Books

Most people use AI. Few understand how far they can take it. AI Levels gives you a practical roadmap from prompting and everyday AI use to workflows, agents, specialized systems, and AI building—one skill at a time.

La inteligencia artificial está cambiando las reglas. AI Levels te lleva, paso a paso, de usuario de IA a creador de soluciones inteligentes: aprende, crea, automatiza y construye con IA.

Meta Muse changes the way you work with AI. This practical guide shows you how to write better prompts, build reliable workflows, automate everyday tasks and avoid common mistakes. Whether you're new to agentic AI or already putting it to work, you'll learn how to get more done with less friction and more confidence.

What does it take to turn an AI agent from a clever demo into something you can trust in production? This hands-on guide uses DeepSeek Harness to show how to build reliable, secure and observable agents, from a simple script to a production-ready service with budgets, tracing, evals and multi-tenant support.

Get more from Gemini 4 Argon with practical prompting techniques that work on real-world tasks. This guide covers coding, research, legal and financial work, long-horizon workflows, optimization and prompt evaluation, with clear examples and strategies for getting reliable results from one of the most capable AI models available.

A Comprehensive Engineering Guide to Autonomous Agent Architectures, Multi-Agent Systems, Memory, Tool Execution, Reliability, Observability, and Production DeploymentAutonomous AI agents represent a fundamental shift from conventional conversational applications toward software systems capable of executing multi-step tasks, interacting with external tools, maintaining persistent state, coordinating specialized components, and adapting their behavior to changing conditions. Building such systems requires considerably more than connecting a language model to a prompt. It demands a disciplined approach to execution control, memory architecture, workflow orchestration, security, evaluation, and production infrastructure.Mastering AI Agents: Hands-On Production Code is a practical, implementation-focused engineering reference to designing, building, and deploying autonomous AI agent systems. Across 38 chapters, it progresses from low-level LLM runtime primitives and a zero-dependency Python agent loop to cognitive architectures, persistent memory, stateful workflows, multi-agent coordination, secure tool execution, production observability, and enterprise deployment.

Get more from Claude Sonnet 5.5 with practical prompting techniques that actually work. This guide explores instruction design, effort control, tool use, structured outputs and agentic workflows, with clear distinctions between documented behavior and practical experience. Built for developers, prompt engineers and advanced users.

AI can write code fast, but getting reliable software still starts with clear thinking. This book shows how to turn ideas into precise specifications, then use AI assistants and autonomous agents to build, test and maintain real-world software. Follow a complete project from business problem to production and learn a practical approach to AI-assisted development.

Run Jev-style decision models on your own hardware with Ollaya. Learn how these fast, structured models differ from LLMs, then build real applications with typed outputs, Python, JavaScript and MCP. From first setup to production, this practical guide shows you how to make AI faster, cheaper and more private.

What happens when AI moves beyond answering questions and begins to pursue goals?Agentic AI: The Rise of Autonomous, Goal-Driven Intelligence explores the emerging world of intelligent systems that can perceive, reason, plan, learn, collaborate, and act within defined environments.From the foundations of autonomous agents and multi-agent systems to robotics, finance, logistics, security, ethics, and future research, this book provides a structured journey through the rapidly evolving landscape of Agentic AI.Discover how goal-driven intelligence works, how autonomous agents make decisions, how multiple agents collaborate, and why safety, trust, accountability, and human oversight are essential to the future of autonomous systems.Understand the agents. Explore the architectures. Examine the applications. Think about the future.

Construye tu primer agente con Python o TypeScript y aprende a desarrollarlo con especificaciones, pruebas y límites claros.

Go beyond basic prompting and learn how to get reliable, high-quality results from Claude Opus 5.5. This practical guide shows you how to structure instructions, manage context, break down complex work and verify outputs across coding, research, analysis, writing and automation.

GPT-6 Astra changes the way prompting works. This practical guide explains what makes it different, why old techniques can fail and how to write prompts that deliver reliable results. Learn how to build, refine and troubleshoot prompts while finding the right balance between control and autonomy.

Learn how production coding agents are really built, by reading the actual source code of Pi --- the open-source agent runtime.From the stateless agent loop to tool calling, sessions, extensions, and sandboxing, every concept is grounded in codes and UML diagrams.

Spring AI gives you one API for chat models, embeddings, vector stores and tools, and swaps the provider with a single property. This book teaches it by building: thirteen chapters, seventeen complete Spring Boot projects, and every program run on a free local model and on a paid cloud model before a word was written about it. Start chapter 1 with no account, no API key and no credit card.