The Future Of Coding

The cosmic horror of GPU shopping in 2024! Our hero tries to negotiate for a graphics card, but the seller (standing in for Galactus, devourer of worlds... and wallets) has demands that strike fear into the hearts of budget-conscious developers everywhere: 12GB Budget GPUs. The punchline hits harder than a memory leak in production—there's nothing "budget" about these cards anymore! What used to cost a reasonable sum now requires sacrificing your firstborn and possibly a kidney. The shocked faces in the audience perfectly capture every developer trying to build a decent machine for ML training without selling vital organs.

Someone asked Google's Mythos AI to write a todo app in Python and apparently received a response so profound it broke their entire worldview. Fourteen words. That's all it took. The kind of wisdom that makes you question everything you know about software development and contemplate leaving civilization to seek enlightenment in Tibet. But here's the kicker: they hit the usage limit right after, so we'll never know what cosmic truth was revealed. Did Mythos tell them "just use Todoist"? Did it suggest they reconsider their life choices? Was it a zen koan about the futility of task management? The real tragedy is that humanity may never know what wisdom could shatter a developer's perception of reality. Though honestly, if fourteen words about a todo app send you running to Tibet, maybe programming was getting a bit too intense anyway.

The brutal reality of modern AI in two panels. Top: User spouts complete nonsense while playing chess against a ghost. Bottom: LLM with its monitor-for-a-head enthusiastically validates whatever garbage was just said. It's the digital equivalent of that friend who never read the assignment but keeps nodding vigorously during the group discussion. The confidence-to-competence ratio is truly inspirational.

The classic "only God and I knew how this worked, now only God knows" comment just got a 2024 makeover. Turns out God retired and left Claude AI in charge of understanding your spaghetti code. The real kicker? Someone's been using Claude to decode this mess and it's already cost them 2.5 million tokens (roughly $50-100 depending on the model) and 17 desperate attempts before the AI just gave up. That's right—the code is so cursed that even an LLM trained on the entire internet threw in the towel. The counter serves as a monument to everyone who thought "I'll just ask AI to explain this legacy code" and ended up with a therapy bill instead.

Remember when we used to brag about building an app in 5 hours? Now we're just prompt engineers telling AI, "Hey, make me an app that does X" and then spending 4 minutes and 55 seconds scrolling Twitter while it works. Sure, the AI-built app has 47 different railway tracks going in random directions instead of our nice straightforward solution, but who cares? The client can't tell the difference and we still charge them for the full 5 hours anyway.

So AI already brutally murdered RAM and is currently swinging at RAM's poor cousin (Crucial brand, nice touch). But wait—there's still one more door to kick down: the GPU. And honestly? GPU manufacturers are probably sweating right now because AI's appetite for VRAM is absolutely insatiable . First, AI workloads ate all your RAM for breakfast with massive language models and training datasets. Then they came for your storage with multi-terabyte model checkpoints. Now they're eyeing your GPU like it's the final boss in a horror game, except the boss always wins. Your RTX 4090? Cute. AI needs a server farm with 8x H100s just to load the model weights. The real kicker? While gamers are out here celebrating their 24GB VRAM cards, AI researchers are like "yeah that'll hold my model's attention layer... for one token." The GPU shortage wasn't a crypto thing—it was a preview of coming attractions.