Researchers have introduced FASE, a novel approach to measuring code quality through adaptive semantic entropy, addressing the limitations of current methods in multi-agent code generation. This paradigm aims to simulate human software engineering, but its reliability is compromised by large language model hallucinations and error propagation. FASE offers a principled way to quantify uncertainty without relying on ground-truth answers, providing a more robust alternative to existing methods. By leveraging semantic entropy, FASE can help mitigate the risks associated with autonomous software development, such as system crashes and security vulnerabilities. The introduction of FASE has significant implications for the development of more reliable and secure software systems, particularly in scenarios where state-aligned threat activity raises the stakes from criminal to geopolitical1. This matters to practitioners because it enables them to develop more robust and reliable software systems, reducing the risk of errors and security breaches.