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Building Agentic AI Systems

You're reading from   Building Agentic AI Systems Create intelligent, autonomous AI agents that can reason, plan, and adapt

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Product type Paperback
Published in Apr 2025
Publisher Packt
ISBN-13 9781803238753
Length 288 pages
Edition 1st Edition
Concepts
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Authors (2):
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Anjanava Biswas Anjanava Biswas
Author Profile Icon Anjanava Biswas
Anjanava Biswas
Wrick Talukdar Wrick Talukdar
Author Profile Icon Wrick Talukdar
Wrick Talukdar
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Foundations of Generative AI and Agentic Systems
2. Chapter 1: Fundamentals of Generative AI FREE CHAPTER 3. Chapter 2: Principles of Agentic Systems 4. Chapter 3: Essential Components of Intelligent Agents 5. Part 2: Designing and Implementing Generative AI-Based Agents
6. Chapter 4: Reflection and Introspection in Agents 7. Chapter 5: Enabling Tool Use and Planning in Agents 8. Chapter 6: Exploring the Coordinator, Worker, and Delegator Approach 9. Chapter 7: Effective Agentic System Design Techniques 10. Part 3: Trust, Safety, Ethics, and Applications
11. Chapter 8: Building Trust in Generative AI Systems 12. Chapter 9: Managing Safety and Ethical Considerations 13. Chapter 10: Common Use Cases and Applications 14. Chapter 11: Conclusion and Future Outlook 15. Index 16. Other Books You May Enjoy

Summary

In this chapter, we discovered that while advanced intelligent agentic systems hold immense potential to drive innovation, enhance creativity, and revolutionize various industries, their deployment and development must be approached with utmost care and responsibility. Armed with awareness of the potential risks and challenges associated with generative AI, organizations and stakeholders can proactively implement measures to ensure safety, uphold ethical principles, and address privacy and security concerns. By doing so, they can harness the transformative power of these technologies in a trustworthy and accountable manner, fostering confidence among users and stakeholders. Embracing a proactive and responsible approach to generative AI development involves implementing robust testing and monitoring frameworks, adhering to ethical guidelines and frameworks that prioritize human well-being, accountability, and inclusive governance, and establishing comprehensive data governance...

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