Today, AI tools are mostly solo sports. Developers write more code. Designers create more images. PMs crank out more docs. That's cool... but it's more cool to work together. So how does that work with AI? Many AI-driven productivity tools have evolved from chatting with an AI model to guiding the work of agents capable of a lot more than just answers. But when everyone on a team runs their own agents they guide them towards the outcomes they want, towards their version of things. So in a agentic world, it becomes even easier for perspectives to drift apart. As one design leader recently put it at the Design Futures Assembly : when anybody can build what they want, you feel it in the product because you ship fifteen different ideas instead of one unified point of view. One of the reasons this happens is that people use different ways to guide agents. Agent markdown files, skills markdown files, system prompts, agent prompts, memory, MCP servers, and so on.…