Vibe Engineering

Software development is changing fast, and Claude Code is at the center of that shift. Learn how to work effectively with AI agents to write code, automate workflows, and build larger projects with confidence. From setup and prompt design to real-world engineering practices, this book provides a practical guide to modern software development in 2026.

A hands-on guide to downloading, running, serving, and maintaining open-weight LLMs on your own machine (492 manuscript pages).

Learn Claude Code by building real projects. This hands-on companion turns the Claude Code Masterclass workshop into a practical self-paced guide for planning, coding, testing, reviewing, refactoring, and shipping software with AI.

El desarrollo de software está cambiando rápidamente, y Claude Code lidera esa transformación. Aprende a trabajar con agentes de IA para escribir código, automatizar tareas y crear proyectos más grandes con confianza. Este libro ofrece una guía práctica para el desarrollo moderno de software en 2026.

Die Softwareentwicklung wandelt sich rasant, und Claude Code steht im Zentrum dieses Wandels. „Mastering Claude Code“ zeigt, wie Entwickler mit KI-Agenten Code schreiben, Arbeitsabläufe automatisieren und auch komplexe Projekte effizient umsetzen. Praxisnah vermittelt das Buch Einrichtung, Prompt-Design und bewährte Engineering-Praktiken für moderne Softwareentwicklung im Jahr 2026.

A practical guide to operating a fleet of AI coding agents through routing, memory, skills, MCP, guardrails, and a persistent control plane (286 manuscript pages).

Lo sviluppo software sta cambiando rapidamente e Claude Code è al centro di questa trasformazione. Mastering Claude Code insegna agli sviluppatori come usare gli agenti di intelligenza artificiale per scrivere codice, automatizzare i flussi di lavoro e sviluppare software in modo più efficace. Una guida pratica per comprendere come nasce il software moderno nel 2026.

Master Codex CLI from your first prompt to production-ready AI workflows. Learn how to automate coding, streamline development, and use OpenAI's terminal-native coding agent with confidence.

Mastering Claude Code montre comment collaborer avec des agents d’IA pour écrire du code, automatiser des flux de travail et réaliser des projets d’envergure. De la configuration aux bonnes pratiques d’ingénierie logicielle, ce guide pratique explique comment les logiciels modernes sont conçus en 2026.

OpenClaw in Production shows you how to run OpenClaw as a secure, reliable service that can handle real workloads. Whether you're deploying on a Raspberry Pi or operating a Kubernetes cluster, you'll learn the practical skills needed to keep your agents stable, secure, and easy to manage as they grow from a single instance to production at scale.

MCP is the protocol powering the next generation of AI agents, and this is the only book that teaches you all of it. From Python fundamentals to low-level SSE transport, go from zero to production-ready MCP developer.

Build and operate production AI platforms on Kubernetes. Learn to manage NVIDIA GPUs, serve and optimize LLMs with vLLM, run training and batch workloads, and design secure, observable, multi-tenant infrastructure for AI at scale.

Mastering Deep Learning with PyTorch: From Fundamentals to Real-World Projects This first edition delivers a complete end-to-end learning pathway for mastering modern deep learning using PyTorch. Major Topics Covered • Deep Learning Fundamentals• Artificial Neural Networks• PyTorch Framework and Tensor Operations• Automatic Differentiation (Autograd)• Feedforward Neural Networks• Convolutional Neural Networks (CNNs)• Recurrent Neural Networks (RNNs)• Long Short-Term Memory Networks (LSTMs)• Attention Mechanisms• Transformer Architectures• Hugging Face Ecosystem• Generative Adversarial Networks (GANs)• Computer Vision Applications• Natural Language Processing Applications• Model Evaluation and Optimization• Hyperparameter Tuning• Explainable Artificial Intelligence (XAI)• Ethical AI and Bias Mitigation• Model Deployment and Production Pipelines Practical Implementations Included • Image Classification Systems• Object Detection Models• Image Segmentation Applications• Text Classification Systems• Sentiment Analysis Models• Language Translation Pipelines• Transformer-Based NLP Applications• GAN-Based Image Generation Capstone Projects Project 1: Pneumonia Detection using CNNProject 2: Sentiment Analysis using LSTMProject 3: Image Colorization using GANProject 4: Real-Time Object Detection SystemProject 5: Transformer-Based Intelligent Chatbot Industry Tools and Technologies • PyTorch• TorchVision• Hugging Face Transformers• TensorBoard• Flask• ONNX• Docker Concepts• AWS Deployment Basics• Google Cloud Deployment Concepts Intended Audience • Undergraduate Students• Postgraduate Students• Data Scientists• Machine Learning Engineers• AI Researchers• Software Developers• Academic Professionals• Industry Practitioners Learning Outcomes Upon completion of this book, readers will be able to:• Design and train neural network architectures.• Build computer vision applications using CNNs.• Develop NLP solutions using RNNs, LSTMs, and Transformers.• Implement generative AI systems using GANs.• Evaluate and optimize deep learning models.• Deploy PyTorch models into production environments.• Understand ethical considerations in AI development.• Create portfolio-ready deep learning projects.This release establishes a strong foundation for academic learning, industrial applications, and advanced research in modern deep learning.

AI can write code faster than you can read it—so why do projects still derail? The answer is the spec. This book teaches Spec-Driven Development hands-on, building a complete app one loop at a time with Spec Kit. Stop prompting and praying. Start shipping software AI actually gets right.

Your AI-generated code passes 18,000 tests and reports healthy — while entire data pipelines silently produce nothing. Silent Wiring names the failure mode nobody's tooling catches, and shows you how to find it before your users do.