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Book Overview & Buying
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Table Of Contents
Architecting AI Software Systems
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Throughout this book, we have explored core principles of AI system architecture, focusing on managing complexity, ensuring scalability, and integrating AI technologies into enterprise software. We examined how software engineering best practices, such as modular design and structured data pipelines, help optimize AI-enabled systems. We also addressed challenges such as aligning AI applications with stakeholder expectations, implementing effective design patterns, and adopting iterative development cycles that adjust to changing data and business needs. Case studies and real-world examples provided a structured framework for balancing technical precision with flexibility.
This final chapter focuses on generative AI and Large Language Models (LLMs) as a case study in applying architectural best practices to real-world AI deployments. We will walk through the design of an LLM-powered customer support knowledge management...
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