Scrum Masters Are Safe

The massive tower labeled "ALL MODERN DIGITAL INFRASTRUCTURE" vs. the tiny rectangle labeled "AI" pretty much sums up the current state of tech hype. Billions in VC funding for what's essentially a fancy pattern matcher running on infrastructure built over decades. Yet somehow AI is going to replace us all by Tuesday. Sure thing, buddy. I'll start worrying when it can configure a printer without having an existential crisis.

Ah yes, the pinnacle of modern debugging: when your code fails, just ask ChatGPT to fix it. Who needs Stack Overflow anymore when you can just wrap your entire codebase in a try-catch and let AI handle the rest? Next step: AI that writes the bugs for you so the other AI can fix them. The circle of life in silicon.

The classic bull in a china shop, but make it tech. That's Cursor AI—the new code assistant—asking if it can bring its "friend" into your pristine codebase. Every developer who's ever let an AI tool loose on their project knows that feeling of watching it confidently rewrite your carefully crafted code into something that technically works but somehow manages to violate every coding standard you've established over the last decade. Five minutes later, you're frantically running git reset --hard while quietly questioning your life choices.

The second you mention you're learning to code, every relative suddenly transforms into Usain Bolt chasing you down with AI course recommendations. Nothing says "supportive family" like implying your freshly-learned print("Hello World") is already obsolete before you've even figured out how loops work. The programming journey: 10% learning syntax, 90% sprinting away from people telling you that what you're learning is already outdated. Pro tip: develop selective hearing - it's the most valuable skill in your coding toolkit.

Ah, the classic "let's use a sledgehammer to kill a fly" approach. Every tech startup these days thinks they need machine learning to solve problems that could be handled with an if-statement and a cup of coffee. After 15 years in the industry, I've sat through countless pitch meetings where some bright-eyed founder explains how their revolutionary AI will disrupt the sandwich-ordering process. Meanwhile, their actual problem is that they can't figure out how to store user preferences in a database. The real kicker? When they finally implement their neural network to predict topping preferences, it works worse than random chance. But hey, at least they can put "AI-powered" in their pitch deck!

When your neural network sees a GPU and a 3D loss function plot trying to solve what your brain does naturally: "Look what they need to mimic a fraction of our power." Hardware engineers sweating as they build increasingly monstrous GPUs just to calculate gradients, while the human brain sitting there using 20 watts and somehow understanding why that cat meme is funny. The ultimate flex of biological computing.