AI Agents in Practice — Read from the beginning
The article discusses a practical guide to building AI agents, focusing on production challenges and engineering definitions. It highlights the difference between successful demos and the realities of production environments. The series aims to clarify the components and functioning of AI agents through various parts that will be published over time.
- ▪The series begins with an exploration of why AI agent demos often fail in production settings.
- ▪It defines an agent in engineering terms, emphasizing its components and operational boundaries.
- ▪Future parts of the series will detail the operational loop of AI agents and their decision-making processes.
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 23 AI Agents in Practice — Read from the beginning #ai #agents #architecture #webdev A practical, production-oriented guide to building AI agents — patterns over products, anti-hype, vendor-neutral. The Series Part 1: The Demo Worked. Production Didn't. Priya's refund went through on a shipped order. The model was right. The system around it wasn't. Why agent demos break the moment they meet production — and what the demo hid that production reveals.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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