Stop Prompting Your Agents. Start Designing Loops….

2026-06-20 · Source: Artificial Intelligence on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

The concept of "agent loops," or "loop engineering," is emerging as a significant shift in AI engineering, moving beyond traditional prompting. Boris Cherny of Anthropic and Peter Steinberger, creator of OpenClaw and now at OpenAI, highlight this change, with Google's Addy Osmani coining the term "loop engineering." This paradigm redefines the interaction with AI models: instead of manually typing sequential prompts, engineers now design automated loops where the AI model functions as a subroutine called by their code. This allows agents to autonomously perform tasks like spinning up sub-agents, writing prompts, and designing systems without direct human input.

Key takeaway

For AI Engineers focused on building autonomous systems, you should prioritize designing agent loops over traditional sequential prompting. This approach transforms the AI model into a callable subroutine within your code, enabling agents to operate independently, generate prompts, and design systems. Consider exploring frameworks that support loop engineering to enhance agent productivity and reduce manual intervention in complex AI workflows.

Key insights

AI engineering is shifting from direct prompting to designing automated loops where models act as subroutines.

Principles

• Models become subroutines in code.
• Engineers design the loop, not prompt it.
• Loop engineering automates agent interactions.

Method

Design a loop that calls the AI model as a subroutine, enabling agents to autonomously generate prompts and design systems.

In practice

• Automate prompt generation.
• Spin up sub-agents for complex tasks.
• Design systems without manual input.

Topics

• Agent Loops
• Loop Engineering
• AI Engineering
• Autonomous Agents
• Prompting
• OpenClaw
• Anthropic Claude

Best for: AI Architect, AI Engineer, Machine Learning Engineer, Prompt Engineer

Related on AIssential

• You Shouldn’t Be Prompting AI Anymore. You Should Be Designing Loops. — The future of AI interaction is designing autonomous, verifiable loops, not just prompting agents.
• What is Loop Engineering? — Loop Engineering automates the iterative interaction with coding agents, freeing humans from repetitive prompting.
• Autoresearch, Agent Loops and the Future of Work — AI agentic loops enable autonomous, iterative experimentation and continuous improvement across various domains.
• Agents: Inner Loop vs Outer Loop — Agent "loop closing" is about learned behavior within a hardcoded cycle, not new infrastructure.
• Why AI Agents Need to Check Their Own Work — Semantic control loops enable AI agents to self-correct and adapt by understanding the meaning of goals, not just numerical targets.
• Autoresearch, Agent Loops and the Future of Work — Agentic loops, like Karpathy's auto research, enable autonomous, iterative optimization based on objective metrics.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence on Medium.