The article describes the Plan-and-Solve agent architecture, which improves upon the ReAct model by first generating a complete action plan before executing any steps. Unlike ReAct's locally optimal, …
This article is a practical, production-oriented guide to building AI agents, focusing on engineering patterns rather than hype or specific products. It explains why agent demos often fail in producti…
The article explains that AI agents often get stuck in infinite loops, repeatedly calling the same tool with slightly different queries, which wastes tokens and increases costs. This is identified as …
The article explains the ReAct (Reasoning and Acting) agent paradigm, introduced by researchers from Princeton and Google in 2022, which improves upon Chain-of-Thought (CoT) reasoning by allowing a la…