Java Build Speed Impact on AI Workflow

TIL: The best programming language for AI isn't Python A Tencent study tested 30+ models across 20 languages. Elixir hit 97.5% problem completion. Claude Opus scored 80.3% on Elixir — next closest was C# at 74.9%. Turns out immutability, great documentation, and a decade of stable APIs make it easy for LLMs to reason about your code. Who knew that making things simple for humans also makes things simple for robots. Add to that Tidewave.ai: a fantastic MCP server that gives coding agents direct access to the entire Elixir docs ecosystem. You get context engineering at the language level. Thanks to José Valim, read his article: https://lnkd.in/ehiavfsE

We just open-sourced our first core developer library Today we’re releasing Pygments Swift — a Swift-native port of the legendary Python Pygments syntax-highlighting engine. This is our first open-source release in the code-highlighting space, and it’s a foundational piece we built for our own Mac/iOS project: QW Code Viewer. Why this matters  🧠 Swift-native syntax highlighting (no Python runtime, no bridges)  🧪 Proper testing baked in — including visual regression tests  🖼️ PNG & PDF output verification using OCR  Yes — we literally read the rendered images back to confirm correctness.  📂 Supports 20 programming file formats (and growing) We believe code highlighting is infrastructure, not a UI afterthought. If developers are going to read code more than they write it (hello, AI 👀), the reading experience needs to be rock-solid. This library powers QW, our artisan code viewer built for:  reading code  sharing beautiful snippets  archiving human-written code for the future This is just the beginning. More tools, more open source, more love for code readers ❤️

Claude Code recently added LSP support and it's a game-changer for developers. Before: Claude was doing fancy grep to understand your code. Burning tokens searching blindly. Now: It understands your code the SAME way IDE does. ✅ Real-time error detection after every edit ✅ Go-to-definition & find references instantly ✅ Traces call hierarchies like a pro IDE ✅ Actually UNDERSTANDS your codebase semantically The result? ~10x fewer wasted tokens. Less guessing. Fewer bugs. Smarter code generation. This is the moment AI coding stopped guessing and started truly understanding code. Enable it: ENABLE_LSP_TOOL=1 claude Supports: TypeScript, Python, Rust, Go, Java, C/C++ & more #ClaudeCode #LSP #AI #Developers #Anthropic

Need to quickly understand a programming language's syntax?  Learn X in Y Minutes is a community-driven platform with 200+ programming language and tool cheat sheets.  Each guide is heavily commented, executable code designed for rapid learning - perfect for syntax refreshers or getting started with a new language. Want to quickly grab idea of Ansible playbooks? Understand Lua for ngx_http_lua_module? Get a grasp of Elixir, Zig or Rust? It's all there. Not a replacement for deep learning, but perfect for quick starts and refreshers. Check it out: https://lnkd.in/g4GNhich Direct links:  • Ansible: https://lnkd.in/gJQbHbcn  • Lua: https://lnkd.in/g8K6tNBr  • Elixir: https://lnkd.in/g84ibCef  • Zig: https://lnkd.in/gDV2CERh  • Rust: https://lnkd.in/gPddNuTV  #programming #learning #devtools #ansible #lua #elixir #zig #rust

🚀 DSA Journey — LeetCode Practice 📌 Problem: Bulb Switcher 💻 Language: Java 🔹 Approach: In this problem, bulbs are toggled multiple times based on their positions. After analyzing the pattern, only bulbs at perfect square positions remain ON (1, 4, 9, 16…). So instead of simulating every toggle, I counted how many perfect squares are less than or equal to n. This can be done by incrementing i while i * i <= n. ⏱ Time Complexity: O(√n) 🧩 Space Complexity: O(1) 📖 Key Learning: Understanding the mathematical pattern behind the problem helped avoid brute-force simulation and led to a much more efficient solution. Turning observations into optimized code is what makes problem-solving exciting 💡 #DSA #Java #LeetCode #ProblemSolving #CodingJourney #LearningInPublic #DSAWithedSlash

The new edition of the Go Developer Survey shows that Go developers are very satisfied with the programming language, but less so with AI assistants.

The new edition of the Go Developer Survey shows that Go developers are very satisfied with the programming language, but less so with AI assistants.

Ever wonder why some systems crumble under scale while others thrive? The answer often isn’t the tools. It’s the way we think about building software. This first post in our new series explores how functional programming in Scala can help tackle unpredictable state, hidden side effects, and concurrency challenges without drowning in complexity. Follow along as we dive deeper into practical FP insights, real-world applications, and why Scala is worth your attention. Don’t miss the full series! Read the first post in the series: https://lnkd.in/gektCmX9

Ever wanted to build your own programming language? Here’s my step-by-step tutorial series. Introducing Pyxc (pronounced “Pixie”) — a compiled, Python-inspired language built from scratch with LLVM. Think of it as Python meets systems programming: familiar, readable syntax paired with the performance of compiled code. Why build yet another language? Because learning how compilers really work is one of the most rewarding skills a developer can master. And while the classic Kaleidoscope tutorial is a great start, I wanted something with a more modern, practical feel. So I’m writing Pyxc: My First Language Frontend with LLVM, a hands-on guide that walks you through creating a real, usable language—not just a toy. What you’ll build: ✅ A Python-like lexer and parser ✅ LLVM IR generation ✅ JIT compilation and optimization ✅ Control flow, variables, and user-defined operators ✅ Structs, classes, and a basic type system … and more, chapter by chapter. This isn’t just theory. You’ll end up with a working compiler for a language you designed yourself—perfect for a portfolio, a learning milestone, or just the thrill of creation. The first two chapters are live now: Chapter 1: Language and Lexer – tokenizing Python-like syntax Chapter 2: Parser and AST – building your abstract syntax tree 👉 Read and follow along here: https://lnkd.in/g4Dj_Rij New chapters drop frequently. Whether you’re a curious engineer, a student, or just someone who loves to build—come code a compiler with me. #Compilers #LLVM #ProgrammingLanguages #Python #Cpp #SoftwareEngineering #LearnToCode #OpenSource

🐍 Day 33 — Introduction to Object-Oriented Programming (OOP) Day 33 of #python365ai 🧱 OOP helps structure programs using objects. Core ideas: - Classes - Objects - Attributes - Methods 📌 Why this matters: OOP is widely used in large software systems and frameworks. 📘 Practice task: Think of a real-world object (e.g. Student) and list its attributes. #python365ai #OOP #PythonProgramming #LearnPython