A framework for technical writing in the age of LLMs (thedataquarry.com)

A recent blog post presents a new framework for technical writing tailored for the evolving landscape dominated by large language models (LLMs). The author reflects on his success in engaging a diverse audience with his writing and emphasizes the importance of authenticity and depth in content creation. He argues that while LLMs excel at generating text, they often lack the nuanced understanding and emotional investment that human writers bring to their work. The framework divides the writing process into three layers: the outline (structure and vision), ideas (core themes), and details (specific examples and data). This approach encourages writers to first clarify their ideas, develop an organized outline, and only then add rich details, ensuring the final product resonates more deeply with readers. This perspective is significant for the AI/ML community, highlighting the limitations of current automated writing tools and reiterating the value of human creativity and judgment in producing meaningful content. As AI-generated texts often feel generic and lack genuine insight, the framework aims to elevate human writing amidst a surge of low-quality, LLM output. By advocating for a structured approach that prioritizes authentic engagement and thoroughness, the author hopes to inspire more compelling long-form writing in the future, countering the trend of superficial content prevalent in online platforms.