This article provides a thorough analysis of agent engineering based on official guides from Anthropic and OpenAI. It covers key architectural decisions such as tool use, memory management, and orchestration patterns. The author compares different agent frameworks and offers practical advice on selecting the right approach for specific use cases. The content is structured around real-world deployment considerations, including scalability, monitoring, and error handling. This is a valuable resource for engineering teams looking to move from prototype to production with AI agents. The synthesis of two major AI labs' recommendations provides a balanced perspective on current best practices.
A comprehensive guide synthesizing Anthropic and OpenAI's official agent building recommendations, covering architecture patterns, selection criteria, and deployment strategies.