AI & Startup Law

Is my AI-generated code safe to use commercially?

Applications built largely by AI coding agents carry three legal blind spots: open-source contamination (generated code can reproduce copyleft-licensed patterns without attribution), copyright uncertainty (purely AI-generated code lacks the human authorship U.S. law requires for protection), and diligence exposure (a founder often cannot represent that they cleanly own the codebase). None of this means AI tools cannot be used — it means the code needs audit, documentation, and an IP strategy first. Lysinski & Associates P.C. assesses that exposure.

What are the legal blind spots in AI-generated code?

Three — open-source contamination (generated code can reproduce copyleft-licensed patterns without attribution), copyright uncertainty (purely AI-generated code lacks the human authorship U.S. law requires), and diligence exposure (you may not be able to represent that you cleanly own the codebase).

None of this bans AI tools; it means audit and document before you rely on the code commercially.

Who owns code written by AI?

Purely AI-generated code generally is not protected by U.S. copyright, because the law requires human authorship; what you own turns on the human contribution.

Courts and the Copyright Office have held a machine cannot be the sole author, and in 2026 the Supreme Court declined to review that holding.

Can AI-generated code create open-source license problems?

Yes — a coding agent can reproduce patterns from copyleft code (for example, GPL-licensed code) without attribution, creating contamination risk.

This connects directly to open-weight and open-source license compliance. See the open-source page.

Can I raise money with a vibe-coded MVP?

You can, but an investor may want an IP representation you cannot honestly give without an audit and documentation.

Get the assessment before diligence, not during it.

How do I reduce the risk?

Audit the codebase, document how it was built, and put an IP strategy in place — distinguishing routine autocomplete from agent-generated architecture matters for the analysis.

That distinction is exactly where operator-level judgment helps.

Talk to an attorney who builds AI

Your AI-built MVP got traction — now an investor wants an IP rep you cannot honestly give. Get a legal-risk assessment from counsel who understands both the tools that wrote your code and the standards that will judge it. (773) 777-9888.

For the firm’s related legal service, see AI IP & training-data counsel.

(773) 777-9888 · info@lysinski.com ·

Frequently asked questions

Who owns code written by AI?

Purely AI-generated code generally lacks the human authorship U.S. copyright law requires, so it may not be protected at all; what you can own depends on the human contribution to it. Document where humans meaningfully shaped the code.

Is my AI-generated code safe to use commercially?

It can be used, but it should be audited first for open-source contamination and ownership gaps. The tools are not the problem; shipping unreviewed agent-generated code into a product you will raise on or sell is the risk.

What are the risks of building with Cursor, Copilot, Replit, or Bolt?

The same three across tools: open-source contamination from reproduced patterns, copyright uncertainty for purely AI-generated code, and a diligence gap where you cannot cleanly represent ownership. The fix is audit, documentation, and an IP strategy — not avoiding the tools.

Can I raise on a vibe-coded MVP?

Yes, but expect an IP representation you may not be able to give without review. Founders who built fast from an AI coding tool should get a legal-risk assessment before an investor asks for clean-ownership reps.

Does AI-generated code have more security defects?

Independent testing has found elevated security-defect rates in AI-generated code. The Veracode 2025 GenAI Code Security Report found that AI-generated code introduced security flaws in 45% of tests across more than 100 large language models. Treat that as a reason to review and test generated code, not to avoid it.

How do I document ownership of an AI-built codebase?

Keep records of how the code was produced, which tools were used, and where humans contributed, and pair that with an open-source compliance audit and an IP strategy. The goal is to be able to represent ownership credibly in diligence.

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