This book explores the conceptual foundations, including clarity, specificity, contextuality, and iterative refinement and the technical underpinnings of contemporary LLMs to present prompt engineering as a fundamental skill for effectively leveraging large language models (LLMs).
With a structured, step-by-step approach, the book introduces reusable prompt patterns such as persona templates, chain-of-thought reasoning, flipped interactions, and semantic filters, supported by case studies across multiple domains. Ethical considerations, memory and context management, and system-prompt interactions are emphasised throughout.
The final sections provide enterprise-focused guidance, detailing prompt generation, tuning, API integration, monitoring, and compliance, demonstrating how to move from concept to proof-of-concept in professional settings.
Key Features
-Comprehensive coverage of foundational and advanced prompt engineering concepts.
-Pattern-based, reusable strategies for real-world LLM applications.
-Step-by-step guidance on integrating prompts into enterprise workflows.
-Case studies across healthcare, e-commerce, education, and customer support.
-Ethical considerations, memory management, and responsible AI deployment.
