LinkedIn has become saturated with performative productivity that prioritizes appearance over substance, particularly in the realm of computer vision projects. Users routinely share videos of themselves waving their hands to trigger basic object tracking, or demonstrating pothole detection systems that serve no practical purpose beyond posting. As the author describes, 'every time I open LinkedIn, I get hit by these Computer Vision Projects of some guy waving his hand around, and it tracks them,' noting these projects are 'not even useful' and 'not even something anyone would like using.' This phenomenon reflects a broader culture where 'normal human text goes to die and can only be kept alive by an LLM like a radiation protection suit.' The term 'larpmaxxing' captures this Live Action Role Playing of productivity, where users simulate skilled work primarily for visibility rather than genuine innovation or utility.
The article describes how users share pothole detection systems that serve no practical purpose beyond posting, illustrating performative computer vision content.
The article notes that users frequently post videos of themselves waving hands to trigger basic object tracking, which requires little skill but appears impressive.
To quantify how trivial such content creation has become, the author built a 'YOLO Post Detector' specifically designed to identify LinkedIn posts boasting about YOLO (You Only Look Once) object detection projects. The process required minimal expertise: collecting 200 screenshots from their LinkedIn feed using an automated script, annotating them in Roboflow by drawing boxes around target elements (taking about 20 minutes), and training a YOLOv8n model for 50 epochs at 320-pixel image size. Despite using what they described as a 'potato pc,' the entire endeavor—from learning the tools to deploying a working detector—took only 90 minutes. The resulting script successfully identified posts with phrases like '🚀 Excited to announce I made a YOLO project,' proving how little effort is needed to produce content that appears technically impressive on the platform.
This ease of creation exposes LinkedIn's fundamental misalignment of incentives: the platform rewards looking interesting rather than demonstrable skill growth. As the author concludes, 'Nothing on that site rewards you for getting better. It’s a platform built around selling yourself for a job, so what survives isn’t skill; it’s looking interesting.' Users repeatedly share variations of the same superficial projects—'the same guy detecting potholes over and over and over with zero signs of improvement'—because commenting critically risks damaging one's professional profile. Consequently, LinkedIn has become a space where performative displays of AI and computer vision fluency thrive not because they represent meaningful expertise, but because they generate engagement in an environment that values optics over actual competence.