Agent as Superintelligence: Building, Evaluating, and Understanding AI Agents, from Practical Systems to Possible Futures - Couverture souple

Patil, Niket

Couverture souple

ISBN 13 : 9798164804909

Editeur : Independently published, 2026

Synopsis

Agent as Superintelligence

Building, Evaluating, and Understanding AI Agents, from Practical Systems to Possible Futures

AI agents are moving beyond answering questions. They can plan tasks, use tools, retrieve information, maintain context, and take actions across multiple steps. But how do we make these systems useful, reliable, secure, and worthy of trust?

Agent as Superintelligence is a practical guide to understanding and engineering AI agents, from foundational concepts to the broader questions surrounding advanced machine intelligence.

Inside, you will explore:

• Foundations of agency: Understand how agents differ from chatbots, conventional automation, and fixed workflows.

• Architecture and memory: Learn how models, tools, state, retrieval, planning, and orchestration work together.

• Evaluation and reliability: Define success, test failure modes, preserve evidence, and build effective recovery procedures.

• Security and oversight: Examine permission boundaries, untrusted inputs, human approval, and responsible deployment.

• Multi-agent systems: Understand coordination, specialization, verification, and the costs of added complexity.

• Superintelligence and evidence: Separate demonstrated capabilities from generality, autonomy, emerging research, and future forecasts.

• Practical worksheets and code: Turn concepts into reviewable experiments with explicit constraints, measurable outcomes, and documented limitations.

Through the recurring illustrative story of Mira, technical explanations, architectural patterns, evaluation methods, and hands-on working records, this book connects engineering decisions to the people who depend on the systems being built.

The central lesson is straightforward: a capable agent is not automatically a reliable one. Good engineering requires evidence, bounded permissions, meaningful human oversight, and a clear understanding of when not to delegate.

Whether you are a developer, AI practitioner, technical student, researcher, or builder exploring agentic systems, this book offers a structured way to understand what agents can do, how to evaluate them, and what responsible implementation demands.

Build with curiosity. Evaluate with evidence. Deploy with responsibility.

Détails de l'édition

• Éditeur: Independently published
• Date d'édition: 2026
• Langue: anglais
• ISBN 13: 9798164804909
• Reliure: Paperback
• Nombre de pages: 134
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible