From data-science snake oil to blockchain buzzwords, the AI gold rush looks eerily familiar. Are we buying the same dream in a shinier box?
Every decade has its magic word. Yesterday it was blockchain, today it’s AGI. The headlines scream breakthrough, the VCs open their wallets, and the rest of us wonder if we’re witnessing history or déjà vu. Let’s peel back the marketing stickers and ask the uncomfortable questions.
The Déjà Vu Pattern
Remember when data science was the new oil? Suddenly every spreadsheet jockey became a guru. Then came crypto, the new internet, followed by NFTs, the new art. Each wave followed the same script: a catchy acronym, a sky-high promise, and a flood of overnight experts. AI hype fits the pattern like a glove. The buzzwords change, but the playbook doesn’t. Investors chase the next unicorn, founders polish the same pitch deck with fresh fonts, and the media prints breathless profiles. The only real innovation seems to be in the PowerPoint transitions.
The Saturation Point
Large language models are starting to feel like late-night infomercials. The latest demos look slick, yet the underlying leap feels incremental. We get smoother animations, snappier replies, and a fresh coat of UX paint. Meanwhile, the core architecture hasn’t budged. Engineers whisper that scaling laws are flattening. Benchmark gains shrink quarter by quarter. The industry keeps cranking the hype dial louder to drown out the plateau. When the breakthroughs slow, the storytelling speeds up.
Job Displacement Myths
Headlines warn that AI will replace everyone from coders to poets. Reality is messier. The roles most at risk are the ones already teetering on redundancy: low-stakes content mills, cookie-cutter code snippets, and academic busywork. Core business challenges still demand human grit. Negotiating a supply-chain crisis, calming an angry customer, or inventing a new product category requires context, empathy, and risk tolerance that code can’t fake. AI hype often confuses automation with augmentation. The former replaces, the latter empowers. Guess which one actually moves the needle?
What Happens When the Bubble Pops
History offers a sobering preview. When the dot-com bubble burst, pets-dot-com became a punchline, but Amazon quietly built the future. The same sorting is coming for AI. Overhyped startups will crater, headlines will scream scandal, and the public will swear off tech again. Yet beneath the rubble, real builders will keep shipping. They won’t chase vanity metrics or viral demos. They’ll focus on boring, profitable problems like fraud detection, supply-chain optimization, and personalized medicine. The question isn’t whether AI will matter, but which version survives the hype cycle. Place your bets accordingly.
