Books

AI can speed up learning and coding — but only if you stay in control. This book shows new developers how to use GPT-6, Claude, and Cursor effectively: how to ask clear questions, supply useful context, review generated code, test edge cases, and avoid common mistakes such as invented APIs, insecure suggestions, and overconfident explanations. You will build practical habits for explanations, small features, tests, debugging, and documentation — while protecting private data and remaining responsible for the final result. Ideal for students, self-learners, and early-career developers who want to learn with AI, not instead of learning.

The Future of Software Engineering Has Arrived.AI can now write code, generate tests, analyze requirements, explain systems, assist with debugging, and automate increasingly complex engineering tasks.But building great software has never been just about writing code.How do you design the right architecture?How do you build systems that remain secure and reliable at scale?How do you integrate AI without sacrificing quality, privacy, or control?How do you use AI to make engineers more effective without replacing engineering judgment?Engineering Software Systems in the AI Era explores these questions and provides a practical framework for designing, building, testing, securing, deploying, operating, and evolving modern software systems.Inside, you will explore:Modern software architecture and system designCloud-native and scalable systemsData architecture and intelligent data systemsAI engineering and AI-native applicationsCybersecurity and privacy by designSoftware quality and reliabilityDevOps, DevSecOps, and continuous deliveryObservability and production engineeringAI-augmented software developmentAI agents and intelligent engineering workflowsPlatform engineeringTechnical debt and engineering strategyAI governance and risk managementTechnical leadership in the AI eraThe future of software engineeringThe central message is simple:AI may make software development faster. Engineering makes software better.Learn how to combine the power of artificial intelligence with the discipline of software engineering to build systems that are secure, scalable, reliable, intelligent, maintainable, and ready for the future.

ספר הדרכה מעשי מלא בעצות מהשטח שיעזור לך לכתוב קוד טוב יותר, לאמץ הרגלי פיתוח יעילים, ולבנות תוכנה מעולה.

There has been a lot of change in API-land since the first edition, so let's stop building APIs like it's 2013.

Explore the power of Rust with "Rust Projects: Write a Redis Clone". This hands-on guide takes you through building a Redis-inspired database from the ground up, introducing key programming concepts like TCP connections, the RESP protocol, and concurrency. Following the CodeCrafters challenge, this book gradually builds your skills, making complex topics accessible. Whether you're new to Rust or looking to deepen your understanding, this project-based journey offers practical, real-world insights into modern systems programming. The book contains 40% discount code for CodeCrafters.io!

This book is designed for individuals who have already learned the basics of web security. It provides a systematic guide to acquiring the "practical bug hunting skills" necessary to achieve your first valid report (First Blood), earn your first bounty, and consistently deliver results in real-world bug bounty programs.

A how-to field guide on building leak-free abstractions and algebraically designing real-world applications.

15 Years of Gamification Design Experience and Research in one book. Companies pay thousands of dollars to learn Yu-kai's Octalysis Framework. Get it all here.

Continuous Delivery and DevOps experience reports from the wild

The tool made you fast before it made you good. The Sovereign Apprentice is the regime that rebuilds what fluency skipped — judgment, verification, and a craft that's actually yours. Companion to The Sovereign Engineer.

Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident. This book shows you how to build a scanner that catches these issues automatically. You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments. **What you'll build:** - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions **Who this is for:** - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.

Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident. This book shows you how to build a scanner that catches these issues automatically. You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments. **What you'll build:** - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions **Who this is for:** - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.

Threat modeling is broken. It takes days, costs thousands, and most teams skip it entirely. What if your AI coding assistant could do it for you — systematically, consistently, and in minutes? This book shows you how to build an MCP server that makes it happen. You'll create 80+ structured tools that guide any AI assistant through a rigorous 9-phase STRIDE threat modeling workflow. Not vague prompts that produce unstructured text — real, typed, validated tools that build up a complete threat model piece by piece: business context, architecture, threat actors, trust boundaries, data flows, STRIDE-based threats, mitigations, and a final JSON export compatible with AWS Threat Composer. **What you'll build:** - A full MCP server with FastMCP (stdio + SSE transport) - Pydantic v2 data models for type-safe threat modeling - Case-insensitive enum validation (because AI isn't always consistent) - 11 tool modules covering every phase of STRIDE analysis - Customizable organization security guidelines loaded from `.md` files - Docker deployment for team-wide access - Compliance gap analysis that validates against mandatory controls - A complete workflow orchestrator with progress tracking **What makes this different:** The server doesn't call any LLM itself. It provides the structure and tools — your AI assistant (Claude, Kiro, Cursor, Copilot) provides the intelligence. This means it works with any model, any provider, forever. No API keys, no token costs for the server itself. **Who this is for:** - Security engineers who want to automate repetitive threat modeling - Python developers building MCP servers for any domain - DevSecOps teams embedding security into AI-assisted workflows - Architects who need consistent, auditable threat models - Anyone curious about how MCP tools work under the hood **By the end of this book**, you'll have a production-ready MCP server, a deep understanding of how AI tools are structured, and transferable patterns for building MCP servers in any domain — not just security.

Guarantees are a simple and powerful tool to help you write good code. They test critical assumptions and make them explicit and obvious. They help you, and anyone reading your code, make guarantees about the code.

Holistic testing is a comprehensive term to encompass testing throughout the development cycle from the start of an idea, through to customer interaction with a delivered feature. All members of a delivery team think about testing and quality from the beginning and throughout the cycle.  This book is about the Holistic Testing Model and how to apply it to develop a quality and testing strategy for the whole team. If you care about quality – no matter what your specialty or role in your organization is – we think you’ll find it helpful. UI/UX designers, product owners, programmers, testers, database experts, business analysts, site reliability and platform engineers, and more – this model will guide you as you collaborate to continually improve your process and product.