IMHO this guide should have been called "a theoretical guide for building agents". In practice, you cannot build agents like that if you want them to do useful

IMHO this guide should have been called "a theoretical guide for building agents". In practice, you cannot build agents like that if you want them to do useful things. Also, the examples provided are not only not practical but potentially bad practice. Why do you need a manager pattern to control a bunch of language translation agents when most models will do fine especially for latin-based languages? In practice a single LLM will not only be more cost-effective but also good for the overall user experience too. Also, prompting is the real unsung hero that barely gets a mention. In practice you cannot get away with just a couple of lines describing the problem / solution at a high-level. Prompts are complex and very much an art form because and frankly, let's be honest, there is no science whatsoever behind them - just intuition. But in practice they do have enormous effect on the overall agent performance. This guide is not aimed at developers to really educate how to build agents but at business executives and decision-makers who need a high-level understanding without getting into the practical implementation details. It glosses over the technical challenges and complexity that developers actually face when building useful agent systems in production environments.