Software Engineering

AI engineering is becoming one of the most valuable and in-demand areas of software development, and Python, LangChain, and LangGraph are core skills for building the systems behind it. Learn how to turn basic Python knowledge into production-grade backend and agentic AI applications—and move toward an engineering niche centered on building and controlling AI rather than competing with it.

Build modern Android applications with Kotlin and Jetpack using practical, real-world development techniques. Learn how professional Android developers structure projects, manage UI and state, and create scalable, production-ready apps.

Building an impressive AI agent demo is easy. Running one in production—reliably, at scale, with governance—is where most enterprises get stuck. Agentic Orchestration shows how BPMN-based process orchestration governs AI agents at scale, drawing on real deployments across banking, telecom, and healthcare. Reasoning without orchestration is expensive chaos. This book shows the way out.

An LLM is not an AI system.Systems Thinking for Agentic AI shows software engineers and architects how to design reliable AI applications with prompts, RAG, tools, memory, orchestration, guardrails, evaluation, observability, and runtime control.Move beyond chatbot demos and learn how to build production-ready agentic AI systems you can reason about, measure, debug, operate, and improve

Build disciplined AI-assisted development workflows from foundations to production. Visual explanations and practical examples cover agents, verification, security, delivery, and operations.

Learn C++ from core foundations to production systems engineering. Visual explanations and practical examples cover ownership, concurrency, security, performance, and operations.

This book aims to explain the concepts of Domain-driven Design in a way that it is easily applicable in practice. Each chapter contains a theoretical part which is explained from the point of view of practical applicability and then exercises with solutions based on a comprehensive, complex case study (real estate loans).

This book aims to explain the concepts of Domain-driven Design in a way that it is easily applicable in practice. Each chapter contains a theoretical part which is explained from the point of view of practical applicability and then exercises with solutions based on a comprehensive, complex case study (real estate loans).

Once the five essential hooks are in place, the incidents that keep happening are the guards themselves failing, silently. Nine chapters collect the hooks (Git, credentials, token spikes, autonomous operation, multi-agent work), a chapter on hooks that do not fire, eight dated incidents from the author's own unattended operation, and a 50-point audit you can run against your own setup.

Python 3 Combat Guide is a practical guide, full of actual experience and common sense, to avoid errors and to develop Python 3 Software Projects and System Administration programs.Targeted to SDM, Team Manager and Developers, defines practical strategies and tricks, and teach the basis of Unit Testing in pytest.You'll learn OOP easily.

Explore the power of Rust with "Rust Projects: Write an Interpreter". This hands-on guide takes you through building an implementation of the programming language Lox, invented by Robert Nystrom. The book will follow Robert Nystrom's book and the CodeCrafters challenge "Build your own Interpreter", and at the same time will help you to understand strengths and weaknesses of Rust. Whether you're new to Rust or looking to deepen your understanding, this project-based journey offers practical, real-world insights into modern coding. The book contains 40% discount code for CodeCrafters.io!

Learn how large language models work instead of relying on black-box APIs. Building Large Language Models from Scratch takes you through training a Transformer model in PyTorch, from raw text to a working inference API, covering tokenization, attention, distributed training, and alignment along the way.

What if you could build software without manually writing every line of code? Artificial Intelligence is transforming the way software is designed, developed, tested, and deployed.But becoming an AI-powered software engineer isn't simply about asking an AI to write code.It's about learning how to think, design, build, test, verify, and improve software with AI as your engineering partner.The AI-Powered Software Engineer takes you on a practical journey from traditional programming to AI-assisted development and modern AI engineering.Learn how to use AI to:Design software. Generate and understand code. Debug complex problems. Build AI-powered applications. Automate workflows. Test and secure software. Deploy real products. Build AI-powered SaaS businesses.You don't need to become the fastest programmer in the room.You need to become the person who can turn an idea into a working, reliable, valuable system.Write less code. Think more. Build faster. Engineer smarter.The future of software engineering isn't humans versus AI.It's humans building with AI.

Close the gap between "AI that generates code" and "AI-assisted development for production software" with this complete, proven playbook including the six-phase arc from audit to production.

A roadmap you can run. What is planned for the Nasdanika SDK, with working modules, tests and model sketches built on the released runtime, so that you can try an idea today and say what is wrong with it while it is still cheap to change.