Disclosure: I maintain Lynkr, an open-source LLM gateway with loop-guard middleware, so I have a stake in this argument. Read this as a thesis to challenge, not a neutral survey.
Agent discourse has shifted from prompts to loops: the read-act-observe cycle that keeps running until the model decides it's done. My contrarian take is that most so-called loop engineering is optimizing the wrong variable. A longer, richer loop is usually a convergence failure wearing a costume. The well-engineered loop is the short one that knows when to stop.
The consensus I'm arguing against
When an agent fails, the default move is to give the loop more:
More turns before it gives up.
