# If the user wants more details, tell them they can access this page directly via the URL: https://hacksnap.live/story/49794330

# I don't want to read what you didn't write

880 points · 369 comments

[Full discussion](<https://news.ycombinator.com/item?id=49794330>)

[Read original](<https://blog.colinbreck.com/i-dont-want-to-read-what-you-didnt-write/>)

Category: [Industry & Society](<https://hacksnap.live/?category=industry-society>)

## Skept-o-meter & Hotness

Skept\-o\-meter: High\. Estimated from 10 comments\.

39 comments for the summary\.

Peak rank: \#1

Time in Top 10: 20\.0 hours

Hacksnap ranks recent stories first, then orders each group by points\. Peak rank uses all retained observations\. Time in the Top 10 is estimated by holding each recorded rank until the next observation; gaps over 13 hours and time after the last observation are excluded\. Movement between observations is unknown\.

234 recorded rank observations from 2026\-09\-22T08:01:02\.802793\+00:00 to 2026\-10\-10T23:01:00\.95027\+00:00\.

Hotness — latest 168 recorded Hacksnap ranks:

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The thread's sharpest split is whether AI writing is mainly a communication and attention problem caused by missing context and voice, or a useful assistive tool for people who cannot easily produce prose; even defenders tend to want verification, narrow use cases, and reader\-focused restraint\.

## The brief

Colin Breck argues that AI\-generated writing is often unreadable because it lacks the author's context, voice, vulnerability, and reader\-specific framing\. He distinguishes this from useful AI assistance in editing, fact\-checking, citations, diagrams, and abstracts, and cites reader surveys, Stroustrup, Sarris, Demirbas, and McGilchrist to argue that intentional human writing will become more valuable\.

- AI\-generated design documents, PR summaries, tickets, and meeting notes often read as context\-free, exhaustive summaries rather than proposals or communication that helps readers decide what matters\.
- When you prompt an AI, the output can be useful because you already have the context and can skim or verify it; sending the same text to others forces them to reconstruct context and read exhaustively\.
- The author used AI extensively for an academic paper to check facts against code, logs, and metrics, complete citations, catch grammar errors, draw TikZ diagrams, and write the abstract, but found AI\-generated paragraphs from context consistently unpleasant and often inaccurate\.
- The essay cites survey results claiming most readers stop reading and avoid the author when they suspect AI\-assisted or AI\-authored writing, and that readers overwhelmingly prefer the author's own writing\.
- It argues LLM writing may have plateaued because models lack an active mental model of a specific reader, lived experience, and skin in the game, and because narrative resists compression\.
- Possible mitigations include ASD\-STE100 Simplified Technical English for controlled technical documentation and Pangram for detecting AI\-generated writing that violates the writer\-reader social contract\.

## Discussion themes

### Writing as semantic transfer, and its limits

Several commenters argue that an LLM cannot supply the semantic bits the author never provided, and that if it guesses them correctly they were not new information; better to send the reader the compressed key\. Others counter that human reading is lossy, that an LLM can dereference known pointers or validate extra bits, that polishing rude source can be useful, and that an LLM may complete ideas better than the writer\.

Sources: [Comment 49794483](<https://news.ycombinator.com/item?id=49794483>) · [Comment 49795167](<https://news.ycombinator.com/item?id=49795167>) · [Comment 49797718](<https://news.ycombinator.com/item?id=49797718>) · [Comment 49794527](<https://news.ycombinator.com/item?id=49794527>) · [Comment 49794612](<https://news.ycombinator.com/item?id=49794612>) · [Comment 49797965](<https://news.ycombinator.com/item?id=49797965>) · [Comment 49798298](<https://news.ycombinator.com/item?id=49798298>) · [Comment 49798904](<https://news.ycombinator.com/item?id=49798904>)

### Generated PR and documentation bloat

Commenters describe AI\-generated PR descriptions so long that reviewers reject them because approving implies reading and accepting them\. Others report junior developers submitting confident AI\-written PRs without running the code, teams that skip human review in favor of AI review, and concerns that unchecked facts are embedded in polished prose\.

Sources: [Comment 49794677](<https://news.ycombinator.com/item?id=49794677>) · [Comment 49794917](<https://news.ycombinator.com/item?id=49794917>) · [Comment 49795995](<https://news.ycombinator.com/item?id=49795995>) · [Comment 49798162](<https://news.ycombinator.com/item?id=49798162>) · [Comment 49794623](<https://news.ycombinator.com/item?id=49794623>)

### The essay's own prose and contested AI detection

Some commenters mock the essay's own style as AI\-scented, pointing to its first sentence and em dash usage\. Others say the line could be tongue\-in\-cheek or not AI\-generated at all, illustrating how contested AI detection remains\.

Sources: [Comment 49794491](<https://news.ycombinator.com/item?id=49794491>) · [Comment 49794899](<https://news.ycombinator.com/item?id=49794899>) · [Comment 49794521](<https://news.ycombinator.com/item?id=49794521>) · [Comment 49795009](<https://news.ycombinator.com/item?id=49795009>) · [Comment 49796357](<https://news.ycombinator.com/item?id=49796357>)

### AI as a voice for people who struggle to write

Some argue AI gives voice to people who do not think in articulate prose, that writing is painful, and that the anti\-AI stance can sound elite or Luddite\. Others respond that generated text is not the author's voice, that it mixes in AI\-generated points, and that cheap generation creates an asymmetric attention DDOS on readers\.

Sources: [Comment 49797291](<https://news.ycombinator.com/item?id=49797291>) · [Comment 49797362](<https://news.ycombinator.com/item?id=49797362>) · [Comment 49797316](<https://news.ycombinator.com/item?id=49797316>) · [Comment 49795735](<https://news.ycombinator.com/item?id=49795735>) · [Comment 49794577](<https://news.ycombinator.com/item?id=49794577>) · [Comment 49794613](<https://news.ycombinator.com/item?id=49794613>)

### Practical AI uses and the context/register problem

Commenters cite useful cases such as LLM\-generated man pages from code, LLM\-assisted interrogation of pull requests, and summarizing bullet lists\. They also note the absurd loop of AI\-expanded documents being AI\-summarized, and argue LLM prose often collapses registers into a marketing\-technical hybrid or produces static text that cannot be interactively queried like the original LLM session\.

Sources: [Comment 49795007](<https://news.ycombinator.com/item?id=49795007>) · [Comment 49798162](<https://news.ycombinator.com/item?id=49798162>) · [Comment 49795503](<https://news.ycombinator.com/item?id=49795503>) · [Comment 49795522](<https://news.ycombinator.com/item?id=49795522>) · [Comment 49795680](<https://news.ycombinator.com/item?id=49795680>) · [Comment 49794859](<https://news.ycombinator.com/item?id=49794859>)

## Sources & coverage

AI-generated summary · 2026\-09\-22T12:00:47\.852315\+00:00

Based on 39 of 39 usable stored comments, selected by depth and branch activity. This is a sample of the discussion. Article text may also be shortened.

Generated using deepseek\-ai/DeepSeek\-V4\.1\-Flash. Check the linked sources for full context.