Books

Software is more than code. It is a living system shaped by people, feedback and constant change. This book helps you think beyond features and fixes to understand why systems behave the way they do. Learn practical ideas that lead to better architecture, smarter decisions and software built to last.

The system design book for the AI era. Five complete end-to-end designs (chat service, RAG, content moderation, coding assistant, multi-modal platform), a structured six-step framework, and chapters on cost optimization, reliability, and observability — all with realistic capacity estimates and production-grade code.

Ein Coding-Agent liefert in Sekunden makellosen Code, mittendrin eine Funktion, die es nie gab: Halluzinations-Lasagne. Claude Shannons verrauschter Kanal von 1948 erklärt, warum plausible Ausgaben nicht verlässlich sind, und wie ein geschärfter Sender, ein beherrschter Kanal und ein prüfender Empfänger daraus verlässliche Software machen.

Master Kong API Gateway with a practical guide that takes you from core architecture to advanced AI-powered API management. Learn to build secure, scalable platforms with production-ready examples, explore Kubernetes, decK and Terraform workflows, and discover how Kong AI Gateway enables intelligent LLM routing, semantic caching, guardrails and cost optimization across modern AI applications.

Learn how to build a fast, private AI search engine that indexes and retrieves documents using modern open-source tools. From a simple prototype to a production-ready system, you will create intelligent local search that runs entirely on your own hardware.

Scaling isn't just about handling more traffic. The Scalable SaaS Architecture Handbook shows you how to design SaaS systems that remain reliable, maintainable, and efficient as they grow, using proven patterns and real-world lessons.

Ship the NEXUS-1 backend for real: a genuine SQL Server on every test run, a dispatcher proven under a killed process, structured logs with a correlation id, and a CI gate that will not package a red build. Two hundred tests, one Dockerfile, one honest boundary.

From Flow to Proof turns distributed-system promises into explicit models, properties, counterexamples, and evidence. Explore state machines, contracts, temporal logic, concurrency, ownership, refinement, and honest proof boundaries—with companion artifacts at github.com/gregory82gr/Nexus-1-phase-0.

The CCAR-P exam tests judgment, not trivia. This scenario-based guide covers all seven domains, from solution design and RAG to governance and stakeholder communication, with 62 sketchnote figures, chapter quizzes, a distractor appendix that explains every wrong answer, and a full 63-question practice exam.

The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.

Give the tested core a database and a public API — without letting either touch its rules. Build NEXUS-1's Infrastructure and API layers in .NET: EF Core, repositories, the outbox, RFC 7807, JWT. 654 tables, one seam that stays signed — every rule proven by watching it fail.

Build microservices the way architects do—not by splitting code, but by discovering true boundaries. Using the NEXUS-1 digital twin, this book explores DDD, APIs, messaging, eventual consistency, sagas, resilience, and migration, showing when distributed systems are worth their cost.

Advanced DDD before microservices: From Context to Flow shows how NEXUS-1 moves from bounded contexts to domain events, integration events, outbox, sagas, anti-corruption layers, auditability, and eventual consistency.

Mastering Elasticsearch is a hands-on guide to building fast, scalable search and analytics systems. It covers core concepts, index design, Query DSL, relevance tuning, vector search, and production operations with practical examples in Python, Java, JavaScript, and REST.

You shipped the demo. The model worked. Now production is coming, and the demo is not a system. An agentic system is a distributed-systems engineering problem — the reliability lives in the shell, not the model.