Akash Wakade’s Post

𝗪𝗵𝘆 𝗣𝗿𝗼𝗯𝗹𝗲𝗺-𝗦𝗼𝗹 v𝗶𝗻𝗴 𝗜𝘀 𝗠𝗼𝗿𝗲 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗧𝗵𝗮𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 When someone asks you which programming language to learn first, what do you say? You might say Python, JavaScript, or Java. But the question itself might be wrong. The language is just a tool. What matters is how you think through a problem. Here are a few things to consider: - Problem-solving is key to programming. - You can learn any language in weeks if you think clearly. - Languages are visible, but problem-solving is invisible and harder to measure. Let's try something. Imagine your friend asks you to share 10 chocolates equally with 4 people. You don't need a programming language to answer this. You just think through it. That's problem-solving. A developer who thinks in problems first can pick up any language quickly. They understand how buildings work, not just the tools. So, focus on building your problem-solving skills. Read problems out loud, write your logic in plain English, and practice on paper. This will make you better in every language. Source: https://lnkd.in/gcuJXWhP

How Garbage Collection Works in Modern Languages Writing code is fun. Managing memory? Not so much. Fortunately, most modern programming languages handle that for you through a mechanism called Garbage Collection (GC). What is Garbage Collection? When a program runs, it constantly allocates memory for variables, objects, and data. Once that data is no longer needed, the memory should be freed. In languages like C, developers do this manually. One mistake and you get memory leaks or crashes. Garbage Collection automates this process. It identifies memory that is no longer in use and reclaims it, so developers can focus on building rather than managing memory. How Does It Actually Work? Modern garbage collectors use several strategies: Reference Counting Every object tracks how many references point to it. When the count drops to zero, the memory is freed. Simple, but struggles with circular references where two objects pointing to each other will never reach zero, causing leaks. Python uses this approach alongside a cycle detector. Mark and Sweep The GC starts from root references like global variables and active stack frames, and marks every reachable object. Everything left unmarked is considered garbage and gets swept away. Java and JavaScript use variations of this. Generational Garbage Collection Most objects die young. Memory is divided into generations. New objects go into the young generation, and only objects that survive multiple GC cycles are promoted to older generations. This makes collection faster and more efficient. Used by the JVM, V8, and CPython. The Trade-off Garbage collection is not free. It introduces GC pauses, brief moments where the program freezes while memory is being cleaned. Modern GCs like Go and Java are highly optimized to minimize these pauses, but they still exist. This is why performance-critical systems like game engines or operating systems still prefer manual memory management in C and C++, or ownership models like in Rust. Why Should You Care? Understanding GC helps you write memory-efficient code, debug unexpected slowdowns, and make informed decisions when choosing a language or runtime for your project. You may not manage memory manually, but knowing who does it for you and how, makes you a sharper engineer. #snsdesignthinkers #snsdesignthinking #snsinstitutions #GarbageCollection #MemoryManagement #ProgrammingLanguages

“Why do we learn so many programming languages in B.Tech?” If you’ve ever asked this question… you’re not alone. At some point, every engineering student wonders— “Why C, C++, Java, Python, SQL… all of them?” Here’s the truth 👇 Each programming language is not just a tool… it’s a new way of thinking. 🔹 C teaches you the foundation — how memory works, how logic is built from scratch. 🔹 C++ introduces you to object-oriented thinking — structuring real-world problems. 🔹 Java builds scalability and discipline — writing robust, enterprise-level code. 🔹 Python shows you simplicity and speed — solving complex problems with clean syntax. 🔹 SQL/MySQL teaches you how to communicate with data — because data drives everything today. 💡 So, it’s not about learning “every language”… It’s about learning every perspective. Because in the real world: ➡️ Problems don’t come labeled with a specific language ➡️ Solutions require flexibility ➡️ And great developers don’t just code… they adapt The more languages you explore, the better you become at problem-solving, logic-building, and choosing the right tool for the job. 📌 So next time you feel overwhelmed, remember: You’re not just learning syntax… You’re building a mindset that sets you apart. 💬 Let’s make this interactive: Which programming language changed your way of thinking the most—and why? 👇 Drop your answer in the comments!

I LIKE functional programming. If you know me, you know my passion is Clojure. I like FP thinking, and like to use it. But funnily enough I'm getting the AI to write me an (originally small, but growing) Python application, and one thing that surprises me is that there are lots of things that look like obvious candidates for classes and OO solutions that it, instead, solves with a stack of functions. And even some huge closures. I mean, really big 1000 line closures with dozens of function definitions nested inside. These are obviously classes in all but name. If you're writing python there are times you don't want classes. We've all read "Execution in the Kingdom of Nouns", and laughed at Java (back when all Java functions needed a class escort) But there are definitely some times that classes ARE the right solution in Python. So it's weird. Did OO fall out of fashion and people now think you always need to avoid classes and objects? And the AI training data is now skewed away from them?

Software engineers hate taking out their trash. That's why the most popular programming languages in the world are Python, Javascript, and Java. These languages have "automated garbage collection" baked in, AKA users don't need to manually allocate and deallocate memory for each variable they use. This saves engineers a ton of time and makes software much less error prone compared to lower level languages like C, Rust, and Fortran. In the world of LLMs and AI agents, everyone today is doing the equivalent of coding in C or Fortran. Managing context is like managing CPU memory. Developers using LLM APIs need to deliberately manage the context for their system, and failing to do so properly will cause the whole system to collapse. An *unlimited* context window won't solve this (or ever happen), but automated garbage collection will. That's a core component of our Agent Engines at Subconscious. We've built automated context management directly into the model and inference runtime layer, to bring us into the next era of agent building. We're constantly improving about how we clean out your context window automatically. We take out the trash. Dana Wensberg wrote up a great post on our automated context management system, read more in the comments.

I used to hate Python. Coming from C++ and Java, it felt fragile, inconsistent, and way too forgiving. Indentation defines scope, types are optional, performance isn’t great… and don’t get me started on packaging. The interesting part is: most of those things are still true. In today’s video, I talk about why I still use Python anyway, and the bigger lesson behind it. At some point, you realize it’s not about finding the “best” language. It’s about understanding trade-offs and choosing the right tool for the problem you’re solving. If you want to grow as a developer, that shift in thinking matters much more than the language you use. 👉 Watch here: https://lnkd.in/eXAPr3wq. #python #softwareengineering #programming #developers #careergrowth

Programming languages are just tools. But the way we use them makes all the difference. ⚙️ 🔹 C — Simple, but you better be careful 🔹 Java — Structured, reliable, enterprise-ready 🔹 JavaScript — Flexible… sometimes too flexible 😅 🔹 C++ — Powerful, but can get messy fast 🔹 Python — Simple, yet dangerously powerful 🚀 Here’s the truth most beginners miss: 👉 No language is “best” 👉 Every language is optimized for a problem space The real skill is not *learning more languages*… It’s knowing **when to use which tool**. Because in real-world engineering: ✔️ Clarity beats complexity ✔️ Maintainability beats cleverness ✔️ Problem-solving beats syntax Focus less on *which language is trending* Focus more on *what problem you’re solving*. That’s how great developers think. 💡 #Programming #SoftwareDevelopment #Coding #Python #JavaScript #Java #Cpp #DeveloperMindset #TechCareers

🚀 Starting my journey in Java programming! Today I implemented a simple concept with a Program— Factorial of a number. Factorial is widely used in mathematics and programming problems. Through this program, I practiced loops, condition handling, and method creation in Java. 💡 What I learned: • Writing reusable methods • Handling edge cases (like negative numbers) • Taking user input using Scanner • Strengthening my logic-building skills Here’s my implementation: import java.util.*; class FactorialProgram { private static int factorial(int a) { int fact = 1; if (a >= 0) { for (int i = a; i >= 1; i--) { fact = fact * i; } } else { System.out.println("Factorial of negative numbers cannot be determined"); return 0; } return fact; } public static void main(String args[]) { Scanner sc = new Scanner(System.in); System.out.print("Enter the number: "); int a = sc.nextInt(); System.out.println("\nFactorial of the Number: " + factorial(a)); sc.close(); } } Would love feedback or suggestions to improve this further 🙌, as i am learning please help!! #Java #Programming #CodingJourney #LearningInPublic #BeginnerDeveloper #TechSkills

Been looking at how different languages handle errors lately, and it's kind of interesting how different they all are. Some languages like Go make you check errors explicitly at every step. It's verbose but you always know what's happening. Rust does something similar but forces you to handle things with its Result type. Java and C# go the exception route. Errors bubble up until someone catches them. Python does this too. It's cleaner to read but sometimes exceptions get lost if you're not careful. Then there's languages like Elm or Haskell where errors are just data you pass around. No exceptions at all. None of these approaches are perfect. They all have tradeoffs between safety, readability, and how much code you have to write. What's worked best for me is just understanding the pattern my language uses and being consistent with it. Fighting against the language's style usually makes things worse. #SoftwareEngineering #Programming #ErrorHandling

Everyone asks: 👉 “Which is the best programming language?” But very few ask: 👉 “What logic does this language teach me?” The truth is — there is no “best” language. There is only the language that shapes your thinking. 🟢 C teaches you how memory actually works. 🟢 Java teaches you structured, object-oriented thinking. 🟢 Python teaches you clarity and simplicity. 🟢 JavaScript teaches you asynchronous thinking and real-world adaptability. But here’s the real secret 👇 Languages change. Logic stays. Frameworks evolve. Syntax updates. Trends come and go. But if you understand: ✔ How data flows ✔ How memory is managed ✔ How problems are broken into steps ✔ How systems communicate You can learn any language. The best journey in a developer’s career is not mastering one language. It’s mastering the way of thinking behind them. Because coding is not about typing faster. It’s about thinking deeper. Choose a language. Respect its logic. Learn the fundamentals. And you’ll never fear technology changes again. 🚀 #Programming #DeveloperJourney #CodingLife #TechGrowth #SoftwareDevelopment