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Boosted by baldur@toot.cafe ("Baldur Bjarnason"):
oatmeal@kolektiva.social wrote:
The AI Great Leap Forward
Similar to the #Chinese Great Leap Forward's inflated grain production reports, companies are fabricating or exaggerating #AI adoption and productivity gains to please leadership, leading to increased investment based on made up numbers. The focus seem to have shifted from genuine AI development to "demoware" – impressive-looking prototypes and interfaces with little underlying validation, data infrastructure, or maintenance plans, creating future tech debt.
[…] Entire departments are stitching together n8n workflows and calling it AI — dozens of automated chains firing prompts into models, zero evaluation on any of them. These tools are merchants of complexity: they sell visual simplicity while generating spaghetti underneath. A drag-and-drop canvas makes it trivially easy to chain ten LLM calls together and impossibly hard to debug why the eighth one hallucinates on Tuesdays. The people building these workflows have never designed an evaluation pipeline, never measured model drift, never A/B tested a prompt. They don’t need to — the canvas looks clean, the arrows point forward, the green checkmarks fire. The complexity isn’t avoided. It’s hidden behind a GUI where nobody with ML expertise will ever look.
https://leehanchung.github.io/blogs/2026/04/05/the-ai-great-leap-forward/