Day 2: Evolution in Code: The Core Concepts

Day 2: Evolution in Code: The Core Concepts

At their core, genetic algorithms are built on five foundational principles that closely resemble biological evolution: 1. Genes and Chromosomes In biology, genes are units of information, and chromosomes are structured collections of those genes. In GAs, a chromosome is a single candidate solution, typically represented as an array, list, or string. Each gene in the chromosome represents one aspect …

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Day 1: The Survival of the Fittest Code: Why Learn Genetic Algorithms in C#?

Day 1: The Survival of the Fittest Code: Why Learn Genetic Algorithms in C#?

What if you could write code that evolves? Not just code that runs, but code that iteratively improves its own solutions to complex problems without requiring you to handcraft every edge case. That’s the promise of genetic algorithms (GAs), an AI-inspired method rooted in Darwinian evolution, and it fits surprisingly well in the world of modern C# development.

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volve Your C# Code with AI: A 5+ Week Genetic Algorithms Bootcamp for Developers

Evolve Your C# Code with AI: A 5-Week Genetic Algorithms Bootcamp for Developers

What if your code could evolve like life itself—adapting, optimizing, and learning over time? Welcome to the AI-inspired world of Genetic Algorithms, where we blend evolution with code to solve complex problems cleverly.

Starting this week, I’m launching a 42-day blog series—a 4-week bootcamp—designed to teach C# and .NET developers how to build, run, and scale Genetic Algorithms. From foundational concepts to solving real-world optimization problems, this series is your guide to coding like Darwin meant it.

Using clean, testable C# code, we’ll simulate survival of the fittest with fitness functions, crossover operations, mutations, and elite selection. This isn’t theoretical fluff—it’s practical, hands-on AI for your everyday dev life. Whether you’re optimizing routes, building smarter schedules, or just curious how to make your software think, this series is for you.

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Final Reflections: What Rust Taught Me as a C# Dev

Final Reflections: What Rust Taught Me as a C# Dev

Day 42, and here we are. Six weeks of learning Rust from the perspective of a C# developer. We covered the basics, wrestled with ownership, danced with traits and lifetimes, and shipped a working CLI app. Along the way, there were moments of frustration, lightbulb moments, and more than a few “why is this so hard” conversations with the compiler.

This final reflection is about stepping back and asking the big questions. What did Rust really teach me? What am I taking back to my C# projects? What might be next?

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Packaging and Releasing a Rust CLI Tool

Packaging and Releasing a Rust CLI Tool

Day 40, and today we are looking at how to package and release your Rust CLI app. You have written the code, added argument parsing, handled the logic, and even written tests. Now it is time to get that shiny CLI tool into the hands of others.

This process will feel familiar if you have worked with .NET global tools. Rust’s cargo makes it easy to build, release, and share your command-line apps.

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Parsing Arguments and Writing Logic

Parsing Arguments and Writing Logic in Rust

We are up to Day 37, and today, we are continuing to build out our Rust CLI app. Last time, we set up a simple command-line tool using the clap crate. Now, it is time to dig a little deeper into parsing arguments, handling input validation, and structuring our logic cleanly.

If you are coming from the C# world, this is where you would probably set up your Program.cs to parse args, maybe use a library like CommandLineParser, and then branch out into your application logic. Rust gives you similar tools but with its own flavor.

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