LOOKING AHEAD: The cost of running AI agents is starting to shape how developers design them – and it's one reason a growing number are rethinking the role of the prompt altogether. As more complex agent systems take hold, particularly in coding, developers are finding that continuously running multiple models and sub-agents can consume tokens quickly. That reality is forcing a shift toward more efficient, self-sustaining setups – systems designed to operate with minimal human input once they are in motion.
Developers have started calling these recurring setups 'loops.'
OpenAI engineer Peter Steinberger, creator of the OpenClaw project, has been vocal about that shift. "Here's your monthly reminder that you shouldn't be prompting coding agents anymore," he wrote on X. "You should be designing loops that prompt your agents." In practice, instead of typing one prompt after another, you set up a framework and let the agent keep working toward the goal.
A loop is essentially a recurring workflow. Rather than typing instructions at every step, you set a clear goal and a scaffold so the system can keep going until it's done. One example is the /goal command in tools such as Claude Code or OpenAI's Codex, which keeps an agent working through a task instead of stopping after each reply.
