Are you still speaking from the perspective of the people who use LLMs to quickly turn around their half-baked ideas, or from the perspective of readers who will be deluged more and more with LLM-baked content?
Good catch, the perspective shifted in the paragraph. The question was meant to be spoken from the perspective of deluged readers. Edited for clarity.
What do you mean by the internet—even before someone actually reads a post or article, a whole host of factors determine if it even gets a chance before the first paragraph: what personal or contextual relevance? Hyperbole (“10 best pictures of Fawns, you won’t believe no. 4”)? Ragebait?
Agreed, there is a host of factors that determine if something gets a chance at being read independent of the meaningfulness of the text itself. What I am trying to get at is that among content that does get a chance, fluency used to be a weak signal that the person who wrote it probably at least spent time trying to understand or write something meaningful, and so it may be worth a read. When everything looks coherent upon first glance due to LLMs polishing surface-level coherence, that signal gets covered in noise. So people spend less time engaging with unknown sources online, as it’s simply too expensive to evaluate all the content, and they resort to trust networks rather than independent discovery.
One place we may already be seeing this is cold email. Historically, receiving a personalized email from a stranger was weak evidence that another human had spent nontrivial effort thinking specifically about you. Since personalization was costly, it functioned as a signal. LLMs partially collapse this. Once plausible personalization can be generated at near-zero marginal cost, “I saw your recent work on X” no longer strongly implies genuine attention. Average cold email reply rates have dropped from around 8.5% in 2019 to 3.43% in 2026 (per the Instantly 2026 benchmark report), with industry analysts directly attributing part of the decline to low-effort AI-generated outreach. As the cost of generating plausible communication approaches zero, recipients adapt by allocating more attention through existing trust networks (friends, colleagues, reputation systems, established communities), and discoverability increasingly flows through connection graphs rather than unsolicited communication.
On the flip side. Kant is notoriously difficult to interpret, Wes Cecil says it is easier to read Kant in English translations than his native German. Will such difficulty of prose become the new sign of intentionality?
Difficulty is probably part of it, though I’m not sure exactly what the new signals will look like. If I had to guess, it would be anything structurally farther from what an LLM would output: relevant comic strips between paragraphs, forgoing em dashes, idiosyncratic structure. For cold emails, it may mean bypassing email entirely and showing up at a professor’s office hours without prior introduction.
I do suspect that genuinely difficult writing (actual hardness, not the appearance of it) will increasingly signal intentionality.
Good catch, the perspective shifted in the paragraph. The question was meant to be spoken from the perspective of deluged readers. Edited for clarity.
Agreed, there is a host of factors that determine if something gets a chance at being read independent of the meaningfulness of the text itself. What I am trying to get at is that among content that does get a chance, fluency used to be a weak signal that the person who wrote it probably at least spent time trying to understand or write something meaningful, and so it may be worth a read. When everything looks coherent upon first glance due to LLMs polishing surface-level coherence, that signal gets covered in noise. So people spend less time engaging with unknown sources online, as it’s simply too expensive to evaluate all the content, and they resort to trust networks rather than independent discovery.
One place we may already be seeing this is cold email. Historically, receiving a personalized email from a stranger was weak evidence that another human had spent nontrivial effort thinking specifically about you. Since personalization was costly, it functioned as a signal. LLMs partially collapse this. Once plausible personalization can be generated at near-zero marginal cost, “I saw your recent work on X” no longer strongly implies genuine attention. Average cold email reply rates have dropped from around 8.5% in 2019 to 3.43% in 2026 (per the Instantly 2026 benchmark report), with industry analysts directly attributing part of the decline to low-effort AI-generated outreach. As the cost of generating plausible communication approaches zero, recipients adapt by allocating more attention through existing trust networks (friends, colleagues, reputation systems, established communities), and discoverability increasingly flows through connection graphs rather than unsolicited communication.
Difficulty is probably part of it, though I’m not sure exactly what the new signals will look like. If I had to guess, it would be anything structurally farther from what an LLM would output: relevant comic strips between paragraphs, forgoing em dashes, idiosyncratic structure. For cold emails, it may mean bypassing email entirely and showing up at a professor’s office hours without prior introduction.
I do suspect that genuinely difficult writing (actual hardness, not the appearance of it) will increasingly signal intentionality.