Why mastering C# still matters in the age of AI
AI is a powerful tool, but for critical systems, it cannot replace human judgment and oversight. Only when developers maintain genuine ownership of their code can they effectively manage technical debt and maintenance costs over the long term.
So yes, mastering programming languages and APIs matters more than ever.
However, this is not an exhaustive C# reference. Instead, this book focuses on the essential, advanced, and practical aspects of C# that require deep mastery. Unlike traditional programming guides, we emphasize “deep understanding” and encourage you to leverage AI tools to accelerate your development. In an era of AI-generated code, developers need sharper judgment regarding quality, security, and performance—and the skill to precisely direct AI to produce high-quality C# code.
Who this book is for
This book is for developers who already have a foundation in C# or another programming language and want to dive into modern C# syntax and practical details (C# 14 and .NET 10). We skip the basics to focus on the advanced details that AI often overlooks or misinterprets.
This book does NOT cover programming fundamentals, such as:
- How to call functions and pass parameters
- Basic loops and control flow
- Core object-oriented concepts (classes, inheritance, polymorphism)
(Even so, Chapter 1 begins with a concise “Hello World” example, allowing developers from other languages to quickly transition into the .NET ecosystem.)
Learning approach
To help you learn more effectively, this book uses the following approaches to guide your learning:
- Side-by-side comparisons: For easily confused concepts, we show both “not recommended” and “recommended” versions and explain why.
- Visual aids: Diagrams are used where helpful to clarify complex ideas.
- Practice-oriented: Not just “how,” but also “why,” “when to use,” “when not to use,” and the potential performance impact.
- Ask AI: You’ll see prompts sprinkled throughout to encourage using AI as a learning aid.
- C# version notes: We mark which C# version introduced a feature to help you understand the language’s evolution.
- Sample code links: All sample code is published on GitHub, and the book includes links where appropriate.
Chapters
- Preface
- Chapter 1: Modern environment and fundamentals (Read now for free)
- Chapter 2: Declarations and syntactic sugar
- Chapter 3: Null safety
- Chapter 4: Immutable design
- Chapter 5: Error handling and resource management
- Chapter 6: Pattern matching
- Chapter 7: Generics
- Chapter 8: Delegates and events
- Chapter 9: LINQ and functional programming
- Chapter 10: Extension methods
- Chapter 11: Asynchronous programming
- Chapter 12: High-performance memory operations
- Afterword
Free Preview: Chapter 1 - Modern environment and fundamentals
Tools used in this book
To follow along with the hands-on exercises, you’ll need:
- .NET 10 SDK or later
- An IDE or editor: Visual Studio 2026 (or VS Code, Rider, etc.)
For installation steps and tooling suggestions, see Section 1.2 of “Chapter 1: Modern environment and fundamentals.”
Sample code
The sample code for this book is hosted on GitHub:
https://github.com/huanlin/csharp-book-support
Preface
In an era where AI tools are evolving at a breakneck pace, writing code by feel using natural language—a practice often called vibe coding—has become increasingly common. This begs the question: do we still need to learn programming languages?
It is a question I often ask myself.
Vibe coding offers undeniable benefits: it boosts productivity, allows for early testing of product ideas, and enables rapid iteration. However, it also comes with risks: it may be less rigorous, it can encourage lax security habits, and it can create the illusion of rapid progress. When a product is built at this speed, the codebase keeps growing in size and complexity over time, while the team may not truly understand—or take ownership of—the code that AI tools generate. The end result can be a fragile product that’s hard to maintain.
This is why I believe that learning a programming language remains essential. It does not necessarily mean you must write every line of code yourself. At a minimum, it means possessing the ability to read and review AI-generated code—ensuring you truly own the application you build alongside AI. Given the current state of technology, AI still makes mistakes. For mission-critical projects or core system components, human review remains the ultimate quality gate.
Take the writing process of this book as an example. I used AI tools for collaboration and proofreading, aiming to polish the manuscript, reduce errors, and accelerate publication. While AI was incredibly helpful, it was far from perfect. Frequently, while reviewing AI-edited sections, I found that correct passages had been altered into incorrect ones. I also had to explicitly enforce rules, such as: “C# 14 was officially released in late 2025—stop labeling related syntax as a preview feature.” Even worse, ghost paragraphs—entire blocks of unrelated text—would occasionally appear out of nowhere.
In short, AI is a powerful tool, but for many critical systems today, it cannot fully replace human judgment and oversight. Only when developers maintain genuine ownership of their code can they effectively manage technical debt and maintenance costs in the long run. That is why I believe this book still holds value—not only to help readers sharpen their technical skills, but also as a testament to my own commitment to continuous growth.
Keep learning. Invest in yourself.
Michael Tsai (February 2026)
Note: The term “vibe coding” originates from a social media post by Andrej Karpathy in February 2025. Karpathy, a renowned AI researcher who served as Tesla’s Director of AI and is a co-founder of OpenAI, described a workflow where he relies entirely on LLMs (large language models). In this workflow, he describes requirements in natural language, rarely inspects the generated code closely, and simply feeds any error messages back to the AI to fix—a process guided entirely by “vibes.”
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