Requirements in Confluence. Architecture decisions in someone s head or a six monthbold Notion page. Code in Git. Slack threads nobody searches. And a new developer joining who has to piece all of it together from scratch every single time. We talk a lot about building smarter with AI, but the actual bottleneck isn t code generation. It s that by the time AI touches anything, half the reasoning behind the system is already gone. It generates against the what while the why has completely evaporated. The result: inconsistent decisions across sprints, onboarding that takes weeks instead of days, and AI suggestions that are locally correct but architecturally wrong. Has anyone actually solved context continuity on a real engineering team? Curious what s worked or what s failed spectacularly.