This episode of Rooting exposes the hidden enemy of modern agent architectures: context rot. We explore why long context windows aren’t a silver bullet, how attention budgets degrade over time, and the four ways rot shows up in real systems—poisoning, distraction, confusion, and clash. Listeners learn why million-token prompts still fail, why observability must extend into the model’s working memory, and how emerging strategies such as isolation, selective retrieval, compression, external memory, semantic chunking, and standards such as MCP are reshaping how robust agents are built. This is a practical, technical deep-dive for architects and developers who want their AI systems to survive contact with reality.

This episode includes AI-generated content.