The “clean room” reimplementation defense is familiar in software IP law. The idea: if developers who never saw the original code independently reconstruct equivalent functionality from a specification, the output is generally held to be non-infringing. The doctrine has survived multiple rounds of copyright litigation.
AI has introduced a new variable. When the “developer” doing the reimplementation is a large language model rather than a human engineer, and when the LLM was trained on data that may have included the original code, the clean room defense becomes legally uncertain terrain.
That’s the situation emerging from the March 31, 2026 Claude Code leak. Approximately 512,000 lines of Anthropic’s code became publicly accessible. Within days, developers began using AI coding assistants to reconstruct equivalent functionality, framing the effort as a clean room implementation that avoids direct copying. Legal analysis from Bean Kinney identifies this as a novel and unresolved question: whether AI-assisted reimplementation, where the AI tool may carry training-data exposure to the leaked material, qualifies for the same clean room protection courts have extended to human-led implementations.
The copyright background matters here. The DC Circuit ruled in 2023 that fully AI-generated works lack human authorship and therefore copyright protection. According to legal analysis published by Bean Kinney, the Supreme Court declined to review that ruling in *Thaler v. Perlmutter* in March 2026, leaving the DC Circuit’s standard in place, though that SCOTUS cert denial cannot be independently confirmed from the sources available to this brief. If it stands, it has an ironic implication for the Claw-Code scenario: the AI-generated reimplementation may itself lack copyright protection, which changes the economics of the dispute for both sides.
The open questions stack up quickly: Does the clean room defense apply when the implementing “room” was an AI system that trained on the internet, including, potentially, the leaked code itself? Does the human developer directing the AI tool bear infringement liability for the AI’s output if that output is substantially similar to the original? And if the AI-generated reimplementation lacks its own copyright protection, what is Anthropic’s practical remedy?
PYMNTS has covered the broader contours of the IP dispute as it develops. The legal debate is current through April 2026; the outcome will depend on litigation that hasn’t been filed yet, or at least hasn’t produced rulings yet.
Watch for: any DMCA takedown actions Anthropic takes against repositories hosting the reimplemented code; any litigation filed asserting trade secret claims (a potentially stronger avenue than copyright for leaked source code); and how AI coding tool providers characterize their liability exposure when their products are used in this kind of reconstruction effort.
TJS perspective: The Claw-Code scenario is an early test case for a question the AI industry will face repeatedly, what happens when AI tools are used to work around IP protections in ways that don’t fit cleanly into existing legal categories? The clean room defense was designed for human developers following a structured process. Its application to AI-assisted reconstruction is genuinely unsettled, and the outcome will have implications well beyond this specific leak.