Description

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.