Aquí está cómo puedes usar la IA para enseñarte a ser robusto: 15 proyectos para impresionar a los reclutadores de MAANG

¿Por qué tener un monitor cuando puedes tener cinco? Rust es el rey hoy - y AI puede ayudarte a aprenderlo Rust is acclaimed as the king of modern systems programming. Rust is acclaimed as the king of modern systems programming. It is not just challenging but also overpowering the long-standing dominance of C and C++. Lo consigue proporcionando: The raw performance of C++ Guaranteeing comprehensive memory safety Providing compile-time concurrency safety Avoiding the majority of hackers’ loopholes, especially memory issues Providing the best package and configuration manager today in cargo . El rendimiento crudo de C++ Garantizar la seguridad de la memoria Proporcionar seguridad de compilación-tiempo Evitar la mayoría de las fallas de los hackers, especialmente los problemas de memoria Proporcionar el mejor gestor de paquetes y configuración hoy en día en carga. La encuesta de desarrolladores de Stack Overflow ha coronado a Rust el lenguaje de programación "más amado" por ocho años consecutivos. La encuesta de desarrolladores de Stack Overflow ha coronado a Rust el lenguaje de programación "más amado" por ocho años consecutivos. Esta popularidad sin precedentes proviene del hecho de que los desarrolladores que superan su curva de aprendizaje inicial. Estos pocos afortunados encuentran las características y garantías de Rust ventajosas y productivas. Killer Features of Rust for Systems Programming Características de Rust para la Programación de Sistemas Rust ha tomado toda la industria de la programación de sistemas. Esta es la razón. Memory Safety without a Garbage Collector: Rust's compiler statically guarantees memory safety This eliminates entire categories of common bugs like: null pointer dereferences buffer overflows dangling pointers. // This code, which would cause a dangling pointer in C++, won't even compile in Rust. fn get_dangling_reference() -> &String { let s = String::from("hello"); &s // Error: `s` does not live long enough } Zero-Cost Abstractions: Rust le permite escribir código expresivo de alto nivel usando: Abstractions like: Iterators Closures async/await map/reduce patterns first-class functions: Sin incurrir en una sanción de rendimiento. // This high-level iterator... let numbers = vec![1, 2, 3, 4, 5]; let sum_of_squares: i32 = numbers.iter().map(|&x| x * x).sum(); // ...compiles down to machine code as efficient as a manual C-style loop. Fearless Concurrency: The same ownership and type system that guarantees memory safety: Prevents data races at compile time! This makes it significantly easier and safer to write concurrent, multi-threaded programs. use std::thread; fn main() { let mut data = vec![1, 2, 3]; // This attempt to use the same mutable data from two threads is a compile-time error. // Rust forces you to use safe concurrency primitives like Arc and Mutex. // thread::spawn(|| { data.push(4); }); // Error: closure may outlive current function // thread::spawn(|| { data.push(5); }); // Error } Modern Tooling with Cargo: Cargo is Rust's integrated build system and package manager It is praised for its simplicity and power Cargo handles: project creation dependency management building testing And much more with simple commands. # Create a new project cargo new my_awesome_project # Add a dependency by adding one line to Cargo.toml # [dependencies] # serde = "1.0" # Build and run cargo run Ep Curva de Aprendizaje The Infamous Ste El infame es y El principal obstáculo para los principiantes es el compilador de Rust. The compiler is famously strict because: It must statically prove the correctness of your program's memory management It must prevent any errors in concurrency at compile time. It uses advanced algebraic structures to guarantee error-free concurrency. El compilador es muy riguroso porque: Debe demostrar estatisticamente la corrección de la gestión de la memoria de su programa Debe evitar cualquier error en la concurrencia en el tiempo de compilación. Utiliza estructuras algebraicas avanzadas para garantizar concurrencia libre de errores. Esta rigidez significa que el código que podría ejecutarse (y más tarde caer) en otros idiomas ni siquiera compilará en Rust hasta que cumpla con las reglas de seguridad. The Borrow Checker and Ownership Rules La gestión de la memoria de Rust se rige por un conjunto de reglas que el compilador verifica en el tiempo de compilación. Este sistema se llama propiedad. Rule 1: Each value in Rust has a single owner. Regla 1: Cada valor en Rust tiene un único propietario. fn main() { // s is the owner of the String data "hello" allocated on the heap. let s = String::from("hello"); } Rule 2: There can only be one owner at a time. Regla 2: Sólo puede haber un propietario a la vez. When a value is assigned to another variable, ownership is . moved fn main() { let s1 = String::from("hello"); let s2 = s1; // Ownership of the String data is moved from s1 to s2. // The line below will cause a compile-time error because s1 is no longer a valid owner. // println!("s1 is: {}", s1); // Error: value borrowed here after move } Rule 3: When the owner goes out of scope, the value is dropped. Regla 3: Cuando el propietario sale de alcance, el valor se disminuye. Rust automatically calls a special drop function to free the memory. fn main() { { let s = String::from("I live only within these curly braces"); } // `s` goes out of scope here, and the memory is automatically freed. } Para acceder a los datos sin tomar propiedad, puede Y eso. En préstamo Esto se hace mediante la creación de una referencia. Immutable Borrows: Los préstamos inmutables: You can have multiple immutable references (&T) to a value simultaneously. Se trata de un acceso solo de lectura. fn main() { let s1 = String::from("hello"); let r1 = &s1; // Immutable borrow let r2 = &s1; // Another immutable borrow is fine println!("r1 = {}, r2 = {}", r1, r2); // This works perfectly. } Mutable Borrows: Sólo puede tener una referencia mutable (&mut T) a un valor en un rango específico. Esto impide (Google para saber más) data races fn main() { let mut s1 = String::from("hello"); let r1 = &mut s1; // One mutable borrow // let r2 = &mut s1; // Error: cannot borrow `s1` as mutable more than once at a time r1.push_str(", world!"); println!("{}", r1); } You cannot have a mutable borrow while immutable borrows exist. fn main() { let mut s = String::from("hello"); let r1 = &s; // immutable borrow let r2 = &mut s; // Error: cannot borrow `s` as mutable because it is also borrowed as immutable // println!("{}, {}", r1, r2); } El es la parte del compilador Rust que aplica todas estas reglas de propiedad y préstamo. borrow checker Los programadores Rust principiantes a menudo pasan una cantidad significativa de tiempo "luchando contra el control de préstamos". Beginner Rust programmers often spend a significant amount of time "fighting the borrow checker." Es la escalera de cada aprendiz. Pero con Gemini, las explicaciones están disponibles a través de Q&A simple en inglés. But with Gemini, explanations are available via simple English Q&A. Este proceso implica aprender a estructurar el código de una manera que satisfaga las garantías de seguridad de Rust. Esta lucha inicial, aunque frustrante, es lo que construye la comprensión fundamental necesaria para escribir código Rust seguro y eficiente. Es como tener un mentor riguroso que te obliga a construir buenos hábitos desde el primer día. Other Arcane Rules That Make Rust Difficult Lifetimes: de la vida: Lifetimes are the syntax Rust uses to tell the borrow checker how long references are valid. In many cases, the compiler can infer lifetimes, but sometimes, you must annotate them explicitly using an apostrophe syntax, like 'a. Lifetimes prevent dangling references, where a reference points to memory that has been deallocated. // We must explicitly tell the compiler that the returned reference (`&'a str`) // lives at least as long as the shortest-lived input reference (`'a`). fn longest (x: &'a str, y: &'a str) -> &'a str { if x.len() > y.len() { x } else { y } } Traits: Traits: A trait tells the Rust compiler about functionality a type must provide. It's similar to an interface in languages like Java or C#. It enables incredibly powerful polymorphism capabilities. // Define a trait `Summary` pub trait Summary { fn summarize(&self) -> String; } // Implement the trait for the `Tweet` struct pub struct Tweet { pub username: String, pub content: String, } impl Summary for Tweet { fn summarize(&self) -> String { format!("{}: {}", self.username, self.content) } } Generics: Los genéricos: Generics are abstract stand-ins for concrete types. They allow you to write flexible code that avoids duplication by operating on many different data types. // This function can take any type `T` that implements the `PartialOrd` and `Copy` traits. fn largest (list: &[T]) -> T { let mut largest = list[0]; for &item in list.iter() { if item > largest { largest = item; } } largest } Ahora podemos ver cómo entra AI en la imagen. Needed to set the context first! Now, we can see how AI comes into the picture. Needed to set the context first! How AI Can Act as a Highly Reliable Free Tutor Inicialmente no se requiere ingeniería avanzada. Sin embargo, dominar la ingeniería rápida es vital en el mundo de hoy. But we digress. Advanced prompt engineering is not initially required. Advanced prompt engineering is not initially required. However, mastering prompt engineering is vital in today’s world. But we digress. Para aprender Rust, puede hablar en lenguaje similar al inglés a la AI. For example: “Enseñame los conceptos básicos de Rust”. “Help me create a project in Rust.” “Help me install Rust in my Windows/Linux/Mac system.” “Write a program in Rust for …” “Please debug this Rust program (paste the program below).” le.” “Help me understand this with an examp “Explain this concept to me as if I were 10 years old.” “Explain the borrowing checker and ownership model to me as if I were a teenager.” “Explain this error message to me in simple terms and show me how to correct the code.“ 1. Enséñame los conceptos básicos de Rust. “Help me create a project in Rust.” “Help me install Rust in my Windows/Linux/Mac system.” “Write a program in Rust for …” “Please debug this Rust program (paste the program below).” “Ayúdame a entender este concepto de ‘Rust’ con un ejemplo”. “Explain this concept to me as if I were 10 years old.” “Explain the borrowing checker and ownership model to me as if I were a teenager.” “Explain this error message to me in simple terms and show me how to correct the code.“ It is so simple that children can do it and are doing it! An AI assistant like Google Gemini in Google AI Studio can act as a: Título Interactive Personalizados Adjustable Custmizable poderoso Gentle paciente Kind Y un tutor infinitamente energético para aprender los conceptos complejos de Rust. En lugar de simplemente leer la documentación: You can have a conversation with the AI. You can ask it to rephrase explanations or provide different examples. Until a concept clicks. Este es un cambio de juego para los desarrolladores que tuvieron que pasar por los libros de texto de 900 páginas. Un AI puede tomar un error de compilador intimidante y traducirlo al inglés común. Puede explicar por qué ocurrió el error y sugerir múltiples maneras de corregirlo. ¡Este es un superpoder para cualquiera que aprenda Rust en múltiples niveles! En lugar de simplemente leer la documentación: En lugar de simplemente leer la documentación: You can have a conversation with the AI. Puedes pedirle que redefine las explicaciones o proporcione ejemplos diferentes. Until a concept clicks. Usted puede tener una conversación con el AI. Puedes pedirle que redefine las explicaciones o proporcione ejemplos diferentes. Until a concept clicks. Este es un cambio de juego para los desarrolladores que tuvieron que pasar por los libros de texto de 900 páginas. This is a game-changer for developers who had to pore through 900-page textbooks. Un AI puede tomar un error de compilador intimidante y traducirlo al inglés común. An AI can take an intimidating compiler error and translate it into plain English. Puede explicar por qué ocurrió el error y sugerir múltiples maneras de corregirlo. Puede explicar por qué ocurrió el error y sugerir múltiples maneras de corregirlo. ¡Este es un superpoder para cualquiera que aprenda Rust en múltiples niveles! This is a superpower for anyone learning Rust on multiple levels! Puede utilizar el siguiente mapa de ruta para aprender Rust: https://roadmap.sh/rust?embedable=true You can use AI (LLMs) to understand every concept you do not understand. Every doubt, concept, and challenging process can be explained with Google AI Studio. Switch models to avoid exceeding rate limits (Gemini Flash or Flash-Lite instead of Gemini Pro). Usted puede usar otros modelos de LLM de IA si se ejecutan todos los límites de uso libre en Google AI Studio: Some of the best are: Claude: https://claude.ai/ ChatGPT: https://chatgpt.com/ Perplexity: https://www.perplexity.ai/ DeepSeek: https://chat.deepseek.com/ Grok: https://grok.com/ Every doubt, concept, and challenging process can be explained with Google AI Studio. Every doubt, concept, and challenging process can be explained with Google AI Studio. Google AI Studio. Switch models to avoid exceeding rate limits (Gemini Flash or Flash-Lite instead of Gemini Pro). Cambie de modelos para evitar exceder los límites de tasa (Gemini Flash o Flash-Lite en lugar de Gemini Pro). Usted puede usar otros modelos de LLM de IA si se ejecutan todos los límites de uso libre en Google AI Studio: Usted puede usar otros modelos de LLM de IA si se ejecutan todos los límites de uso libre en Google AI Studio: Some of the best are: Some of the best are: de Claude: de Claude: https://claude.ai/ https://claude.ai/ https://claude.ai/ ChatGPT: El ChatGPT: https://chatgpt.com/ https://chatgpt.com/ https://chatgpt.com/ Perplexity: Perplexity: https://www.perplexity.ai/ https://www.perplexity.ai/ https://www.perplexity.ai/ En profundidad: DeepSeek: https://chat.deepseek.com/ https://chat.deepseek.com/ https://chat.deepseek.com/ Grok: Grok: https://grok.com/ https://grok.com/ https://grok.com/ I placed them in order of my use, and with so many other (Mistral, Qwen, Kimi) generative AI models available for free: I placed them in order of my use, and with so many other (Mistral, Qwen, Kimi) generative AI models available for free: Usted no tiene que pagar por una suscripción para aprender Rust con AI. Usted no tiene que pagar por una suscripción para aprender Rust con AI. How. Awesome. Is. That! How. Awesome. Is. That! For Example // User pastes this code and the resulting error: fn main() { let mut v = vec![1, 2, 3]; let first = &v[0]; v.push(4); // Error: cannot borrow `v` as mutable... println!("The first element is: {}", first); } Y la explicación: "The error happens because you have an immutable reference `first` to an element inside the vector `v`. Then, you try to call `v.push(4)`, which is a mutable operation. Pulsar un elemento podría requerir que el vector realocara su memoria, lo que invalidaría la referencia "primera". To fix this, you should ensure the immutable reference `first` is no longer in use before you mutate the vector. For example, you could move the `println!` before the `push`." "The error happens because you have an immutable reference `first` to an element inside the vector `v`. Then, you try to call `v.push(4)`, which is a mutable operation. Pulsar un elemento podría requerir que el vector realocara su memoria, lo que invalidaría la referencia "primera". Para corregir esto, debe asegurarse de que la referencia inmutable "primero" ya no esté en uso antes de que mute el vector. For example, you could move the `println!` before the `push`." Screen Sharing This is why I highlighted Google AI Studio over other tools. This is why I highlighted Google AI Studio over other tools. Practically none of the other AI tools I mentioned have this feature as well-developed as Google Gemini as of the date of writing this article. Gemini's potential screen-sharing capability could be a lifesaver for Rust debugging, especially in production. A learner could share their VS Code window: Highlight a block of code rejected by the borrow checker, And get a live, contextual explanation Along with refactoring suggestions A learner could share their VS Code window: Highlight a block of code rejected by the borrow checker, And get a live, contextual explanation Along with refactoring suggestions It could be your lifesaver in critical situations, such as debugging a server outage. Screen sharing is not a paid feature. You can access it for free with Google AI Studio. Hay límites de tarifas para la versión gratuita, así que use con discreción. AI-Generated Code Y, por supuesto, una vez que aprendas más sobre Rust, puedes empezar a pedir a Gemini que genere código para ti. Asegúrese de que entiende bien el código que genera, especialmente en entornos de producción. Ensure you thoroughly understand the code you generate, especially in production environments. Especially then! For Example Usuario inmediato: "Generate a basic web server in Rust using the Axum framework that responds with 'Hello, World!' at the root URL." use axum::{routing::get, Router}; use std::net::SocketAddr; async fn root() -> &'static str { "Hello, World!" } #[tokio::main] async fn main() { let app = Router::new().route("/", get(root)); let addr = SocketAddr::from(([127, 0, 0, 1], 3000)); println!("listening on {}", addr); axum::Server::bind(&addr) .serve(app.into_make_service()) .await .unwrap(); } Advantages of Google Gemini AI as a Teacher Experiences from other educational AI tools, like Khan Academy's tutor, show that AI can: Provide guided practice Answer silly repeated doubts Be tailored to your level Provide hints Be available at any time of the day Correct itself when fact-checked with the compiler. Add encouragement Provide multi-domain knowledge such as AWS, GCP, Azure, and others Screen sharing can anticipate the required correction Provide company-saving advice during site outages Applying this to Rust: An AI can create a personalized learning path. If you struggle with Lifetimes: It can generate a series of targeted exercises and code-reading challenges to strengthen that specific skill. Ditto for Ownership Rules And for Traits And for Third Party Libraries Documentation And any concept you do not understand Una IA sobresale en explicar el código complejo y real que sería intimidante para los aspirantes a Rustaceos. For example, you can examine the explanation below: An AI excels at explaining complex, real-world code that would be intimidating to aspiring Rustaceans. For example, you can examine the explanation below: Example: Foreign Function Interface (FFI) Example: Foreign Function Interface (FFI) // Opaque C struct struct CComplexObject; // Functions imported from a C library extern "C" { fn c_complex_new() -> *mut CComplexObject; fn c_complex_process(obj: *mut CComplexObject, value: i32); fn c_complex_destroy(obj: *mut CComplexObject); } // Idiomatic and safe Rust wrapper struct SafeWrapper { obj: *mut CComplexObject, } impl SafeWrapper { fn new() -> Self { Self { obj: unsafe { c_complex_new() } } } fn process(&mut self, value: i32) { unsafe { c_complex_process(self.obj, value) }; } } impl Drop for SafeWrapper { fn drop(&mut self) { unsafe { c_complex_destroy(self.obj) }; } } AI Explanation: AI Explanation: extern "C" tells Rust you are defining functions that follow the C Application Binary Interface (ABI), allowing Rust to link with C libraries. *mut CComplexObject is a raw pointer. It's unsafe because the Rust compiler cannot guarantee that what it points to is valid. The unsafe keyword is required to call these C functions or dereference raw pointers, as you are telling the compiler, "I have read the rules and I guarantee this operation is safe." The SafeWrapper struct is an idiomatic way to manage the raw pointer. It holds the pointer internally. By implementing the Drop trait, you ensure that the C object's memory is always cleaned up (c_complex_destroy) when the SafeWrapper goes out of scope, preventing memory leaks. This is a core Rust pattern called RAII (Resource Acquisition Is Initialization). extern "C" tells Rust you are defining functions that follow the C Application Binary Interface (ABI), allowing Rust to link with C libraries. *mut CComplexObject is a raw pointer. It's unsafe because the Rust compiler cannot guarantee that what it points to is valid. The unsafe keyword is required to call these C functions or dereference raw pointers, as you are telling the compiler, "I have read the rules and I guarantee this operation is safe." The SafeWrapper struct is an idiomatic way to manage the raw pointer. It holds the pointer internally. By implementing the Drop trait, you ensure that the C object's memory is always cleaned up (c_complex_destroy) when the SafeWrapper goes out of scope, preventing memory leaks. This is a core Rust pattern called RAII (Resource Acquisition Is Initialization). Reducir el riesgo de alucinaciones Todos los LLM, incluyendo Gemini, pueden halucinar a veces. All LLMs, including Gemini, can hallucinate sometimes. All LLMs, including Gemini, can hallucinate sometimes. But we have an advantage: the Rust compiler! La ventaja más poderosa de usar la IA para aprender Rust es el loop de retroalimentación con el compilador. You can treat the compiler as the ultimate source of truth. You can treat the compiler as the ultimate source of truth. How to Check for AI Hallucinations: Cómo detectar las alucinaciones: Ask Gemini to write Rust code for a specific task. The AI generates the code. Paste this code directly into your local main.rs file or . the online Rust Playground Run cargo check. This command checks your code for errors without producing an executable. If the AI's code was incorrect (a "hallucination"): The Rust compiler (rustc) will almost certainly catch it. It will produce a high-quality, specific error message. You can then take this error message, feed it back to the AI, and ask: "The compiler gave me this error. Can you fix the code?" Ask Gemini to write Rust code for a specific task. The AI generates the code. Paste this code directly into your local main.rs file or . the online Rust Playground Run cargo check. This command checks your code for errors without producing an executable. If the AI's code was incorrect (a "hallucination"): The Rust compiler (rustc) will almost certainly catch it. It will produce a high-quality, specific error message. You can then take this error message, feed it back to the AI, and ask: "The compiler gave me this error. Can you fix the code?" the online Rust Playground This process of validating AI output with the compiler is an incredibly effective learning tool. Este proceso de validación de la salida de IA con el compilador es una herramienta de aprendizaje increíblemente eficaz. This process of validating AI output with the compiler is an incredibly effective learning tool. Other AI and Some Traditional Tools to Master Rust Several AI and non-AI tools help to assist your Rust learning journey. RustCoder Una herramienta gratuita y de código abierto llamada RustCoder ha sido utilizada efectivamente como un backend para herramientas de codificación Vibe modernas como Cursor. It is trained extensively on Rust code and can handle most of the Rust challenges that exist today. It even produces ‘Rustic’ code (did I just create a new technical term?). It even produces ‘Rustic’ code (did I just create a new technical term?). It is open to all and free. Más detalles están disponibles abajo: https://www.cncf.io/blog/2025/01/10/rustcoder-ai-assisted-rust-learning/?embedable=true El lenguaje de programación Rust Online Documentation The definitive guide to everything about Rust. Este es un recurso clásico que no debe omitirse. Comprender el código que produce la IA será mucho más sencillo con este recurso en línea gratuito. Understanding the code that AI produces will be much simpler with this free online resource. https://doc.rust-lang.org/stable/book/?embedable=true Los ejercicios del compañero - Rustlings These exercises will help you work through the Rust online book systematically. If you get stuck, you can ask an AI for the answer! https://rustlings.rust-lang.org/?embedable=true El gran valor del aprendizaje hoy en día Rust is in huge demand today for systems programming. Rust is in huge demand today for systems programming. La seguridad del tiempo de compilación para la concurrencia ha atraído la atención de numerosas empresas que alcanzan miles de millones de usuarios. Quizás el único idioma en mayor demanda es Python para la automatización y los agentes. ¡Y Rust también está atrapando en el espacio de agentes! Companies Pivoting to Rust Microsoft: Actively rewriting core Windows components, like parts of the kernel and the Win32 API, in Rust to reduce memory safety vulnerabilities. Amazon Web Services (AWS): Built Firecracker, the virtualization technology powering AWS Lambda and Fargate, entirely in Rust for security and speed. They also use it in parts of S3 and CloudFront. Google: Supports Rust for Android OS development and is funding efforts to write new Linux kernel modules in Rust, particularly for drivers, to improve kernel safety. Meta (Facebook): Rewrote their Mononoke source control server from C++ to Rust, citing performance and reliability improvements. They also use it heavily in their blockchain development. Apple: Apple is investing heavily in Rust for Robotics, AR/VR code, and Neural Engine processing. Hiring for Rust is at an all-time high. Cloudflare: Rust is used extensively across its product stack for performance-critical services, including its firewall, CDN, and Workers platform. Discord: Replaced a Go service with Rust to solve latency spikes in a real-time service, demonstrating Rust's superior performance for low-latency applications. Even today, many more companies are joining the bandwagon. Los desarrolladores de Rust cualificados están en alta demanda. Skilled Rust developers are in high demand. El paso fundamental crítico: Proyectos reales No se puede aprender un idioma sólo estudiando sus características. You need to get your hands dirty with real projects. Usted necesita para obtener sus manos sucias con los proyectos reales. You need to build high-quality projects that solve real business problems. Y si es posible, abrirlos y ganar atracción pública. If you do that, companies will come to you instead of you having to go to them! You need to build high-quality projects that solve real business problems. And if possible, open-source them and gain public traction. If you do that, companies will come to you instead of you having to go to them! This GitHub project below is an excellent guide for systems programming details: https://github.com/codecrafters-io/build-your-own-x?embedable=true There are even tutorials focused on Rust in this fantastic repository. There are even tutorials focused on Rust in this fantastic repository. Este tipo de reclutamiento inbound es la mejor oportunidad posible de destacarse en el mercado de asesinos de hoy. Miles de resúmenes generados por IA están golpeando a los reclutadores. This type of inbound recruitment is the best possible chance you have of standing out in today’s killer market. Thousands of AI-generated resumes are hitting recruiters. Un proyecto de código abierto que las empresas han adoptado podría ser su puerta de atrás en MAANG! An open-source project that companies have adopted could be your back door into MAANG! ¡Hay tantas opciones disponibles! There are so many choices available! Finally, the key moment you’ve been waiting for! ¡La fundación está firmemente establecida! Finally, the key moment you’ve been waiting for! The foundation has been firmly set! 15 ideas de proyecto que podrían llevarte a MAANG Inteligencia artificial y aprendizaje automático A "Zero-Trust" Federated Learning Framework: Implement a secure multi-party computation (MPC) framework in Rust for training machine learning models on decentralized data. Provide a production-ready, performant, and memory-safe alternative to current Python-based frameworks, which often struggle with security and efficiency in real-world federated learning scenarios. High-Performance Inference Engine for Edge AI: Develop a lightweight, high-performance inference engine in Rust, optimized for resource-constrained edge devices. Create a runtime that is significantly faster and more memory-efficient than existing solutions like TensorFlow Lite, enabling complex AI models to run on a wider range of IoT devices and sensors. A Verifiable and Reproducible ML Pipeline Tool: Build a tool that ensures the entire machine learning pipeline, from data preprocessing to model training, is cryptographically verifiable and reproducible. Leverage Rust's performance to create a tool that can handle large-scale datasets and complex models, addressing the critical need for trust and auditability in AI systems. Blockchain and Web3 A Scalable and Interoperable Blockchain Sharding Implementation: Design and implement a novel sharding mechanism for a blockchain that addresses the trilemma of scalability, security, and decentralization. Create a Rust-based solution that is more performant and secure than existing sharding approaches, a major hurdle for mainstream blockchain adoption. A Privacy-Preserving Smart Contract Platform with Zero-Knowledge Proofs: Build a blockchain platform that allows for confidential smart contracts using zero-knowledge proofs. Create a developer-friendly platform in Rust that simplifies the creation of privacy-preserving decentralized applications (dApps), a significant gap in the current Web3 ecosystem. A High-Throughput, Cross-Chain Communication Protocol: Develop a secure and efficient protocol for interoperability between different blockchain networks. Build a Rust-based solution that is significantly faster and more reliable than existing bridge protocols, which are often bottlenecks and security risks in the Web3 space. Los transformadores y los transformadores An Optimized Inference Server for Large Language Models (LLMs): Create a highly optimized serving framework for LLMs that minimizes latency and maximizes throughput. Leverage Rust's concurrency and low-level control to build a server that can handle massive-scale inference for generative AI applications, a major operational challenge for companies deploying these models. A Memory-Efficient Transformer Architecture: Implement a novel Transformer architecture in Rust that significantly reduces the memory footprint during training and inference. Address the quadratic complexity of the self-attention mechanism, a major bottleneck for working with long sequences, making large models more accessible and cost-effective to train and deploy A Framework for Fine-Tuning and Deploying Generative AI Models with Strong Security Guarantees: Develop a framework that focuses on the secure fine-tuning and deployment of generative AI models, addressing concerns like data privacy and model inversion attacks. Provide a Rust-based solution that integrates privacy-enhancing technologies directly into the MLOps lifecycle for generative AI. Computación cuantitativa A High-Performance Quantum Circuit Simulator: Build a quantum circuit simulator in Rust that can handle a larger number of qubits and more complex quantum algorithms than existing simulators. Leverage Rust's performance and memory management to push the boundaries of classical simulation of quantum computers, a critical tool for quantum algorithm development. A Post-Quantum Cryptography Library for Secure Communication: Develop a comprehensive and easy-to-use library for post-quantum cryptography algorithms. Provide a production-ready Rust library that is highly performant and resistant to attacks from both classical and quantum computers, a critical need as the threat of quantum computing to current encryption standards grows. A Compiler for a High-Level Quantum Programming Language: Create a compiler that translates a high-level, expressive quantum programming language into low-level quantum assembly code. Build this compiler in Rust to ensure its correctness and performance, enabling developers to write complex quantum algorithms more easily and with greater confidence. DevOps y MLOPS A Blazing-Fast, Cross-Platform Build and Deployment Tool: Develop a next-generation build and deployment tool in Rust that is significantly faster and more efficient than current solutions like Jenkins or Travis CI. Create a tool with a minimal footprint and first-class support for containerization and modern cloud-native environments, addressing the need for faster and more reliable CI/CD pipelines. A Secure and Observable Microservices Framework: Build a microservices framework in Rust that prioritizes security and observability from the ground up. Provide a framework with built-in features for service-to-service authentication, authorization, and detailed telemetry, addressing the growing complexity and security challenges of microservices architectures. An MLOps Platform for Rust-Based Models: Create an MLOps platform specifically designed for the lifecycle management of machine learning models written in Rust. Provide a seamless workflow for training, deploying, monitoring, and retraining Rust-based models, filling a gap in the current MLOps tooling which is heavily focused on Python. ¡Esto es tan complejo! ¡Soy un principiante! (AI al rescate) Remember, this is your pathway to a MAANG company. ¡Y AI está aquí para ayudarte! Remember, this is your pathway to a MAANG company. And AI is here to help you! Para un principiante, abordar un proyecto grande y complejo es una maratón, no un sprint. AI assistants like Google AI Studio can act as your personal tutor and coding partner. La colaboración de código abierto proporciona a la comunidad y el apoyo para verla a través. Open-source collaboration provides the community and support to see it through. Tu proceso de pensamiento lógico (pasos de bebé) : Understand the Core Problem Before writing a single line of code, use AI to explain the project's domain. Ask it, "Explain federated learning in simple terms". Or, "What is the blockchain scalability trilemma?" : Break It Down Ask your AI assistant, "I want to build a quantum circuit simulator in Rust. What are the main components I need to build Break this down into smaller, manageable tasks." : Generate the Skeleton For a small task like "create a struct for a blockchain block," ask the AI to generate the initial Rust code. This gives you a starting point to build upon. : Code, Test, Refine, Repeat Write your code for one small part. If you hit an error, paste the code and the error message into the AI assistant and ask for help debugging. : Go Public Immediately Create a project on a platform like GitHub from day one. This signals your intent to collaborate and makes it easier for others to join. : Document Your Journey Use the AI to help you write a clear README.md file explaining your project's goal and how others can help. A good project description is critical for attracting collaborators. Cómo ayudan los asistentes : Ask for simple explanations of complex topics like "What is a zero-knowledge proof?" Concept Explanation : Generate boilerplate code, functions, and data structures to get you started. Code Generation : Paste your broken code and the error message to get suggestions for a fix. Debugging : Ask the AI to generate comments for your functions or to write a project README.md file. Writing Documentation : Use it as an interactive tutor that can answer your specific questions as they arise. Learning El poder del código abierto Cada proyecto que construyes debe ser de código abierto. Usted no necesita ser un experto fantástico; sólo necesita una idea y la voluntad de colaborar. Every project you build should be open-source. You don't need to be a fantastic expert; you just need an idea and the willingness to collaborate. Carga de trabajo compartida: No tiene que construirlo todo usted mismo. Aprender de los demás: Revisar el código de los contribuyentes es una forma poderosa de aprender. : More eyes on your code means better quality and faster bug-finding. Get Feedback Conectarse con otros desarrolladores que podrían convertirse en mentores o futuros colegas. Critical First Steps for Beginners : Learn Rust Fundamentals Before starting a big project, complete a basic course. You can't use an AI assistant effectively without understanding the basics of the language. Make sure you understand Git: Git is fundamental. You should be familiar with the basics of Git and GitHub. : Choose a Single Project Pick the idea that excites you the most and stick with it. Focus is an underrated superpower. : Create a Public Repository Use GitHub to host your project. Blog about your product on Medium or HackerNoon. : Define a Clear Goal Write a one-paragraph description of what your project aims to achieve. Use AI if necessary, but make sure you understand everything you are talking about. AI can help you in that, too! : Find "Good First Issues" Look for beginner-friendly tasks in other open-source projects to get a feel for the contribution process. This gives you credibility and experience. Also, actual open source contributions are a dopamine hit! : Actively Seek Collaborators Share your project on platforms like the /r/rust subreddit or Discord communities. Create awareness about your project online with HashNode and LinkedIn as well. Recursos de aprendizaje Todos los recursos a continuación pueden ayudarle en su camino a convertirse en un Rustacean cualificado: All of the resources below can help you on your path to becoming a skilled Rustacean: Complejo Rust (por Google) https://google.github.io/comprehensive-rust/?embedable=true Guía de usuario de Linfa (ML Library) https://rust-ml.github.io/linfa/?embedable=true Construye una Blockchain en Rust Tutorial https://blog.logrocket.com/how-to-build-a-blockchain-in-rust/?embedable=true Aplicaciones de línea de comandos en Rust https://rust-cli.github.io/book/?embedable=true Utilice Perplexity.ai para obtener recursos para aprender sobre cualquier cosa! No utilices Google, ¡la perplexidad es mejor para todo, incluido el código! Blockchain, agentes de IA y IA generativa son actualmente las aplicaciones asesinas para Rust! Blockchain en particular es altamente lucrativo! Utilice Perplexity.ai para obtener recursos para aprender sobre cualquier cosa! Uso Recursos para aprender de todo! Preocupación.es Preocupación.es No utilices Google, ¡la perplexidad es mejor para todo, incluido el código! No utilices Google, ¡la perplexidad es mejor para todo, incluido el código! Blockchain, AI Agents, and Generative AI are currently killer applications for Rust! Blockchain in particular is highly lucrative! Conclusión Rust se encuentra como uno de los idiomas más poderosos pero desafiantes para aprender hoy en día. It has a syntax and a set of rules unlike any other mainstream language. Esta curva de aprendizaje abrupta se puede aplastar significativamente aprovechando herramientas de IA como Google AI Studio como tutor. Las integraciones como el compartir pantalla harán que el desgaste de problemas de propiedad complejos sea un proceso guiado y conversacional. Rust es el futuro definitivo de la programación de sistemas segura y de rendimiento, y su adopción por todas las grandes compañías de tecnología demuestra su valor. La actual escasez de desarrolladores de Rust de alta calidad, combinada con la creciente demanda, hace que el aprendizaje de Rust sea una inversión de carrera invaluable. Therefore, there has never been a more opportune moment to begin your journey with Rust. Con la IA como guía, el camino es más directo que nunca. Rust stands as one of the most powerful but challenging languages to learn today. It has a syntax and a set of rules unlike any other mainstream language. This steep learning curve can be flattened significantly by leveraging AI tools like Google AI Studio as a tutor. Integrations like screen sharing will make debugging complex ownership issues a guided, conversational process. Rust is the definitive future of secure and performant systems programming, and its adoption by every major tech company proves its value. The current shortage of high-quality Rust developers, combined with the growing demand, makes learning Rust an invaluable career investment. Therefore, there has never been a more opportune moment to begin your journey with Rust. Con la IA como guía, el camino es más directo que nunca. Con la IA como guía, el camino es más directo que nunca. I found the article below remarkably helpful for effectively preparing for a successful Rust career: https://medium.com/@CodeOps/i-spent-2-years-learning-rust-and-still-got-rejected-856b3f914520?embedable=true Por favor, tome un momento para leerlo; usted podría ahorrarse dos años de preparación que termina mal. Por favor, tome un momento para leerlo; usted podría ahorrarse dos años de preparación que termina mal. ¡Todo lo mejor, y siga los consejos en el artículo anterior si se está preparando para una carrera de desarrollo de Rust! ¡Todo lo mejor, y siga los consejos en el artículo anterior si se está preparando para una carrera de desarrollo de Rust! ¡Todo lo mejor, y siga los consejos en el artículo anterior si se está preparando para una carrera de desarrollo de Rust! Referencias Stack Overflow. (2023). 2023 Developer Survey. https://survey.stackoverflow.co/2023/#most-loved-dreaded-and-wanted-language-love-dread Khan Academy. (2023). Harnessing AI for education. https://www.khanmigo.ai/ The Rust Language Revolution: Why Are Companies Migrating? https://stefanini.com/en/insights/news/the-rust-language-technology-revolution-why-are-companies-migrating 2022 Review | The adoption of Rust in Business https://rustmagazine.org/issue-1/2022-review-the-adoption-of-rust-in-business Rust in 2025: Why Meta, Google, and Apple Are All In | Rustaceans https://medium.com/rustaceans/why-meta-google-and-apple-are-secretly-betting-on-rust-in-2025 Microsoft joins Rust Foundation - Microsoft Open Source Blog https://opensource.microsoft.com/blog/2021/02/08/microsoft-joins-rust-foundation Google Adopts Rust for Android: A Game-Changer for Mobile OS Security & Performance https://coinsbench.com/googles-rust-adoption-in-android-a-game-changer-for-mobile-os-development Amazon Web Services. (2020). Why AWS loves Rust. https://aws.amazon.com/blogs/opensource/why-aws-loves-rust-and-how-wed-like-to-help/ Discord Blog. (2020). Why Discord is switching from Go to Rust. https://discord.com/blog/why-discord-is-switching-from-go-to-rust General Rust Learning The Rust Programming Language ("The Book") https://doc.rust-lang.org/book Rustlings Exercises https://github.com/rust-lang/rustlings Comprehensive Rust (by Google) https://google.github.io/comprehensive-rust/ 11. AI/ML in Rust Linfa (A scikit-learn-like ML Framework) https://github.com/rust-ml/linfa https://rust-ml.github.io/linfa/ Tutorial: Build a Machine Learning Model in Rust https://www.freecodecamp.org/news/how-to-build-a-machine-learning-model-in-rust/ 12. Blockchain & Web3 in Rust Tutorial: Building a Blockchain in Rust https://blog.logrocket.com/how-to-build-a-blockchain-in-rust/ https://dev.to/iamzubin/how-to-build-a-blockchain-from-scratch-in-rust-38d6 13. Generative AI in Rust Hugging Face Candle (A minimalist ML framework) https://github.com/huggingface/candle 14. Quantum Computing in Rust Qiskit Rust (IBM's Quantum Framework Bindings) https://github.com/Qiskit/qiskit-rust 15. DevOps in Rust Book: Command-Line Applications in Rust https://rust-cli.github.io/book/ https://survey.stackoverflow.co/2023/#most-loved-dreaded-and-wanted-language-love-dread https://www.khanmigo.ai/ https://stefanini.com/en/insights/news/the-rust-language-technology-revolution-why-are-companies-migrating https://rustmagazine.org/issue-1/2022-review-the-adoption-of-rust-in-business https://medium.com/rustaceans/why-meta-google-and-apple-are-secretly-betting-on-rust-in-2025 https://opensource.microsoft.com/blog/2021/02/08/microsoft-joins-rust-foundation https://coinsbench.com/googles-rust-adoption-in-android-a-game-changer-for-mobile-os-development https://aws.amazon.com/blogs/opensource/why-aws-loves-rust-and-how-wed-like-to-help/ https://discord.com/blog/why-discord-is-switching-from-go-to-rust https://doc.rust-lang.org/book https://github.com/rust-lang/rustlings https://google.github.io/comprehensive-rust/ https://github.com/rust-ml/linfa https://rust-ml.github.io/linfa/ https://www.freecodecamp.org/news/how-to-build-a-machine-learning-model-in-rust/ https://blog.logrocket.com/how-to-build-a-blockchain-in-rust/ https://dev.to/iamzubin/how-to-build-a-blockchain-from-scratch-in-rust-38d6 https://github.com/huggingface/candle https://github.com/Qiskit/qiskit-rust https://rust-cli.github.io/book/ Google AI Studio se utilizó en este artículo para la ideación, el resumen, el código y la investigación. https://aistudio.google.com/ Google AI Studio was used in this article for ideation, outlining, code, and research. You can access it here: https://aistudio.google.com/ https://aistudio.google.com/ Todas las imágenes fueron generadas por el autor utilizando NightCafe Studio, disponible aquí:https://creator.nightcafe.studio/explore All images were generated by the author using NightCafe Studio, available here: https://creator.nightcafe.studio/explore https://creator.nightcafe.studio/explore