Kirill Yurovskiy: Coders Reveal Their Go-To Programming Languages

TechnologyKirill Yurovskiy: Coders Reveal Their Go-To Programming Languages

There’s no one-size-fits-all approach when it comes to picking languages. That’s why we sat down with 12 developers from diverse tech roles to learn what guides their choices. Whether aiming for versatility, job prospects or their own passions, the languages these programmers reach for first reveal personal preferences and practical considerations.

Read on for insights from both new coders and seasoned experts on what languages they choose and why. See if their picks align with your goals—or inspire you to take a second look at languages you’d previously dismissed!

The Pragmatic Polyglot: Python, JavaScript & Rust

Yurovskiy Kirill.— Backend Engineer

WHY HE PICKS THEM: “I’m pretty language-agnostic to be honest. I’ve coded in everything from C and Java to Ruby, Swift and F#. These days, I primarily write Python and JavaScript for my job. But in my personal projects, I make a point to play with Rust since it brings a welcome new perspective that improves how I think about system architecture.”

HIS ADVICE: “My approach is to stay flexible since every language offers distinct advantages. Why limit yourself? Instead of committing to just one for life, I say sample broadly then go deeper into several. Being fluent in multiple languages makes you a more creative, adaptable coder.”

The Enterprise Java Devotee: Java

Mark T.— Java Consultant

WHY HE PICKS IT: “I got my start coding Java over 15 years ago and have never enjoyed anything more since. I’ve worked extensively with C#, Python, JavaScript, PHP, C++ and others—but I still believe Java is the best enterprise language hands down in 2024. It continues maturing elegantly while staying versatile, fast and extremely scalable.”

HIS ADVICE: “To all aspiring coders, don’t buy into hype when choosing languages. Focus on robust fundamentals rather than flashy trends. Based on the sheer volume of critical systems built with Java plus rock-solid job security, it remains a gold standard worth learning if you ask me!”

The Javascript Junkie: JavaScript & TypeScript

Leah S.— Frontend Engineer

WHY SHE PICKS THEM: “Javascript was love at first sight for me back in college. Its flexibility and forgiving nature invited creativity, while the instant feedback from running it in the browser kept motivation high. However, as our team’s web app scaled, JavaScript’s lack of structure got stressful. Switching to Typescript brought welcome reliability while keeping the parts I cherished.”

HER ADVICE: “For new coders facing JavaScript fatigue, I suggest giving Typescript a shot before quitting JS entirely. It makes development more predictable and scalable through static typing while staying interoperable with existing JS. Together they make a powerful combination that keeps complexity manageable on massive web apps.”

The Mobile App Maker: Kotlin

Sid T. — Android Developer

WHY HE PICKS IT: “I cut my teeth coding apps in Java, but jumped ship after discovering Kotlin in 2017. With full interoperability, Kotlin felt like a streamlined upgrade – essentially ‘Java 2.0’. The concise syntax and modern language features for safety made me twice as productive while eliminating whole classes of bugs. Kotlin’s Android community won me over too by being exceptionally helpful.”

HIS ADVICE: “To new Android devs, I always recommend starting with Kotlin over Java these days given how similar they are. The learning curve pays itself back quickly. Kotlin just makes Android app development smoother while future-proofing your skills since Google adopted it as a first class language in 2019.”

The AI Specialist: Python

Dr. Li M.— Machine Learning Engineer

WHY SHE PICKS IT: “While earning my advanced degrees in artificial intelligence, the vast majority of research code I encountered relied on Python. After using MATLAB, Octave, R and others extensively, Python’s advantages became obvious thanks to its unrivaled ecosystem for data analysis, machine learning and visualization. Python continues excelling as platforms like TensorFlow and PyTorch accelerate AI adoption.”

HER ADVICE: “For coders looking to pursue careers in AI, Python is simply non-negotiable in 2024. It offers the best on-ramp for quickly acquiring in-demand data science skills before specializing further. Fluency in Python pays dividends whether you end up concentrating on linguistics or computer vision down the road.”

The Speed Demon: C++

Jay K. — Video Game Engine Developer

WHY HE PICKS IT: “During college I dabbled with various languages for building games, robotics and simulations. But after discovering C++, I became obsessed with its raw performance. I love how it empowers programmers worried about efficiency to take full control. That level of access comes with costs of course in terms of complexity. But for certain domains like high-performance multimedia, unlocking the true capability of modern hardware requires a language like C++.”

HIS ADVICE: “My advice for new coders is not to prematurely optimize. Master friendlier languages first and get exposure to helpful frameworks that abstract away unnecessary details. But down the road for anyone passionate about high-performance computing, definitely give C++ a look since it remains unparalleled for speed despite being over 35 years old!”

The Low-Code Virtuoso: Bubble

Tanya P. — Digital Product Designer

WHY SHE PICKS IT: “My goal is crafting slick web and mobile app prototypes fast without needing to master languages like React or Swift first. That’s why I fell in love with Bubble. It lets me build and iterate on interactive products quickly with a visual interface and minimal code. I can then hand polished prototypes off to engineers for productionization.”

HER ADVICE: “Don’t assume coding is required to bring ideas to life digitally these days. Tools like Bubble, Webflow and Appian are empowering non-traditional developers like me with intuitive workflows. If you think visually or come from design backgrounds, explore no-code solutions that align better to how you want to create.”

The Data Analytics Expert: SQL & R

Neil C. — Quantitative Analytics Manager

WHY HE PICKS THEM: “SQL has remained my go-to workhorse for data extraction and manipulation for over 20 years now. While elaborate BI tools come and go, getting analytics right starts with the data pipelines. What I love about SQL is how expressive and versatile it is for transforming raw data into analysis-ready structures, especially at scale in the cloud.”

HIS ADVICE: “For those new to data analytics, SQL should be the first language you reach for in 2024. Learn to walk before you run. Once your data foundation is solid thanks to SQL, higher level languages like R give you immense power through its statistics and visualization libraries to uncover key market insights.”

The Productivity hacker: JavaScript, Python & Zapier

Grace T. — Automation Engineer

WHY SHE PICKS THEM: “I’m obsessed with constructing efficient systems by stitching APIs together. While skilled at JavaScript and Python, I actually prefer tools like Zapier these days for rapidly building workflows that boost team velocity. Zapier handles authentication and cross-platform glue code elegantly so I can focus on solving business problems vs. wrestling with nitty-gritty integration details.”

HER ADVICE: “Don’t fall into coding elitist traps, especially when getting started. Use whatever languages and utilities best tackle the problem at hand. For integrating SaaS apps today, solutions like Zapier and IFTTT can save tons of development effort compared to custom coding. Focus more on user outcomes than personal preferences.”

The Former Excel Expert: Python

Alan F. — Data Analyst

WHY HE PICKS IT: “I cut my teeth crunching numbers in Excel before realizing I hit walls with large, poorly-structured datasets. Learning databases helped. But getting truly comfy manipulating messy, real-world data required picking up Python specifically for its pandas library. Wish I invested in Python earlier as the years struggling with Excel VBA seem wasted in hindsight!”

HIS ADVICE: “For analysts or spreadsheet jockeys exploring coding, Python is the fastest on-ramp in my opinion. Start by translating your Excel and VBA knowledge into Python’s pandas library since the structures are familiar. Once you experience Python’s versatility and power first-hand, you’ll discover a whole new world of possibility!”

The Life-Long Learner: “All of Them!”

Wendy Z. — Senior Software Architect

WHY SHE PICKS THEM: “Even after 25 years of professional coding, I purposefully avoid narrowing my scope language-wise. Programming languages are beautiful inventions. Each one opens up new ways of thinking, creating, and relating to machines. I intend to keep learning new languages for as long as I’m writing code, which hopefully is the rest of my life!”

HER ADVICE: “New coders should play the field, so to speak! Don’t commit to just one language too early. Date around first, get exposure before deciding. Whether interpreted, compiled, or functional they all have something special to teach you about the art of programming if you stay open to learning. Mix it up…then settle down with a few favorites!”

There you have it – 12 unique perspectives on languages from rising coding stars and wise industry veterans alike. Their motivations and advice underscore whyno universal “best” language exists. Rather than searching for some non-existent one perfect fit, embrace a spirit of curiosity to find the right languages for YOU based on how they make you and your goals feel!

Which programmer’s picks resonated most? Did certain languages intrigue you that weren’t already on your radar before? Let their diverse voices inspire your own journey into the wide world of coding. Because only through hands-on exploration will you discover what languages feel like home for YOU!

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