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Agentify: The Art, Science, and Engineering of Successful AI Agents
AI agents are beginning to upend software in a fundamental way. Over the next decade, the familiar...
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AI agents are beginning to upend software in a fundamental way. Over the next decade, the familiar SaaS model will be displaced by complex adaptive systems that act as autonomous coworkers: observing context, taking initiative, delivering outcomes. The shift has already begun, embedded in workflows you use today, but it will accelerate as agents become more competent, trustworthy, and human-like. This book is for those building this future. Grounded in complex systems theory and AI research and engineering, but balanced by design and product thinking, AGENTIFY draws on work with dozens of teams building AI agents today.
Packed with lessons that outlast the weekly flux of new models and frameworks, AGENTIFY combines research depth, engineering rigor, product acumen, and design craft in one meticulous volume. AGENTIFY shows how agents differ from apps: continuous planning loops, memory, tool use, meta-learning, and world modeling. It also develops architectural patterns for autonomy and oversight. Topics include reinforcement learning, synthetic and curated training data, fine-tuning and tool formation, protocols, precision context engineering, and subagent orchestration. Case studies, research surveys, and insights from work with dozens of real teams will help you to ship agents that deliver outcomes.
Here you'll find the foundational patterns, trade-offs, and mental models to navigate the future of software. No other resource in print today spans as many dimensions critical to your agents' success.
Author: Michael Palmer
Publisher: Taos Research Corporation
Published: 11/14/2025
Pages: 428
Binding Type: Paperback
Weight: 1.25lbs
Size: 9.00h x 6.00w x 0.87d
ISBN: 9798993196213
About the Author
Palmer, Michael: - Michael Palmer is the CEO and Chief Scientist of Taos Research Corporation, which focuses on using AI to accelerate business and scientific outcomes for global companies as well as non-profits, government, and academia. Previously, Michael was CTO of U.S. Bank in charge of AI, digital, and data technologies. His career spans over 25 years in Silicon Valley with roles leading large-scale AI & machine learning and data platforms for Yahoo, founding roles at multiple successful startups, and experience in venture capital at Kleiner Perkins Caufield & Byers. Michael holds two master's degrees from Stanford University: one in engineering with a focus on robotics and computer science, the second an MBA. He was a Fulbright Scholar under the auspices of the U.S. Department of State. Michael graduated from Haverford College, Phi Beta Kappa, and magna cum laude. His undergraduate studies were in math, physics, and economics.
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