Building Tomorrow’s Systems Today: Best Practices for Architecting Software with Generative AI and Large Language Models
Keywords:
Generative AI, Large Language Models, AI Architecture, Prompt Engineering, System Design, AI Integration, Software Best Practices, LLM APIs, Model Fine-Tuning, Responsible AI, Intelligent SystemsAbstract
Generative AI and Large Language Models (LLMs) such as GPT, Claude, and PaLM have redefined the possibilities of intelligent software. These technologies are no longer experimental—they are becoming integral components of modern systems, capable of reasoning, generating human-like content, automating workflows, and enabling new modes of interaction. However, incorporating them into robust, scalable, and responsible software requires a new architectural mindset. This paper explores the best practices for architecting software systems that integrate LLMs effectively. It covers considerations such as API orchestration, prompt engineering, latency and performance trade-offs, fine-tuning strategies, context management, cost optimization, and security. The aim is to provide a practical, future-facing framework for engineers and architects seeking to build AI-native applications that are adaptable, intelligent, and trustworthy.
