What Could Go Wrong

The iceberg metaphor is painfully accurate. After 15 years in the industry, I can confirm that typing out the actual code is the easy 10% that everyone sees. The other 90%? That's the soul-crushing existential void of figuring out what to code in the first place. AI can generate syntax all day long, but good luck getting it to understand the business logic buried in 47 conflicting Slack messages, 3 outdated Jira tickets, and that one crucial requirement your PM mentioned offhandedly during a coffee break last Tuesday.

Congratulations, you've just reinvented rubber duck debugging but with extra steps. Turns out, articulating your problem clearly enough for an AI is the same mental process that makes you realize the solution yourself. The real ChatGPT was the brain cells we activated along the way. The irony is delicious - AI researchers discovering that humans think better when forced to explain things clearly. Next breakthrough: water is wet.

The great AI alignment crisis, solved with a simple debugger. While AI researchers are building complex neural networks and transformer models to ensure AI doesn't go rogue, some smartass developer suggests just putting a breakpoint in the code and checking variable values—as if Skynet could be tamed with a console.log() . It's like suggesting we fix climate change by putting the Earth in rice. The beautiful naivety of thinking you can debug superintelligence the same way you'd fix your weekend React project.

The modern tech company hierarchy in one perfect image. Junior dev happily letting AI do the heavy lifting while the senior dev is stuck reviewing 500 lines of algorithmic word vomit. Meanwhile, the project manager is just pointing a gun at everyone's back screaming about deadlines. And there sits the CEO, blissfully unaware in his ivory pew, dreaming about firing the entire dev team because ChatGPT told him it could do their jobs. Ten years of experience just to babysit robot output – exactly what we all went to college for!

The irony is so thick you could debug it with a breakpoint. ChatGPT, an AI itself, somehow "lost its job to AI" — which is basically like saying water got replaced by H₂O. It's the digital equivalent of firing yourself and then complaining about it on your LinkedIn. Next up: Google Search engine shocked to discover it's been replaced by "a search engine." The self-awareness circuit must have crashed spectacularly somewhere between training epochs.

The public thinks AI is some mystical brain-to-brain knowledge transfer. Amateur programmers imagine it's a beautiful network of interconnected nodes making intelligent decisions. Meanwhile, actual developers know it's just a mountain of nested if-statements descending into madness. That bottom panel hits different after you've spent 15 years in the industry. Fancy marketing terms like "neural networks" and "deep learning" sound impressive until you peek behind the curtain and find what's essentially glorified pattern matching with extra steps. The "10,000 if-statements" comment is the chef's kiss of cynical developer truth. We're not creating consciousness—we're just building increasingly complex decision trees and hoping nobody notices.