Original work is now an endangered species (www.trevorlasn.com)

The author observes a growing homogenization online driven by large language models and low-friction web tooling: newsfeeds, blogs, and Product Hunt feeds are flooded with LLM-generated articles and “vibe-coded” apps that all read, look, and behave the same. Headlines recycle the same tropes, articles merely rephrase existing knowledge without new insight, and many startup apps are just CRUD templates dressed in the same Tailwind-style aesthetics and component libraries. Functional but forgettable, these outputs reflect a collapse in the cost and time needed to produce content and products—prompt an LLM and ship in minutes instead of researching, designing, and iterating for weeks. For the AI/ML community this matters because it shifts incentives from idea generation and novel engineering toward mass-producing “good enough” artifacts, diluting signal and making discovery and differentiation harder. Technically, reliance on pretrained LLMs and boilerplate stacks accelerates commodification: repeated training-data patterns are repackaged rather than expanded upon, and product value becomes UX polish over unique functionality. The piece implicitly calls for reorienting tools as amplifiers of human originality—better provenance, curation, specialized data, and deliberate design practices—so AI augments creativity instead of replacing the act of having ideas.