AI / ML

Multi-Agent Architecture

A system design where multiple specialized AI agents collaborate on complex tasks, each bringing domain expertise. A typical split gives one agent attribution, another forecasting, another creative analysis, and so on. Unlike a single monolithic model, each agent is narrow and shares context with the others through a common memory layer, so a finding in one domain can propagate: an attribution agent revising what a channel really drove lets a forecasting agent revise its projection without a human relaying it. The tradeoff is coordination cost, which is why orchestration is a design problem in its own right.