AI agents are learning on the job — just not for your whole team

When someone on a team corrects an AI agent — better prompts, better feedback, better context — that improvement disappears the moment a colleague opens the same tool. The correction doesn't transfer, and the next person starts from zero. The problem compounds in multi-agent workflows, where teams expect agents to share context across users and tasks. Without a shared memory layer, every team member effectively trains a different version of the same agent — and those versions never sync. That ga