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Eric S. Raymond’s October 2026 declaration is a forecast, not a measured finding that every proprietary program has already been defeated. His argument is that AI-assisted reverse engineering is reducing the specialist time needed to turn a distributed executable into understandable, source-like code. If that capability scales, compiled software may no longer provide the durable secrecy advantage it once did.
What Raymond’s quote means
Raymond was reacting to the weakening of a long-standing assumption in commercial software: that shipping a compiled binary keeps the original design and implementation sufficiently obscure. A customer can run the program, but the source code, internal algorithms and engineering choices remain with the vendor.
His claim is that large language models (LLMs) can narrow that gap. An AI system can inspect a binary’s instructions, data structures and calling patterns, infer likely program behavior, and present a human-readable reconstruction. That does not necessarily recreate the original source files, comments or exact variable names. It can, however, make a previously opaque program understandable enough to analyze, modify or reimplement.
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The Firefighter example that prompted the forecast
From an old DOS binary to readable Pascal
Raymond said he asked an AI assistant to decompile Firefighter, an ancient DOS shareware game. The assistant inferred that the executable had been written in Borland Pascal by examining its data layout. It then produced Pascal-like code with sensible function and variable names rather than an unintelligible dump of assembly instructions.
Why the result mattered to him
Raymond transpiled the recovered program to Rust for his heritage-games collection. He initially regarded the exercise as a stunt and doubted that the technique would scale beyond a small, old program. He later learned that people were applying similar methods to complete AAA games. His reported inference was blunt: “If they can be decompiled, anything can be.”
That sentence is an extrapolation from examples, not evidence that an AI can reliably reconstruct every commercial program. Older software, common compiler patterns and relatively simple game logic may be unusually tractable. Modern products can include obfuscation, native and managed components, proprietary hardware interfaces, encrypted assets, distributed services and enormous amounts of domain-specific behavior.
Why compiled code may be less secret than before
Traditional reverse engineering often required disassembly expertise, patience and extensive manual annotation. AI can assist with those labor-intensive steps: identifying likely functions, grouping related routines, proposing names, explaining control flow and translating fragments into a higher-level language.
The important change is economic as much as technical. A task that was once too expensive for all but a specialist team could become practical for a motivated individual or a smaller organization. That could expose implementation techniques, make compatibility projects easier and reduce the value of secrecy based solely on distributing a binary.
The Wentworth Report reproduced Raymond’s broader formulation that shipped executables, including firmware images, should be treated as highly transparent once a motivated person can apply an LLM to them. “Transparent” in this context means inspectable and increasingly understandable, not identical to the vendor’s original source tree.
Where the argument is strongest—and where it is not
| Question | Locally installed software | Vendor-hosted software as a service |
|---|---|---|
| Where the executable runs | On the customer’s computer or device | On infrastructure controlled by the vendor |
| Exposure to binary analysis | A distributed binary can be copied and examined offline | The main executable is normally kept behind a network connection |
| What AI-assisted reverse engineering can reveal | Potentially control flow, data structures and implementation behavior | Client code and exposed interfaces remain inspectable; server-side logic is not delivered in full |
| Dependence on changing data or rules | May be limited to what is packaged with the release | Can depend on continuously updated data, models, policies or business rules |
| Offline resilience | Can continue working without the vendor’s servers, subject to licensing | Usually depends on continued service availability |
This is why Raymond identifies software as a service as a principal refuge for proprietary implementation. Keeping the executable on the vendor’s infrastructure limits direct access to the full server program. It does not make a service impossible to study: clients, APIs, outputs and observable behavior can still be analyzed, and unauthorized access remains a separate security issue.
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The available reporting is qualitative. It cites Raymond’s Firefighter experiment and reports of similar work on AAA games, but it does not provide an independent benchmark showing that AI can reconstruct every class of commercial software. The claim that closed-source business models will collapse is therefore expert opinion and prediction, not a settled measurement.
Legal and contractual limits
Technical ability does not determine permission. Copyright rules, patents, contracts and software licences can restrict copying, modification, distribution or commercial use. The legal analysis cited in coverage also treats continuously changing domain knowledge as a limit: reconstructing code is not the same as acquiring the vendor’s confidential datasets, operational procedures, customer relationships or current business rules.
Engineering limits
- Decompilation may recover behavior without recovering the original architecture or intent.
- Generated names and explanations are inferences and require human verification.
- Obfuscation, encryption, unusual hardware and undocumented operating-system behavior can increase difficulty.
- A program that relies on remote services may be only partly reconstructable from its client binary.
- Reimplementation still requires testing, maintenance and compliance with applicable rights and licences.
What the forecast could change for software makers
Vendors that rely on binary secrecy may need to assume that determined analysts can eventually understand substantial portions of a release. Defensive priorities could shift toward protecting credentials and server-side logic, minimizing sensitive material in clients, hardening update and licensing systems, and treating distributed binaries as public artifacts rather than confidential source containers.
Open-source projects could benefit because AI-assisted reconstruction may make abandoned formats, compatibility layers and preservation work more achievable. At the same time, an easier path to imitation does not remove the value of copyright, patents, contracts, trademarks, support, trust, continuously updated services or specialized expertise.
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Raymond is a long-standing software developer and open-source figure, identified by HDD Law as a co-founder of the Open Source Initiative and the author of The Cathedral and the Bazaar. His October 2026 statement is best read as a provocation about the declining secrecy value of shipped code. It is not proof that all proprietary software has already become open source, nor that AI can reproduce every product on demand.
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