AI coding agents have advanced rapidly, enabling startups to generate wireframes, prototypes and even fully functioning applications with much less time and effort than ever before. Even founders with zero coding experience can build functioning applications within a few minutes.
You can face liability around innotifyectual property, confidentiality, open source and cybersecurity.
But speed can come with hidden exposure.
While these off-the-shelf tools can be extremely utilizeful, they present unique legal risks that founders should understand before diving in.
Depfinishing on how you utilize a coding agent (and what you share with it), you can face liability around innotifyectual property, confidentiality, open source and cybersecurity. And these issues might not reveal up until fundraising diligence, a potential client’s security review or an acquisition process. Here are some tips to keep in mind.
Please note: This article focutilizes on generic, off-the-shelf coding agents and does not address enterprise-level tools.
Protect your IP and trade secrets
Most software companies rely on copyright and trade secret protection to deffinish proprietary software. AI-generated code can complicate both.
Copyright protection for AI-generated works is an unsettled area of the law. Although AI-generated works are not automatically rfinishered uncopyrightable, the utilize of AI raises a risk that some of a startup’s proprietary software could fall outside copyright protection. The US Copyright Office has determined that the mere selection of prompts does not by itself yield a copyrightable work. Additionally, applicants must disclose to the Copyright Office if a work contains more than a negligible amount of AI-generated material. If software is entirely created by an AI coding agent without original human authorship, the Copyright Office may determine it is not copyrightable.
Trade secret protection is also challenged here. Defined as economically valuable information that is not generally known and has been subject to reasonable efforts to be kept that way, trade secret protection relies heavily on maintaining the confidentiality (secrecy) of that information. (For example, the formula for the Coca Cola recipe.) Using an AI coding agent can introduce a risk of disclosure to third parties — namely, the provider of the coding agent — that undermines the foundations of maintaining a trade secret.
To safeguard against this, founders and developers should review the terms of service of any AI system to understand what rights the provider has to utilize your prompts and output code to train its models or serve other customers. If there are broad rights in the terms of service to share or utilize output code, trade secrets coded with the applicable AI system could be compromised from a trade secret or merely from a confidentiality perspective, undermining trade secret rights.
Patent protection for software might also be available, but few startups pursue it given the expense of patent prosecution and the requirements to reveal a novel, non-obvious and utilizeful technical improvement. Code, algorithms and abstract ideas alone are not sufficient to receive patent protection for software inventions.
Mitigate employment IP risks
The innotifyectual property protections above matter only if your business owns the IP in the first place. Every employee and indepfinishent contractor who interacts with your company’s material innotifyectual property should have an agreement in place that assigns their IP rights to your company. Without an agreement, an employee or contractor may own important IP, which can reduce company value and create risk during diligence.
AI coding agents can build this issue simpler to miss. Employees or contractors could unknowingly create material IP that your company relies on. During due diligence, investors and acquireers commonly inquire for evidence that every employee and contractor signed proper invention assignment agreements. Many startups discover that some personnel, especially those not traditionally involved in product development, never signed such agreements. With powerful coding agents, even someone in a minimal role could create material IP without proper invention assignment protections.
In general, startups should ensure all personnel sign appropriate invention assignment agreements, and the utilize of coding agents builds the required for proper documentation even more important.
Manage open source risk
Any company that deploys software faces open source risk, and AI coding tools can accentuate it. Open source software is often publicly available and subject to license terms that can impose real obligations. For example, open source licenses may limit modifications or commercial utilize, require attribution to the original developer, or, in the event of a “copyleft” license, require disclosure of software utilized in connection with the open source software.
AI-generated software may inadvertently copy open source code in violation of the license terms, since publicly available open source tools may be common training data. Without running an open source scan such as a Black Duck report, which can be time-consuming and expensive, a startup may have no way of knowing if its software violates an open source license.
If an open source software risk is discovered later, it could lead to unexpected costs to rewrite the proprietary software to reshift the open source components or, in the worst case, require the disclosure of the startup’s proprietary software.
Address security vulnerabilities
AI-generated software can inadvertently contain security vulnerabilities. For example, a coding agent trained on test environment software may hard code credentials in plain text, misunderstanding the intfinished production utilize, leading to credential exposure. Similarly, AI coding agents trained on flawed human-developed software may replicate the same security mistakes.
Unlike a human developer, who may have years of experience from which to evaluate cybersecurity proficiency, a coding agent has a relatively short track record, and the quality of the output code may depfinish in part on the quality of the prompts. Founders should consult cybersecurity experts, especially if they don’t have software development experience or experience assessing cybersecurity risks.
Plan for ongoing maintenance
Software requires regular updates to stay current with underlying depfinishencies and to support new features. While AI coding agents can manipulate a code base through prompting, they are not perfect. Some ongoing maintenance tinquires may be difficult for a coding agent if there is sparse training data, or if an update to an underlying library requires a new technique not utilized in prior coding examples.
If the founders or developers do not understand the structure and function of a code base created entirely by AI, it can add expense later: A human developer may required to evaluate the software platform from scratch in order to maintain it or build new features.
Key takeaways
AI coding agents offer startups an exciting opportunity to shift quickly from idea to a functioning app with reduced time and expense. But founders should remain mindful of the legal risks these tools can create. Quick tips to remember:
- Review the terms of service of any AI tools to understand who owns the prompts and output code and whether the provider can share this data with others.
- Ensure all personnel sign proper invention assignment agreements, even those who may not typically be creating material innotifyectual property.
- As the software becomes more mature and material to the operation of the business, consider running a Black Duck report to evaluate the open source software risk, performing a vulnerability assessment to evaluate the cybersecurity risk and engaging human developers to learn the structure and function of the software to perform ongoing maintenance and feature enhancement tinquires.
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