Use Cases and Best Practices

Chapter 7 shifts its focus from individual features to the broader perspective of how enterprise AI components—such as retrieval-augmented generation, vector databases, fine-tuning pipelines, agent frameworks, and model registries—collaborate on Red Hat platforms. Rather than advocating a single "correct" approach, it introduces various use case patterns, ranging from using different teacher model models to RAG implementation, and shares best practices, including integrating third-party libraries within virtual environments, pinning OSTree images for reproducibility, configuring OpenAI-compatible APIs, and automating processes via Ansible. The chapter also provides deployment snippets to help practitioners develop portable, auditable, and adaptable solutions.