Artificial Intelligence

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As traditional institutions struggle to keep pace with technology, sovereignty is shifting from legal parchment to digital protocols. Explore how "Algorithmic Sovereignty" is creating a new global order where code acts as the ultimate arbiter of power, property, and personhood.

We are transitioning from an economy of human clicks to a world governed by machine-to-machine APIs. This monograph provides the essential roadmap for surviving the "Agent Economy," where autonomous AI agents negotiate and transact in a market that no longer waits for human permission.

AI doesn’t fail because it isn’t smart. It fails because it isn’t usable. This book defines the foundations of designing AI agents people trust, understand, and rely on.

Master the art of AI interaction with 22 proven prompting techniques, real code examples, and production-tested strategies. From the creator of GitHub's most-starred prompt engineering repository (7,100+ stars).

Stop guessing which machine learning algorithm to use. This book provides clear mathematical explanations, decision frameworks, and real-world examples to help you select, implement, and evaluate models correctly from data to deployment.

Architecture. Teams. Business. Aligned. Finally, a guide that connects the dots. From Team Topologies to Flexible Project Management, learn how to build systems that align with your business goals instead of fighting against them. Stop estimating and start engineering your path to confidence.

Digitale Transformation war das Hype-Thema vor KI. Es gibt allerdings einen nicht geringen Anteil an Fach- und Führungskräften, deren Wissen darüber weiter ausbaufähig ist. Dieses Buch ist eine Einführung für alle diejenigen, die keine "digitalen Pioniere" sind, sondern wissen wollen, was aus dem Thema Digitalisierung auf sie zukommen kann und aus dem Thema KI zusätzlich auf sie zukommen wird.

Bridge the gap between high-level C# and raw hardware execution. Eliminate GC pauses with zero-allocation Span<T> and SIMD vectorization. Learn to build blazing-fast tokenizers and local LLM inference engines. Stop waiting for the runtime—start engineering for extreme AI performance.

Break free from expensive cloud APIs to build private, offline-capable AI systems. Harness ONNX Runtime and LlamaSharp to run LLMs and Vision models natively in C#. Master hardware acceleration and local RAG pipelines for lightning-fast, zero-latency performance. Stop paying per token—start engineering high-performance intelligence directly on the Edge.

Evolve from building static applications to architecting sophisticated cognitive systems. Master the Microsoft Semantic Kernel to bridge deterministic C# code with LLM reasoning. Build autonomous agents that plan, execute, and adapt using advanced enterprise patterns. Stop writing scripts and start engineering the future of intelligent .NET software.

Stop scripting and start engineering the next generation of cloud-native AI. Master C# and Kubernetes to build resilient, distributed agent swarms at scale. Bridge the gap between experimental logic and high-performance, production-grade systems. Architect the future of intelligence—from event-driven scaling to secure service meshes.

Научитесь думать как ИИ через работающую LLM, которую вы построите сами. Проверенное в бою системное мышление из Cray Research, применённое к современному ИИ. Совершайте то, что другие считают невозможным.

Master high-performance C# to build the next generation of AI-powered applications. Go beyond basic async/await to architect non-blocking, massively concurrent AI pipelines. Implement real-time LLM streaming with IAsyncEnumerable<T> and manage backpressure gracefully. Leverage Channels and parallel processing to build a resilient RAG ingestion engine.

Digital Transformation in the Era of AI reframes transformation as a continuous capability, not a one-time program. Drawing on real enterprise experience, this book shows how organisations can evolve their architectures, operating models, and leadership practices to harness AI responsibly and at scale, without breaking what already works.