Generative AI has revolutionized how organizations tackle problems accelerating the journey
from concept to prototype to solution. While these applications enhance efficiency they often
require extensive planning drafting and revising to complete complex tasks. By combining many
of these actions AI agents offer greater autonomy and efficiency but understanding and
deploying them remains a challenge for many organizations especially as technology and
research rapidly develops. This book is your indispensable guide through this intricate and
fast-moving landscape. Author Michael Albada provides a practical and research-based approach
to designing and implementing single- and multi-agent systems. It simplifies the complexities
and equips you with the tools to move from concept to solution efficiently. By the end you'll:
Understand the distinct features of foundation model-enabled AI agents Discover the core
components and design principles of AI agents Explore design trade-offs and implement effective
multi-agent systems Design and deploy tailored AI solutions enhancing efficiency and
innovation in your field Michael Albada is a seasoned machine learning engineer with expertise
in deploying large-scale solutions for major tech firms including Uber ServiceNow and
Microsoft. He holds degrees from Stanford University the University of Cambridge and Georgia
Tech specializing in machine learning.
