AI Agents in Practice — Part 3: How the Control Loop Actually Works
The article discusses the control loop in AI agents, detailing its five steps: observe, decide, act, check, and repeat. It emphasizes the importance of each step in ensuring effective communication and task completion in production environments. The author highlights common engineering challenges that arise during the execution of these steps, particularly in multi-turn interactions.
- ▪The control loop consists of five steps: observe, decide, act, check, and repeat.
- ▪Each step of the loop must perform real work to avoid production failures.
- ▪The article outlines specific engineering problems related to state, stopping, and context discipline.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 2006864) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Gursharan Singh Posted on May 27 AI Agents in Practice — Part 3: How the Control Loop Actually Works #ai #agents #llm #architecture AI Agents in Practice (3 Part Series) 1 AI Agents in Practice — Part 1: The Demo Worked. Production Didn't. 2 AI Agents in Practice — Part 2: What Makes Something an Agent 3 AI Agents in Practice — Part 3: How the Control Loop Actually Works Part 3 of 8 - AI Agents in Practice series.
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