Joost Den Boer’s Post

🚀 AI has changed how we write software — for the better. But lately, I’ve noticed something uncomfortable (starting with myself). We generate code faster than ever… yet we often skip asking: ❓ Is this the best solution? ❓ Is this idiomatic Java? ❓ Can this be simpler, cleaner, or more maintainable? AI is incredibly powerful — but only if we can read, review, and reason about the code it produces. While using AI extensively, I realized I was drifting away from core Java fundamentals. So I decided to restart — slowly, deeply, and intentionally. 📘 I’m now building in-depth Java conceptual notes to strengthen my foundations and use AI more effectively — not blindly. I’ll be sharing these notes topic by topic. This time, the focus is not speed — it’s clarity and depth. If you're on a similar journey, let’s learn together 🤝 #Java #LearningJourney #SoftwareEngineering #BackendDevelopment #AI

🚨 Developer Mistakes While Switching to a New Programming Language 🚨 Switching to a new programming language feels exciting… until reality hits 😅 Many developers think: *"Syntax change hai bas… easy hoga!"* But that’s where most mistakes begin 👇 --- 🔻 1. Thinking Syntax = Mastery Just because you understand syntax doesn’t mean you understand the language. Every language has its own *philosophy* (Python vs Java mindset is very different). 🔻 2. Writing Old Language Style Code C++ mindset in Python = disaster Java mindset in JavaScript = over-engineering 👉 Learn the *idiomatic way*, not just the working way. 🔻 3. Ignoring Core Concepts Skipping fundamentals like: • Memory management • Async behavior • Type system These are the things that actually matter in real-world projects. 🔻 4. Not Exploring Ecosystem Language ≠ Just syntax It includes: ⚙️ Frameworks 📦 Libraries 🛠 Tools Ignoring ecosystem = slow growth 🔻 5. Over-relying on AI Without Understanding Copy-paste from AI tools without understanding logic = long-term damage 👉 AI should *assist*, not *replace thinking* 🔻 6. Expecting Instant Productivity New language ≠ immediate efficiency You will feel slow. You will feel confused. And that’s NORMAL. 🔻 7. Skipping Hands-on Practice Watching tutorials ≠ learning 👉 Build projects 👉 Break things 👉 Fix them That’s how real learning happens. 💡 Final Thought: Switching languages is not about *learning new syntax*, it’s about *rewiring your thinking*. 🔥 Have you ever switched a language and struggled? What was hardest for you? #Programming #Developers #Coding #SoftwareDevelopment #Learning #Python #JavaScript #CareerGrowth #Tech #AI #Automation

I’m releasing Ansatz, a new Clojure library for verified programming: https://lnkd.in/g_3ZcfTF Ansatz explores what it looks like to bring proof-oriented programming into the Clojure/JVM world. The core idea is to write programs and proofs in Clojure s-expressions, check them against a CIC kernel implemented in Java, and then run verified functions as ordinary JVM code. The project is inspired by Lean 4 and aims at interoperability with that ecosystem. It already works with imported declarations from Lean libraries such as Mathlib and CSLib, which opens an interesting path toward using a large body of existing formalized mathematics and verified algorithms from within Clojure. What Ansatz currently focuses on: - verified function definitions - theorem proving with tactics in Clojure syntax - inductive types and structures - import/export around Lean 4, Mathlib, and CSLib - a JVM-native foundation for larger systems This is the first release. It is not a throwaway side project, and a lot of work already went into getting the kernel, import pipeline, and proof machinery into usable shape. I am exploring this direction seriously because I want to build AI infrastructure on top of it (leveraging the persistent memory model also used in https://datahike.io/). At the same time, this is still early work and definitely not stable. I expect rough edges, especially in tactic implementations, and I would not be surprised if there are still gaps in the kernel and the surrounding workflow. There are dragons here. So this release is also an invitation. If you are interested in verified programming, theorem proving, Lean 4 interoperability, or AI systems built on top of more trustworthy formal foundations, I would be glad if you take a look and explore the direction with me. #Clojure #FormalMethods #TheoremProving #Lean4 #JVM #ProgrammingLanguages #AI

The rules of software development just changed. GitHub’s latest Octoverse report reveals a profound structural shift: TypeScript has overtaken Python and JavaScript, surging by 66% in a year. Why? Because we’re no longer just coding for machines; we’re conversing with cognitive partners. This 'Symbiotic Syntax' is driven by AI guardrails and the Convenience Loop. Are you ready to become a system orchestrator? Dive into the full analysis of how AI is rewriting the rules of code. #SoftwareEngineering #AI #GitHub #TypeScript #TechTrends https://lnkd.in/giu7QccF

Everyone is talking about "vibe coding" complex systems with AI. But what happens when that system needs to execute trades in nanoseconds? The vibes stop, and hardcore computer science begins. 📉⚡ I recently architected a hybrid High-Frequency Trading (HFT) engine. I used AI to accelerate the raw syntax generation, but the underlying system design required a deep dive into bare-metal performance optimization. The core challenge: How do you combine the rapid ML iteration of Python with the deterministic, nanosecond latency of C++? The solution: 🚀 C++ "Hot Path" for raw market data ingestion. 🧠 Python "Smart Path" for PyTorch-based regime detection. ⚡ POSIX Shared Memory (mmap) + Flatbuffers for true Zero-Copy Inter-Process Communication, bypassing the OS network stack and starving the Python Garbage Collector. 🛡️ Optimistic Shadow Books & ZMQ Watchdogs to ensure the AI doesn't bankrupt the account during a microsecond latency spike. AI is an incredible tool for writing code, but taking 100% intellectual ownership of the system architecture understanding how every byte moves through RAM is still the job of the engineer. I wrote a deep dive on the architecture and the tradeoffs made here: https://lnkd.in/gVDSQ_pR #SystemsEngineering #Cplusplus #Python #HFT #AlgorithmicTrading #MachineLearning #SoftwareArchitecture

🚀 Claude Code: The AI Coding Assistant Most Developers Are Missing Many developers think AI tools only generate code. But Claude Code goes much deeper. It can: ✔ Read your entire codebase ✔ Edit files directly in your project ✔ Refactor modules ✔ Generate tests and documentation ✔ Debug using full project context In this carousel, I break down: • What Claude Code actually is • How to install and use it • Where it helps the most • Where you should still rely on your own knowledge AI won’t replace developers - but developers who use AI effectively will move much faster. Swipe through to learn how to use it properly. 👇 #AI #Python #Coding #Developers #SoftwareDevelopment #ArtificialIntelligence #Programming #TechLearning #DeveloperTools

Programming language choice used to be about raw performance versus developer productivity. AI code generation is changing that equation. David Parry looks at how AI tools are reshaping what matters when picking a language. Performance gaps are narrowing, but there's a new factor to consider: how well does your language work with AI assistants? The tradeoffs aren't gone. They've just shifted. https://lnkd.in/e6E52DDT #Programming #AI #SoftwareDevelopment #Java

Just completed my Claude certifications and everything changed🤯..... Thought I'd learn some prompt tricks. Instead, I discovered a thinking partner that actually understands problems. Here's what shifted for me: 🧠 Extended Thinking - Claude reasons through complex issues instead of just answering. Caught 3 bugs I would've missed. 🔨 Artifacts - Building and iterating without endless copy-paste. React components, Python scripts, HTML designs—all live and instant. ⚡ Context That Sticks - Multi-turn conversations feel like talking to someone who actually gets what you're building. 💻 Code Execution - Test ideas instantly. No "here's code, go run it yourself." The real lesson? Clarity compounds. The better you frame the problem, the smarter the output. This isn't hype. This genuinely changed how I work. If you build, write, analyze, or solve problems—it's worth the 30 minutes to learn this properly. #Claude #AI #Productivity #Innovation

I’m glad to share that I participated in a webinar on “Prompt-Driven Development: Building Secure Enterprise Java Apps with AI” conducted by NeST Digital Academy. This session gave me valuable insights into: How prompt engineering can enhance development workflows Integrating AI into enterprise-level Java applications Security considerations when building AI-powered systems The future of AI-assisted software engineering As someone deeply interested in system design and scalable backend systems, understanding how AI fits into enterprise development is incredibly exciting. Looking forward to experimenting more with AI-driven development approaches in my projects. #AI #Java #BackendDevelopment #SystemDesign #PromptEngineering #LearningJourney #SoftwareEngineering

The most viral dev tweet of the year and honestly? It's missing the punchline. "Strong engineers create C. C creates good times. Good times create Python. Python creates AI. AI creates vibe coding. Vibe coding creates weak engineers. Bad times create strong engineers." Great meme. But here's what it gets wrong. The next generation of strong engineers won't be the ones who reject vibe coding and go back to writing C. They'll be the ones who can vibe code a full MVP on Monday and then drop into the memory hierarchy to debug why their system is 10x slower than it should be on Tuesday. The engineers I see thriving at startups right now aren't purists. They're not writing everything from scratch. But when the abstraction leaks, and it always leaks as they know what's underneath. They understand why the database is slow. They know what a cache miss actually costs. They can read a flame graph. They don't just prompt. They think. Vibe coding doesn't create weak engineers. Vibe coding WITHOUT fundamentals creates weak engineers. The ones who treat AI as a layer on top of real understanding? They're shipping 10x faster than both camps. That's not the weak engineer phase. That's the strong engineer phase. We're just early.