Crafting Intelligent AI Agents

Unlock the power of transformer large language models (LLMs) with Crafting Intelligent AI Agents: Leveraging Transformer LLMs for Real-World Applications, a comprehensive, hands-on guide designed for developers, AI engineers, data scientists, and product leaders eager to build production-ready AI agents. Authored by Ethan Quan, this 14-chapter book dives deep into transformer fundamentals, covering attention mechanisms, embeddings, and architectures, and progresses to advanced topics like pretraining, fine-tuning at scale, and retrieval-augmented generation. Master self-correcting planning loops, tool integration, and robust inference pipelines with step-by-step tutorials, practical code snippets in Python and TypeScript, and real-world case studies such as boosting agent reliability by 25% with optimized prompting.
Explore scalability and resilience in deployment, monitoring and governance for ethical AI, cost optimization strategies, and security best practices for transformer models. The book culminates in a detailed guide to deploying autonomous agents to production, enriched with insights from real-world transformer applications and a forward-looking chapter on future trends. Whether you're a beginner with no prior transformer expertise or an enthusiast seeking to enhance decision-making and workflow automation, this book equips you with the tools to create intelligent, scalable, and secure AI agents. With concise lessons and actionable checklists, achieve tangible results in days, not months, and transform your AI ambitions into reality.
Key Topics: Transformer LLMs, attention mechanisms, pretraining, fine-tuning, retrieval-augmented generation, self-correcting planning loops, tool integration, inference pipelines, scalability, resilience, monitoring, governance, cost optimization, security, production deployment, ethical AI, real-world case studies.
Who This Book Is For:

• Developers integrating AI into applications.
• AI Engineers building autonomous systems.
• Data Scientists automating analyses with transformers.
• Product Leaders defining AI roadmaps.
• No prior transformer knowledge required-just curiosity and drive.

• Comprehensive Coverage: From transformer internals to production deployment.
• Practical Focus: Hands-on tutorials and reusable code for immediate impact.
• Future-Ready: Insights into emerging trends in transformer-based AI agents.