At what level of deep context engineering does AI output become human-crafted?
I’ve been wrestling with a philosophical and ethical question regarding authorship in the age of LLMs, and I’m curious where the HN community draws the line.
Suppose you spend months deeply researching a niche topic. You make your own discoveries, structure your own insights, and feed all of this tightly curated, highly specific context into an LLM. You essentially build a custom knowledge base and train the model on your exact mental framework.
When you finally want to write a post or comment sharing your findings, you outline your specific thoughts and use that meticulously primed LLM to structure and generate the final prose.
My questions for you:
Is it unethical to post this without an "AI-generated" disclaimer? 2. Whose knowledge is actually being showcased? The LLM is generating the syntax, but the semantics, the insights, and the deep context are 100% human-sourced.
Is this fundamentally different from using a ghostwriter, an editor, or a highly advanced compiler? If I am doing the heavy lifting of context engineering and knowledge discovery, it feels restrictive to say I shouldn't utilize an LLM to structure the final output. Yet, the internet still largely views any AI-generated text as inherently "un-human" or low-effort.
Where does human insight end and AI generation begin? If the core ideas are yours, is the medium of the text really the message?
No comments yet.