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C# & AI Masterclass: Asynchronous AI Pipelines. Async/Await, Parallelism, and Streaming LLM Responses.

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.

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About the Book

Master High-Performance C# to Build the Next Generation of AI-Powered Applications

The AI revolution is here, but is your C# code ready for it? Modern AI systems, powered by Large Language Models (LLMs), demand more than just functional code—they require high-throughput, low-latency, and massively concurrent architectures. A simple blocking API call or an unhandled race condition can bring a sophisticated AI pipeline to its knees. This book is your definitive guide to mastering the advanced asynchronous and parallel programming techniques required to build production-grade AI systems in .NET.

Moving far beyond basic async/await, this volume deconstructs the patterns and primitives that power scalable software. Through practical examples, deep architectural insights, and a comprehensive capstone project, you will learn how to architect resilient pipelines that can ingest, process, and stream data efficiently, all while maintaining a responsive user experience.

Inside, you will discover how to:

  • Architect Non-Blocking AI Pipelines: Master the `async/await` state machine and understand the critical difference between CPU-bound and I/O-bound work to eliminate performance bottlenecks.
  • Stream LLM Responses in Real-Time: Implement the "typewriter effect" using IAsyncEnumerable<T>, providing users with instant feedback from generative AI models.
  • Manage API Rate Limits and Backpressure: Use SemaphoreSlim and System.Threading.Channels to build resilient systems that gracefully handle API throttling and prevent memory exhaustion when your AI generates data faster than your UI can handle it.
  • Process Data in Parallel: Leverage Parallel.ForEachAsync and the Scatter-Gather pattern (Task.WhenAll) to concurrently process large batches of documents for embeddings, dramatically reducing ETL times for RAG systems.
  • Ensure Thread Safety: Protect your application from data corruption with locks, monitors, and concurrent collections, a critical skill for any multi-threaded AI application.
  • Write Deterministic Tests for Async Code: Learn how to mock non-deterministic AI behavior to create fast, reliable unit and integration tests for your asynchronous pipelines.
  • Build a Complete RAG Ingestion Engine: Apply all the concepts in a capstone project where you build a high-throughput ETL system from scratch—the foundational component for any modern semantic search or question-answering application.

This book is for intermediate to advanced C# developers and architects who are ready to move beyond theory and build the scalable, high-performance backend systems that the AI era demands. If you're tired of fighting with unresponsive applications, memory leaks, and flaky tests in your async code, this is the guide you've been waiting for.

Unlock the full potential of .NET and start building the next generation of intelligent, responsive, and resilient AI services today.

Check also the other books in this series

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Author

About the Author

Edgar Milvus

A veteran software engineer with 20 years of experience, I have dedicated my career to the art of automation. My philosophy is simple: programming should eliminate repetitive chores to unlock human creativity. This journey began early on with the development of custom code-generation tools and has evolved into a deep mastery of LLMs and their APIs. Today, I specialize in architecting AI-driven solutions that handle everything from complex coding and security tasks to advanced knowledge retrieval, transforming the way we interact with technology

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