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Why Modern Programming Languages Are Becoming Unsafe Again: The Hidden Costs of Abstraction in Rust, Go, Python, and JavaScript

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  Modern software development went through several cycles of escaping complexity only to recreate it in a different form. In the early days, low level languages like C gave developers full control over memory, layout, and performance, but this freedom came with high risk. Memory corruption, data races, buffer overflows, and undefined behavior were common. Later, languages like Java and C# pushed developers toward safer abstractions. Then Python and JavaScript made the runtime even more forgiving. Today, Rust and Go promise a return to predictability with strict memory models, type safety, and clear concurrency rules. Yet something interesting is happening beneath the surface. Even in languages designed for safety and simplicity, new forms of unpredictability, performance traps, and abstraction-driven risks have emerged. This does not mean these languages are unsafe in the traditional sense, but the hidden costs of modern abstractions create behaviors that developers cannot always r...
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Understanding Function References in Rust: A Deep Dive into Closures, Fn Traits, and Function Pointers

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  In Rust, functions are not just lines of executable code. They are values, and like any value, they can be passed around, stored, and executed later. This is possible because Rust treats functions and closures as first-class citizens. Understanding how function references work is critical for writing idiomatic, efficient, and safe Rust code, especially when designing APIs, higher-order functions, and concurrent systems. In this post, we will explore all types of function references—raw function pointers, closures, and trait-based references ( Fn , FnMut , FnOnce )—explain why they exist, and examine when to use each. 1. Raw Function Pointers ( fn ) The simplest kind of function reference in Rust is the plain function pointer type, written as fn . Unlike closures, fn does not capture any external environment. It simply points to a function with a known signature. Example: fn greet(name: &str) { println!("Hello, {}!", name); } fn call_function(f: fn(&str))...
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Why Indirection Is the Price of Polymorphism, With Assembly You Can Read

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  Polymorphism lets you call methods through an interface without knowing the concrete type at compile time. The CPU and the ABI do not understand interfaces, traits, or virtuals. They only understand bytes, fixed register widths, and stack slots. That mismatch is the root cause of why runtime polymorphism uses indirection. In this extended version I will show concrete assembly flavored examples so you can see exactly where size knowledge matters, how vtables and fat pointers are used, and what gets passed in registers or on the stack. I will use x86-64 System V ABI conventions where practical. Exact assembly will vary by compiler and flags, but the patterns are stable. The goal is to make the invisible visible. A tiny ABI checklist before we start The ABI decides how arguments are passed and where return values land. On x86-64 System V: Integer or pointer arguments are passed in RDI, RSI, RDX, RCX, R8, R9, then the stack. Floating arguments use XMM0..XMM7. The caller align...
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The Next Level AI Language: Beyond Prompts, Toward Precision and Stability

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  Artificial intelligence today feels both miraculous and maddening. It can write essays, generate code, and simulate human conversation with astonishing fluency—but the moment you start relying on it for real work, cracks appear. The same model that solves your problem one day may misinterpret your instructions the next. A subtle change in phrasing can turn a correct response into a hallucination. For all its intelligence, modern AI is unstable, unpredictable, and fundamentally unaccountable. This is not just an inconvenience. It’s a structural flaw that limits AI’s role in critical systems. Banks, medical institutions, aerospace companies, and governments cannot deploy an AI that “usually” gives the right answer. They need determinism, reproducibility, and verifiable logic. The current generation of LLMs—text-predictive, stochastic, and opaque—cannot provide that. The next level of AI will require not just a better model, but a new kind of language designed to control it. The...
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Understanding Cell and RefCell in Rust: Interior Mutability for Real Work

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  Rust’s ownership and borrowing rules keep your programs safe by pushing many errors to compile time. Sometimes, though, code needs to mutate internal state even when it is behind a shared reference. Think of caches, lazy initialization, graph structures with shared ownership, and objects that must expose a read only API while quietly tracking metrics inside. The standard tool for this is interior mutability. In practice, two core types power this pattern in single threaded code: Cell and RefCell. This post explains what they are, how they differ, when to use each one, and how to apply them in realistic examples. We will go step by step, show common pitfalls, and close with a quick comparison to other options like Mutex, RwLock, and atomic types. What interior mutability means Normally, if you have &T you cannot change T. Only &mut T permits mutation. Interior mutability flips this by allowing controlled mutation through a shared reference, while still preserving high l...
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Mastering Prompt Engineering: How to Think Like an AI and Write Prompts That Never Fail

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Introduction: Why Prompt Engineering Is a Moving Target   Prompt engineering itself doesn’t evolve rapidly - but the models it depends on change all the time. Every new generation of large language models comes with new reasoning layers, expanded context windows, modified decoding defaults, and new forms of safety alignment. These shifts alter how models interpret, prioritize, and execute instructions. A prompt that produces clean, reliable output one week might start producing verbose or inconsistent results after a silent update. The role of a prompt engineer is therefore not just to write good prompts, but to detect, analyze, and adapt to these changes. Successful practitioners treat prompt design as an ongoing process of experimentation rather than a fixed discipline. Understanding the Core Ideas Behind Prompt Design At its core, prompt engineering is about communication - bridging human intent and machine interpretation. A good prompt does three things clearly: defines who th...
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