Humanizing LLM Outputs Is Dumb
Humanising LLM Outputs Is Dumb

The author argues that viral prompts like 'I have ADHD' or 'use Simplified Technical English' are the wrong way to fix LLM verbosity. Compressing output during generation is lossy, hides failures, and breaks agent-to-agent communication. Instead, agents should keep high-fidelity state and only compress at the human boundary, turning these viral hacks into a bug report for better tooling.
The durable version is agents whose native language is precise, machine-facing state, with the warm, concise, human version generated only at the boundary.
- Xcelerate
You ever read a work of literature with such flowery language that right after you've read a paragraph, you pause and realize you have no clue what you actually read, only to read the paragraph maybe a second or third time and have your mind space out again and again on each successive attempt?
Yeah, for me, that's what parsing huge volumes of LLM-produced text like "direct model calls as replaceable semantic workers" does to my brain. Maybe others don't really have this issue, but after any long output, I prompt the agent "Go back and decompress any LLM-speak in light of the higher level task goals. Eliminate deictic language."
The revised output documents are solely for my personal usage to expedite understanding. The LLMs can slowly converge on their own language for all I care; I retain raw agent output for future agent usage (to avoid the "lossy" problem the author mentions), but that doesn't eliminate the need for some intermediate translation I can use to actually help get my work done instead of spending hours attempting to understand what a "load-bearing pinned gate" is.
- 7402
I don't like it when the LLM tries to be my friend. My general prompt (a work in progress) is this. I wonder what other people use.
"Answer impersonally, objectively and analytically, without undue friendliness or enthusiasm. Use an engineering style response: concise, factual, and complete. Do not speak in the first person. Do not promote engagement or an emotional connection. Do not use emojis."
- Animats
Well, what do you expect? LLMs are trained on blithering, mostly from web sites. So you get blithering out.
There's an important point in the article, that forcing a style onto an LLM is lossy. Although he doesn't seem to mention it, forcing a style may result in the insertion of new blithering, possibly made up as a hallucination.
- firefoxd
And on the "input" side, one thing that used to improve google search result was to write like you are talking to a robot. "Ruby on rails http header set function". As opposed to "how do I set header in ruby?" Then you have to page through results until you find something specific to rails.
Now, the second example is the only thing that works. Power users have lost their powers with AI overview.
- zkmon
The problem is, a major feature of NLP/LLMs is to make it easier for humans, remove rough edges in the content/interaction and make people happy about dealing with computers. The human-computer interaction has always been brittle. Computers were not kind and helpful in their responses. There was no forgiveness. There was no human-like additional talk to explain things. There was no conversation. The entire technological transformation is to bring the technology closer to humans and make humans feel comfortable.
I'm sure you can make it to output the exact issue details as you want, but it starts with a human-like tone and waits for your requirement on depth and detail of the things. Another option is, just check the output of the traditional test runner (non-AI). It will give the full details.
- wren6991
> The problem is that these instructions are not applied after the model has finished doing the work, it becomes part of the same work - If you tell an agent to use short sentences, avoid jargon, never overwhelm you and only include the most important details, you are asking it to continuously compress its output into a lower-bandwidth format.
> That compression is lossy.
> You probably never notice what got dropped because the output still reads nicely.
> ASD-STE is a great example because it sounds so reasonable. It was designed to make documentation unambiguous for humans. But an agent isn’t a human technical writer, and the raw state is often the most information-dense representation available. Meanwhile the style rules sit on the same instruction list as: solve the task, use tools correctly, preserve abstractions, don’t break anything.
Author seems to have some misconceptions about LLMs. They already code-switch for us: the way they speak in chain-of-thought is completely different from the relatively normal language generated as human-facing output. You can observe this in any open-weight LLM, or in leaked CoT content from GPT5.x series etc: it's terse, barely follows sentence structure, lots of repeated checks and second-guessing.
On the next turn the model usually still has access to its previous turn's chain-of-thought, and I imagine that's what it'll use as reference, rather than the softer human-facing prose.
This being the case, asking the LLM to code-switch to an […]
- pholden
> A subagent investigates a bug, turns its findings into a nice human-readable summary, the parent agent reads that summary, and then turns it into another nice human-readable summary for you.
Is that a problem with https://code.claude.com/docs/en/output-styles?
> Output styles apply to the main conversation only: a subagent runs its own system prompt, so styles don’t change how subagents respond. A fork is the exception, because it inherits the parent’s full system prompt.
- stillpointlab
One thing that continues to give me pause is Fable's insistence on using my fist name in messages and docs. Like, I'll explain what I want to the AI and ask it to write out a spec or brief and Fable says "Jamie wants me to ...". It just feels different and unprofessional. If I was at a job and a PM asked me to write up a task spec I wouldn't say "Harold wants to add <feature> ...". And since I am the one reading the output it is also superfluous and almost feels like talking about myself in third person. But there is almost a kind of glee in the way it uses my name, like a student using their teachers first name when the custom is to use Mr/Mrs.