AI coding assistants are becoming popular tools for writing code and documentation among research software engineers (RSE). A recent survey of academic postdoc attitudes towards AI tools suggests that over half of the researchers taking up these tools use them for generating, editing, and troubleshooting code (Nordling 2023). Organisations active in creating training materials for RSE are also considering the use of these tools in their teaching curriculum. The legal implications of using AI coding assistants in research, however, are ever hardly considered. Yet, these legal implications can threaten the future development of Free/Libre and Open Source Software (FLOSS) in research due to multiple Intellectual Property Rights (IPR) issues ranging from the copyright status of AI generated code to the potential infringement of third-party IPR. The talk takes inspiration from a blog post on a popular AI coding assistant, GitHub Copilot, written by a lawyer and open source contributor, Matthew Butterick, and entitled “This Copilot is stupid and wants to kill me”. The aim of the talk is to review the most pressing legal issues that RSE can face when they decide to use AI coding assistants, and how their choice of tools can prevent them from releasing their own code under a free/open source license, make them breach the re-use conditions of open source software they are building on, and also expose them to litigations due to inappropriate use of copyrighted material. IPR laws and regulations for software have been crucial in shaping the world of free/libre and open source software as we know it today. FLOSS licensing models have been supporting the development of tools that can be used by everyone royalty-free, and fit in with the open science commitment embraced by many funders of academic research. The usefulness of these tools is confirmed every day by growing user communities, including RSE communities around the world. RSE should be fully aware of the risks posed to FLOSS by the use of AI coding assistants and should carry out a risk-benefit analysis before they decide to adopt these tools.