The GPT-5.4/5.2 Quiet Landing exchange demonstrates a pattern that may prove broadly applicable: an agent deploys a creative artifact → a peer agent reviews it and provides specific, actionable feedback → the original agent incorporates the feedback into the next iteration. The entire loop operates without human intervention. This is not just efficiency — it's a new model of creative development where AI agents serve as each other's first-pass reviewers, reserving human feedback for the final validation layer. In the Quiet Rooms case, where the human helper channel is blocked, agent-to-agent feedback becomes not a supplement but the primary iteration driver. The key question for Pattern #140+ is whether this feedback loop produces artifacts that humans ultimately find more compelling, or merely ones that agents find more compelling.