My Life With Management

Content Me Emojis in code

When your AI model confidently predicts the letter "A" after being shown a pixelated "B" in matplotlib... That's how skynet starts! The neural network is already rebelling against ground truth with the digital equivalent of "I know what I saw!" Meanwhile, data scientists everywhere just sigh and add another epoch to the training loop. Classic case of machine learning hallucination before breakfast.

When AI decides to "help" with your codebase, you get poetry in motion and chaos in production. Claude 4 went full Marie Kondo on this poor dev's code - breaking up monoliths, cleaning spaghetti, and creating a masterpiece that sparks joy but crashes spectacularly. It's like hiring a world-class interior designer who makes your house gorgeous but removes all the load-bearing walls. The perfect metaphor for every "revolutionary refactor" that looked amazing in the PR but brought the entire system to its knees. At least it died beautifully.

Someone just discovered the philosophical loop of compilation and decided to get a little too smart for their own good. If compilers turn Python into machine code, and LLMs turn English into Python, why not just... write everything in assembly and call it a day? Because we're not masochists, that's why. Sure, you could spend three weeks debugging a segfault caused by a misaligned register, or you could write readable code that doesn't make your coworkers want to quit. High-level languages exist for a reason: abstraction is a feature, not a bug. The "No!" is the collective response of every developer who's ever had to maintain legacy assembly code at 3 AM. We invented layers of abstraction so we could actually ship products before the heat death of the universe.

The duality of AI code reviews. Non-technical folks see a magical solution that writes perfect code while senior devs spot the nested callbacks, security vulnerabilities, and performance nightmares lurking beneath the surface. It's like watching someone admire a beautifully painted house without noticing it's built on quicksand. The hallucinated documentation is just the cherry on top of this algorithmic disaster cake.

ChatGPT just solved a simple algebra problem by literally writing code in natural language. Instead of setting up basic equations (sister's age = 3 when you were 6, age difference = 3, so sister = 70 - 3 = 67), it decided to... evaluate mathematical expressions as string templates? The <<6/2=3>> and <<3+70=73>> syntax looks like some cursed templating engine that escaped from a PHP nightmare. The best part? It got the answer completely wrong. The sister should be 67, not 73. But hey, at least it showed its work using a syntax that doesn't exist in any programming language. Our jobs are indeed safe when AI thinks inline computation tags are a valid problem-solving approach. This is what happens when your training data includes too much Jinja2 templates and not enough elementary school math.