a published case study but the provided text ends before its full account and supporting evidence. It is therefore unclear which edge cases, versions or workflows were covered.
REA analyzes targets locally, according to the guide, but the results are sent to the AI agent and may also reach the model provider under that provider’s data policy. Local processing should not be read as a promise that information stays on the device. The source also warns that opening an untrusted program exposes it to analysis tools running with the user’s permissions. The performance of agents, coverage of REA’s analysis engines and reliability of inferred findings are not independently established in the supplied material.
AI coding agent tools for software investigation
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Verify Before Building on Findings
The guide’s next step for a developer is to choose a small, owned or otherwise authorized target, confirm that REA is connected, and test one specific behavior with a concrete example. Findings should be separated into observed, inferred and unknown statements, then checked against real inputs and outputs before they become implementation requirements.
The source does not announce a new release or a scheduled product milestone beyond reporting REA 6.7.0 as current on October 19, 2026. Further assessment of the QuickBooks example would require the full case study, its test coverage and independent confirmation of the reported matches. Until then, the reported result is a useful illustration of the method, not proof that REA can reliably reproduce complex software in general.
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Key Questions
What is REA?
Reverse Engineer Anything is an open-source toolkit that connects AI coding agents to software-analysis tools through an MCP server, command-line utility and agent skill, according to the article.
What does the guide say REA can help investigate?
It describes using REA to inspect specific software behaviors, including calculations, stored records and conditions that change results. Its listed targets include native programs, web applications, mobile software, firmware and databases.
Did the QuickBooks project prove REA can reproduce accounting software?
No. The source reports that one developer’s local app matched three financial statements for Intuit’s sample company to the cent. The supplied material does not provide an independent audit or establish that all features and edge cases were tested.
Does local REA analysis keep information away from an AI provider?
Not necessarily. The guide says the analysis runs locally, but results go to the agent and may be handled by its model provider under that provider’s data policy.
How can a user tell whether the agent is actually using REA?
The article says to verify tool use inside the agent, rather than relying only on the setup diagnostic. If the agent answers about a program without calling an REA tool, its response may be based on model guesses rather than an REA investigation.
Source: ThorstenMeyerAI.com
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