In open-source projects, contributors often wear many hats—developer, tester, writer—and resources are typically stretched thin. This multitasking environment can make it challenging to maintain comprehensive and accurate API documentation. Yet, high-quality documentation is vital for the usability and adoption of any open-source project.

This talk focuses on how AI can help simplify one aspect of documentation development: testing. By using AI to simulate user interactions, we can efficiently identify gaps and inconsistencies in API documentation that a contributor might miss due to exceptional knowledge of the topic.

By integrating AI-driven user simulations into your workflow, you can improve the quality of your documentation while managing multiple responsibilities more effectively. This approach not only benefits individual contributors but also strengthens the overall success and sustainability of open-source projects.