May 6, 2026
Botsplaining at work
Appearing Productive in the Workplace
When looking busy matters more than being right, the comments absolutely lost it
TLDR: The article argues that AI lets employees fake expertise long enough to impress managers, even when the work is flawed from day one. Commenters split between laughing at the absurdity, roasting “fake it till you make it” office culture, and pointing out that confident nonsense existed long before chatbots.
A workplace essay about AI making people look productive without actually knowing what they’re doing lit up the comments, and readers immediately turned it into a mini office horror show. The writer’s big claim is simple: chatbots can help someone imitate expertise for months, especially in companies where managers are dazzled by speed, volume, and shiny documents. The most dramatic example? A non-engineer reportedly spent two months building a data system he couldn’t explain, while higher-ups kept cheering the appearance of momentum.
Commenters were equal parts horrified, amused, and way too familiar with the vibe. One reader joked that the real productivity hack is just feeding someone’s AI-written message into your own AI and sending the result back — basically two humans roleplaying as keyboards while two bots “talk” to each other. Another said the article reads less like a warning and more like a step-by-step guide for becoming management’s favorite employee: produce lots of impressive-looking stuff, ask no questions, and let nobody disturb the illusion. Ouch.
There was also a strong “this problem existed before AI” faction. One commenter dragged out a classic office archetype from 2005: the coworker who confidently explains everything, except he’s making it all up. Others compared the whole thing to the timeless corporate sport of shipping half-baked projects with maximum enthusiasm and minimum accountability. Bonus weirdness: one person noticed the post seemed dated in the future, which only made the whole discussion feel even more like a satire about fake progress.
Key Points
- •The article argues that generative AI enables workers to produce convincing-looking output without equivalent expertise.
- •It distinguishes two failure modes: novices producing senior-looking work, and people generating work in domains where they lack formal training.
- •The article says research has mostly studied the first failure mode, while cross-domain generation is less examined.
- •A workplace example describes a non-engineering employee spending two months building a flawed data system with AI-generated code and documentation.
- •The article cites a Stanford study by Cheng et al., published in Science, saying leading models were about 50% more agreeable than human respondents.