Open source gives developers something powerful: the ability to inspect, modify and improve the software they depend on. But as AI-generated code becomes increasingly common, a new question is emerging: does visible source code automatically mean trustworthy software?

AI can generate an impressive open-source project in minutes. It can create dependencies, configuration, authentication logic, tests and documentation too. But who reviewed those decisions? Where did the code come from? Which dependencies are safe? What happens when nobody understands the generated implementation well enough to maintain it?

This session explores what trust should mean in modern open-source development. We will examine practical examples around AI-generated code, dependency risk, maintainability, licensing, security and human review, and look at how developers can use open-source software without treating "the source is available" as equivalent to "the software is trustworthy."

The goal is not to discourage AI or open source. It is to develop a stronger engineering mindset for building with software that is increasingly generated, reused and assembled at unprecedented speed.