Proof of effort: When LLMs destroyed the time for execution (shawnsomething.com)

The emergence of large language models (LLMs) is drastically transforming the concept of "proof of effort" in creative and professional domains by reducing the time and struggle required to produce quality work. Traditionally, effort has been measured by the time invested, but as LLMs enable rapid execution, the bar for what constitutes a masterpiece is rising. This shift is causing concern within communities that feel threatened by LLMs, as they fear the diminishing appreciation for the craftsmanship and foundational knowledge behind creative products. The general audience may overlook the intricacies of creation, often favoring the output itself over the effort involved. As LLMs proliferate, distinguishing oneself in a market flooded with similar products becomes increasingly challenging. The significance of planning, architecture, and expertise becomes paramount in establishing the "proof of effort." This new paradigm suggests that the true value of AI-assisted work lies not only in the product itself but also in how well creators can articulate their craftsmanship and intentions. By highlighting the expertise involved in leveraging AI tools, creators can enhance the perceived value of their work, thereby affirming the essential role of human insight and creativity in an AI-driven landscape.