12 Months Ago..

Getting that baby started on backpropagation before they can even propagate backward out of the room. Gotta secure that AI engineering job by age 3. The kid's already debugging neural network architectures while the rest of us are still trying to center a div. In 20 years they'll be creating sentient AI while we're still arguing about tabs vs spaces.

OH. MY. GOD. The absolute CARNAGE of career trajectories! 2025 is coming for data scientists with a VENGEANCE! 💀 While AI engineers strut around looking like they just walked off a Silicon Valley fashion runway, data scientists are transforming into depressed philosophers drowning their sorrows at the bar! The AUDACITY of this career market! Remember when everyone and their mother was rushing to become a data scientist? "It's the sexiest job of the 21st century!" they screamed. Well, honey, the AI revolution waits for NO ONE. Those fancy regression models aren't looking so hot now that ChatGPT can do your entire job while also writing poetry about it!

Boss walks in with their revolutionary "AI-first" strategy that's definitely going to solve all our problems. Fast forward two sprints and the bug count has doubled. Shocking. Absolutely shocking. Nobody could have predicted that slapping AI onto everything without proper testing would create more issues than it solved. But sure, let's keep pretending that replacing actual engineering with buzzwords is innovation. Meanwhile, the devs are just nodding along, internally calculating how many extra hours of debugging await them. The poker face is strong with this one—probably already updated their resume during the meeting.

The AI gold rush created a beautiful paradox: companies went all-in on AI tooling, hired developers based on "vibes" instead of actual skills, watched their codebase turn into spaghetti junction, then suddenly realized nobody left can actually maintain the mess. Now they're desperately hunting for devs who can, you know, actually code – but surprise, those folks are rare because the number who know what they're doing keeps shrinking while demand skyrockets. It's the tech industry eating its own tail. You can't Copilot your way out of architectural decisions, and ChatGPT won't refactor your 10,000-line God class. Turns out fundamentals still matter. Who knew?

Classic box-and-stick trap setup, but instead of cheese for a mouse, it's RAM sticks for the OpenAI CEO. Because when you're training GPT models that require ungodly amounts of compute and memory, you develop a Pavlovian response to hardware. The joke here is that Sam Altman's AI empire runs on so much computational power that he'd literally crawl under a cardboard box for some extra RAM. Those training runs aren't gonna optimize themselves, and when you're burning through millions in compute costs daily, a few sticks of DDR4 lying on the ground start looking pretty tempting. It's like leaving a trail of GPUs leading into your garage. He can't help himself – the models must grow larger.

OpenAI just declared the AI race is "over" if they can't train models on copyrighted content without permission. You know, because apparently innovation dies the moment you have to actually license the data you're using. The bottom panel really nails it—10/10 car thieves would also agree that laws against stealing are terrible for business. Same energy, different industry. It's the corporate equivalent of "Your Honor, if I can't copy my neighbor's homework, how am I supposed to pass the class?" Sure, training AI models on massive datasets is expensive and complicated, but so is respecting intellectual property. Wild concept, I know.