Running a 70B model to summarize an email wastes money; running a 3B model to review production code courts disaster. Multi-model design isn’t about collecting models — it’s about architecture that puts the right model on the right task at the right time, with the simplest pattern that survives the constraints.
Single-agent systems peaked with bounded tasks and one prompt. Production moved on: organizations now run double-digit agent counts, and a large share of multi-agent pilots die within months of deployment. The killer isn’t the idea — it’s picking the wrong coordination topology, or the right one without knowing its failure modes.
Agent skills and MCP servers are often presented as competing ways to extend an AI agent. That framing is wrong: a skill teaches the agent how to work, while an MCP server gives it governed access to live capabilities. The useful question is not which standard wins, but where each responsibility should live.