Software Engineering

Make ChatGPT, Perplexity, Claude and Google AI cite the sites you build. A code-first AEO/GEO guide for developers and agencies — with a production-tested Next.js boilerplate.

Before containers, service meshes, and modern security platforms, qmail showed how much could be achieved with Unix processes, file permissions, queues, and discipline.

Software and infrastructure only create value when they pull in the same direction as the business. This book shows IT leaders how to get there: from shaping IT strategy and the architecture roadmap to the daily discipline of IT and architecture governance, all built on a pattern-based approach that adapts to your organization rather than forcing it into a template.Grounded in established frameworks such as TOGAF, COBIT, and ITIL, it pairs solid fundamentals with numerous real-world examples — and gives growing weight to compliance and IT security, now central concerns of any IT management agenda.This English edition is based on the German standard work on the subject, fully revised in its 4th edition (late 2024). It is current with TOGAF 10 and reflects recent developments in business-oriented enterprise architecture — including the open-source tool EDGY and patterns for digital strategy — alongside the latest trends in IT risk management and cybersecurity architecture.

Lo que no te cuentan sobre construir el software que mueve un e-commerce en LATAM: facturación electrónica ante el SII, concurrencia con plata de por medio, marketplaces con sus gotchas no documentadas y multi-moneda sin descuadres de un peso. No es teoría ni un "hola mundo": son las decisiones, los bugs que costaron dinero y los patrones que vienen de operar un ERP multi-tenant real en producción.

Coder ne suffit plus. N'importe quel LLM peut générer du code. Pour vingt dollars par mois.Ce qui change tout, c'est d'avoir une **méthode**. Sans méthode, l'IA te produit du code.Avec une méthode, elle te produit le logiciel dont tu as besoin. --- Le vibe coding a un problème Les deux premières semaines sont magiques. Chaque session produit duvrai code. Le projet grandit vite. Troisième semaine : tu corriges un module, quelque chose casse ailleurs.Quatrième semaine : l'agent ne se souvient plus des décisions prises.Cinquième semaine : ce qui prenait une heure en prend maintenant trois. Ce n'est pas un bug. C'est l'absence d'artefact de référence partagé. --- La solution : la spec comme artefact primaire **Spec-Driven Development (SDD)** inverse l'ordre habituel. Le code ne sert plus de source de vérité. La spec l'est.Le code implémente la spec. Les tests vérifient la spec.Et quand quelque chose dérape, tu mets d'abord à jour la spec. Un `.md`. Versionné avec git. Toujours à jour. C'est tout. --- Ce que tu vas apprendre - Pourquoi le vibe coding se dégrade et les 3 symptômes universels- Ce qu'est réellement le SDD (et ce qu'il n'est pas)- Les 7 phases du développement sérieux avec l'IA- Comment écrire un PRD en ~500 mots qui guide tout le reste- Comment transformer un PRD en issues GitHub actionnables- La boucle d'exécution : spec → agent → révision → itération- Les outils : GitHub SpecKit, OpenSpec, et les flux agnostiques- Les antipatterns les plus coûteux et comment les éviter- SDD en équipe, en greenfield et en brownfield- 3 cas complets : webhook, notifications, API publique --- Ce livre est fait pour toi si… - Tu utilises déjà l'IA pour coder mais les projets deviennent ingérables- Tu veux livrer plus vite sans perdre le contrôle de l'architecture- Tu travailles seul ou en équipe et tu cherches un cadre reproductible- Tu veux comprendre la méthode, pas juste copier des prompts

Go from an empty cluster to a self-deploying GitOps pipeline, doing every step yourself: Applications, sync policy, hooks, RBAC, Helm, ApplicationSets, and a setup that ships every branch on push. You finish with a pipeline you can explain line by line, not a demo you watched run.

Go from monolithic frontend pain to a fully deployed micro frontend architecture. A hands-on, production-focused guide to Webpack 5 Module Federation, ending with a complete multi-team app you build and ship yourself.

Deliver What Matters, When It Matters is a practical guide to delivery optimization for teams working in complex environments. Through real-world stories and actionable tools, it helps coaches, product managers, and delivery leaders close the gap between effort and impact.

Why learn one programming language when you can understand three at once? This book introduces the foundations of programming through a powerful side-by-side comparison of Python, Java, and C#, enabling readers to build strong conceptual understanding, transferable coding skills, and a solid pathway toward modern software engineering.

Build real AI products with TypeScript. Learn LLMs, RAG, Agents, MCP, and production AI engineering from a frontend developer's perspective.

A leader at a company opens Slack one morning. The brief their virtual employee wrote looks normal: same headers, same prose voice, same cadence as every other brief that week. The last line ends mid-sentence. The API returned `stop_reason: "max_tokens"`. The system shipped it anyway. No exception. No log line. No retry. That bug doesn't look like the normal kind. This book is about why, and what to build instead.

You are not losing velocity because your engineers are slow. You are losing velocity because every line of untested code is a landmine your team laid for itself — and sooner or later, someone steps on it. This is the book that explains why. No syntax. No tutorials. Just the argument, the evidence, and the standard your team should already be held to. A 30-minute read that changes how you lead software quality forever.

A typed, signed-deliverable playbook for the enterprise-scale Oracle 19c → Azure migration. Across fifteen chapters, thirteen signed JSON deliverables chain end-to-end from Migration Assessment Bundle to Decommissioning Readiness Report. Defensible at a code review. Sign-off-ready for a director.

This book introduces screenshot testing (also called visual or snapshot testing): an automated approach that records a reference image of the expected design, then compares each test run against it to detect visual changes. It’s a natural complement to functional UI tests, which verify behavior but not appearance. The book focuses on the fundamental principles that apply to all frameworks. It works through the questions teams actually face: when to use screenshot tests and when not to, what to verify, which frameworks and tools fit your workflow, how to generate tests from preview functions in Jetpack Compose, how to integrate tests into a CI/CD pipeline, and how to optimize the whole process. By the end, you’ll be able to choose the framework that best suits your project and build a safety net that catches visual bugs before release. Every concept is demonstrated with a demo mood tracker application, with all code available online.

You adopted the agents. You kept the process. That is why it feels broken. AI agents do not need a better workflow. They need a methodology designed for them - one that starts before the first line of code and ends only when the system signals that something needs to change. ANSE is that methodology. Nine pillars. One unbroken loop. The next evolution of AI influenced development - Smarter not just Faster.