Jed Borovik discusses the origins of Jules, an autonomous coding agent born from the breakthroughs of generative AI like Stable Diffusion. Developed within Google Labs through close collaboration with DeepMind, Jules operates on dedicated infrastructure and is designed for long-running, continuous coding tasks. As models have improved, Google has simplified its agent architecture, moving away from complex scaffolding toward minimalist designs. A key technical shift involves replacing traditional embeddings-based RAG with attention-based search for more effective code understanding. Jules has transitioned from a preview to a production product, supported by growing developer adoption and integration with platforms like GitHub. Managing massive context windows—up to 2 million tokens—relies on advanced compression techniques. The podcast also explores the future of software engineering, where AI augments developers rather than replacing them, enabling focus on higher-level design. Emerging practices like interactive planning and spec verification are replacing 'vibe coding,' while multimodal inputs and computer use APIs are expanding how developers interact with AI agents.