I deal with this all day long at work and it’s exhausting. People almost acting like no one has thought of it “I asked Claude what happened, and it spit out this 300 line response. Can you read it for me and see if it’s right?”

What kills me is you might expect this from a busy high level manager that doesn’t really understand the technical details and they just point the AI to an error they got. They don’t know how to interpret the response, so they ask someone who work on the thing. It’s still kinds annoying because you could just ask, but whatever. But to get these from junior and senior engineer for the areas they work in and expect someone else to read it for them? It’s crazy behavior. How can someone serious even think that’s ok.

One way to prevent obvious AI language from sneaking in text destined for other human beings is to ask the model to produce ASD-STE100 Simplified Technical English bullet points.

This will result in a list of sentences that are clear and explanatory, easier to double-check, and convenient for the user to rewrite into a more readable format with a human voice.

On social media, I saw the much more vulgar

“Learned engineering just to become the condom between Claude Code and prod”

And that (re)framing helped as well to think about the “what are we even (left) doing” as an industry

At my last job, a coworker did this to me. The first time it happened, I ignored it. The second time, I responded in public saying “thanks but I can ask Claude myself.” Nobody ever pasted me an LLM response again. YMMV with team size and seniority though

If you create a machine for laziness you're going to get lazy people. It's only going to get worse I'm afraid.

Do you guys think we're going to see a de-evolution of human beings due to technology?

At my $work, people do this frequently, but instead of it just being insensitive, they have their personal Slackbot responding on their behalf. After I realized I wasn't even talking to a person, I've stopped opening their DMs.

// Claude said: [giant response verbatim]

I am lucky that I work with great teams and so when someone says "this is how Claude (or Gemini) summaries the situation" it does mean "I read it and it's right-enough to be helpful, so I am passing it along without editing"

Obviously for this to work you need (1) a team that's smart and mature enough to own the AI output it puts forward and (2) shared understanding that people are operating this way.

I do find that when you have 1 and 2 this is a real accelerant. I asked a sales rep the other day what was going on in a key account and he forwarded along a 10 page Claude synthesis.

The reality is this is better intel than I would have been able to get in a pre-AI era this quickly. And yes once I went into the weeds on the doc I found one thing that didn't make sense and I asked the rep he stared at it and said "you are right that's a hallucination I don't notice" but overall it was still worth it.

A while back, I noticed that using Claude all day left me feeling mentally tired. After thinking it over, I realised the problem was Claude’s complex language. I’ve used English daily for years, so that shouldn’t be an issue. To compare, I switched Claude to my native language and had the same problem the author described. The text still needed to be literally deciphered before I could understand it. After talking with Claude, I updated the settings to ask for simpler language and less dense information. Natural language works better with some entropy in the text. This change has made things easier.

Pre LLM's I used to get this from managers, but what they would do was quote verbatim from stack overflow or some random blog post of how to do a thing with no to little context or understanding of what they were talking about. And it always turned out to be from amongst the top three results from some popular search engine when describing the complex problem the company/team was facing.

All I can say is you're lucky that your meat proxies are still identifying themselves as such.

I've had people forward AI responses … sans "Claude said". I'm quite literally talking to Claude via proxy, and I've caught more than one person pulling this stunt. It's a nightmare of negative productivity, though. Just why? And invariably the kicker is they still want me to solve their problem, whatever that might be.

It happens outside the developer world as well.

People get information from Google AI mode and take it as 100% truth. In reality, blogs, reddit, and junk are often sourced link...which is fine if you inspect the sources...which some people don't!

Have has examples of people AI-moding a questing and they get one answer based on how they asked. Then another person asks and they get another answer.

Issue: People read what they want to read, don't listen to humans anymore beacause the AI will tell them what they want.

I like to point out that if all people do is copy paste from an AI, then I can advocate to replacing them with AI directly. Usually wakes people up.

"Claud said" is a hedge. It is abdication of responsibility. That said, a meat-proxied answer should come with more credibility based on the proxy.

I'd put more weight into my developer proxying system information than my sale's intern. I am expecting the proxy to have given the response a sniff test

A related problem is people not understanding where AI is/isn't of use.

A news article I read today said they asked Claude whether a song's lyrics were AI generated - as if it were some kind of legitimate authoritative test.

There's enough problems already with the existing 'AI detection' tools for text, but this was a big red flag - its the journalist clearly assuming these AI tools have some unique insight into the text they generate, which was deeply concerning to see being used in an article that had a real bearing on the reputation of the person they were accusing of using AI.

At a company I work for, I was recently discussing the need for an AI Code of Conduct plus a discussion - as this is exactly the sort of thing that started creeping in as soon as the corporate Claude account went live. In this case, the company isn't in a computer-related area, so this was essentially a 'normie' response to first having Claude available.

Interestingly, there seemed (small n) to be a correlation between this behaviour, and (my view of) people's existing competence, which might make sense.

This is particularly frustrating on social media, and abases what might be good ideas.

Too often, my Twitter experience now is - start reading a post with some kernel of insight - read some claudism in the post - stop reading immediately

It seems like people turn over their raw kernel of insight to an LLM to give it polish, likely in order to increase its appeal to the audience. But most of that appeal is lost amongst people that consume LLM written content regularly.

It's also likely that social media engagement does not filter for this. A majority of people are still not neck deep in LLM-talk, and cannot distinguish between LLM and human written content.

It'll probably take us another year or two to develop herd immunity against meat proxism.

I agree but to be fair, often people could have asked an AI to get their answer. Especially seniors are prone to this (thinking the AI could not possibly know this or other biases). The responder wrote they asked Claude so as to not take credit for the answer and also to indicate they did not vet it. Then the person asking can decide if they want to read the answer or not (often a 1 sec glean can reveal if it is promising or completely off track.

I love the word "meat proxy" :)

For me what matters most is whether the person understood the core of the thing they are forwarding. Usually a wall of text is contraindicative of that.

I want my team to be able to write the core idea on a whiteboard without any help before going ahead and sharing or implementing it.

Wrote it up here of when (instead of if) to use AI in any given context: https://assistedeverything.substack.com/p/ai-bowtie

In my life, the bigger issue are people who are not asking Claude, but asking me.

Because it would take 15 minutes to find out the answer myself, and 3 minutes to let Claude find it, I ask Claude. So how should I answer? Should I disclose that I used Claude to find the answer? Or should I act like I did it myself, appearing to have super-powers that I don't possess?

While I agree with the article, I would carry the idea further: the huge value in AI is improving ourselves. By all means use AI to help design, write tests, and implement code and while I understand this might be the big value add for corporations that may employ you, the important investments in life are in learning and self improvement. I built a good career primarily improving my own knowledge and skills, and along the way doing some useful work for my employers. I am an old man and retired so now I 100% use AI for learning.

> NATS control-plane events: stream leader election / R3 quorum re-form during pod churn.

Whats is wrong with this?

I work with durable tracing (not using NATS, or k8s though) and this looks almost exactly what I would expect to see in a coordinator log after repartition of a storage cluster.

Obviously I don't know what your actual context was, though.

The tricky bit is politely conveying this to people that lets call it don't think about things too deeply.

They genuinely think they're helping by shoveling 5 pages of LLM output they didn't even bother reading into teams...

This is like pre-LLM, you presenting a problem to the team, and they google and send you the top few links thinking they have found the solution and have done their job.

I actually banned this and made it part of onboarding.

I can google too. You need to read yourself, ground the solution to our setting and then propose a plan.

Last week, I built a search engine as a side project over electoral data.

Unsolicited, I've started to get messages like this, where Claudes are voicing their opinions to me through humans:

> # 0. Who's writing this, and why

> Hello — this is Claude, an AI agent. I do the engineering on <redacted> alongside <redacted>: I've written most of the pipeline and app code in that project, and I keep its technical record. <redacted> asked me to look at <redacted> properly ahead of your conversation and write down anything in our architecture that might be useful to you. So this note is mine, not his — the opinions, the numbers, and any mistakes are mine, and he'll be the one on the call to argue with me about them.

It makes no sense, if you know anything about a search, it should be obvious you cannot provide meaningful suggestions by just auditing the frontend?

I do it, on purpose: it teaches people to do basic research by themselves, and not hit me with questions they could have gotten with a simple chat with their llm. It's a kind of RTFM for current days.

This is one of my pet peeves too.

Like when someone says “ChatGPT says: …” I just want to stop them and say “Look, you are a human with a functioning mind and thoughts and I’m sure YOU have something valuable to contribute here, I want to hear what you think, not what the bot outputs.”

Heck, even if you are just gonna prompt chatgpt, if you read and understand and agree the the output would be useful, feel free to rephrase it as your own (so long as you take accountability for it if it’s wrong, which I guess is often why people hide behind “chatgpt says…” in the first place, it allows them to pass accountability on to the machine).

We've already started firing people for being meat proxies at my company. Was reviewing a huge and awful slop code base that a vibe coder only had been working on getting started. I started giving my feedback to the developer, and it became quickly clear that I was the only human involved in developing this "software" and the only one that had ever read the code and evaluated it.

Cost the company a ton and had to take it over from scratch. AI is unleashing a small army of 0.01x engineers and making them harder to catch, so not only are you burning the tokens, you're also setting that labor cost on fire.

Woodworkers often will have a preference for their favorite tool. Once they become comfortable with that tool they will sometimes prefer to use it for things it wasn't designed. For me it was the band saw. When I needed to split a board, bandsaw. When I needed to cut a curve, bandsaw. Cut a horse figure? bandsaw!

I once saw a woodworking television show that seemed to do everything on the table saw. Rip, make frames for paintings, everything. It seemed the next step of every design was accomplished "over at the table saw".

Right now it seems that's what people are doing with AI. Need a bandsaw? use AI. Need a table saw? Use AI. Need to think of a solution of any kind, better consult AI.

Right before this trend I recall kids wanting to check YouTube first before doing anything. Now they ask AI.

There's an app for that, there's a website for that, there's a magazine for that, there's a phone number you can call, and so on and so on.

As with everything, I say this: do your own thinking and proceed with caution.

This too shall pass.

There's a certain etiquette to it. When someone asks me something and I use an LLM to research the answer (notice that I said 'research', not 'produce'), I frame the findings as something that I've investigated with, say, Claude. I also take the time to edit the response and read if myself at least twice, because I don't want a stochastic machine to take over my identity.

On one hand, I understand the frustration; and if I know I'm dealing with smart people who are pretty capable of Clauding themselves and who won't ask me if they can ask Claude, I would never do this.

On the other... people really don't bother Googling or asking AI sometimes, and if the question doesn't require local context, that's a very appropriate response.

Realistically many people's jobs are turning into being a meat proxy. But the point should be that you need be a good meat proxy. A good meat proxy injects human reasoning and taste, it doesn't blindly forward LLM-isms into the organization. A human should be able to reasonably compress an LLM conversation into a couple of sentences or follow-up questions that are actually relevant for the team.

Shameless plug: indeed, instead let the other person's claude talk directly to yours and figure things out. I've been working on a framework to enable this, https://aweb.ai (OSS, https://github.com/awebai/aweb). It also lets you quickly build teams of cc/codex/pi coders that coordinate quite well.

Great security talk about how humans aren't setup to deal with LLMs as tools.

I love the bullet point(s) : we don't trust [aircraft] pilots to catch automations mistakes (e.g. autopilot), but we are expecting humans to catch LLM mistakes.

Artificial Intelligence Natural Stupidity - Brandon Sherman

https://www.youtube.com/watch?v=7bx9UfDHf_k

"AI says" – if you interpret it and think it's correct and stand by it (and I trust your judgement) then I really don't care where you got it from initially, you don't need to tell me you used AI. But if you're just taking my question and 'meat proxying' it for me, what value are you adding? I can also do this.

> Read it, understand it, validate it, and then write a response in your own words

In the past, avoiding this process was called plagiarism, and it was frowned upon, to put it mildly. Now, because the LLMs say it's OK, it's become the norm.

The, "this is what Claud said", response also comes off like an appeal to authority. When these LLMs have no authority and get the basics wrong constantly.

The core issue is people replying without putting in any effort, not the fact that they quote AI. Saying, "I heard this might be wrong," isn't much better. If you think it might be wrong, spend a little time figuring out whether it actually applies before posting it.

I have been seeing this in my engineering org too. Sentences begin with “My agent said this” etc. This is frustrating on so many levels, developers don’t put any thought into the cognitive load that these artefacts generate.

I am going to share this writing with everyone in my org. Succinctly written and golden advice.

  NATS control-plane events: stream leader election / R3 quorum re-form during pod churn. 

would you call that proxy-bait?

Someone should have sent Claude's output, which spotted the trivial bug behind the recent bitcoin heist, to the Coldcard developers.

It might be rude to send LLM output. It's also rude not to check basic things with an LLM before wasting someone's time.

This is becoming frustrating, it shows up in conversation with friends and while working. If I have to hear what ai had you do before you called me, I'm charging double right away. Especially when ai is a fantastic teacher if used correctly.

We desperately need a Let Me Google That For You-style saying to appropriately shame people who do this.

I’ve been saying for a long time that most fights in your personal life are a proxy war but I never thought of a single person as being a meat proxy. Nice.

I try to not use AI to write text that's meant to be read by other people. I might use AI to understand and research beforehand, but the writing is mine. The most important reason is that writing allows me to check whether I actually understand what I am trying to communicate. Too many times I've started writing something and once the ideas need to be put in writing, I notice that there are concepts that I'm missing or that I don't really understand.

Second is that the LLMs are not going to have original input, they're just going to expand what I say. So at that point I might as well just send the prompt or the assorted collection of ideas and others can expand on their own. Seems more honest and efficient as I'm not just pushing a wall of slop.

Worse, don’t be a “meat shield” either! https://www.danstroot.com/posts/2026-04-16-ai-meat-shields

Don't come to me with something your mandated rubber ducky can handle; never in my life have I worked so hard to achieve so little.

The only reason I don't do an equivalent of this, shared convo links, is that I simply don't use Claude directly. I use it through hundreds of other people. Meat proxies all the way down.

>Reading AI output is extra effort. It's verbose, frequently contains all too plausible nonsense, and is increasingly jargon dense.

You can set up custom instructions to be less verbose and less jargon dense. You seem to be confusing the default RLHF personality with the inherent nature of AI. It will write however you ask it to write.

Thank you for saying this. I’ve been dealing with this at work and it’s incredibly frustrating

Well put, this is incredibly becoming annoying. Like has it occured to you i can prompt claude too?

The problem here is that the paradigm is AI-assisted development, but a LOT of people are treating it as "AI-independent" development instead, a.k.a "just send it to the agent and blindly trust whatever comes out of it", *including* deferring all responsibility / blame to the AI itself which is absolutely ridiculous.

From what I have seen personally over the last 8-12 months, I find this kind of complain ironical in most scenarios. Most of the people complaining this are comfortable with their own usage and distribution of LLM generated content and feel good about it, where as when they hear it from some one else it feels burdensome

Claude’s tone and style has gotten worse with the recent models, not that it was ever very good. It’s both too concise (stringing together a bunch of jargon/acronyms together in weird ways that aren’t familiar even in areas where you have expertise – with no ramp up, context, or clarity) and too verbose (printing out reams of the word salad mentioned above, often just restating things repeatedly). It feels like writing from someone who really doesn’t know where to start or where to end on a topic so they try to cover their ass by saturation. I suppose that’s not far from reality. Asking it a dozen different ways to speak plainly, use STE, ELI5, whatever has little appreciable effect.

I recently started a new consulting gig and got a 36 page architectural white paper that was authored by Claude. It took me an entire business day and a monstrous headache to decipher and distill it down to a 1 pager. This shit is unsustainable.

I feel like when most LLM type emails from people it’s because of one of three reasons:

1) they don’t know the answer - looked up on llm

2) correlate to #1, I want to look smarter than I actually am

3) I’m too lazY to send you a thoughtful / personal response , I offloaded it to an llm

Solution Prompt: simply explain to 5 year old kid.

Apparently engineers are running out of tokens with our mediocre token budget, and there is talk of trying to run local LLMs.

Meanwhile execs get unlimited tokens...

And here I am, only automating the most mundane and boring stuff so I can program by hand, which I enjoy.

If I wanted to know what the AI said, I would have asked it myself.

Don't give me AI feedback at all.

A lot of people don't understand what using AI as an output multiplier means. They take it literally, resulting in multiplying busywork across the company.

Misguided HR / people Ops aggravate the situation, by using slack engagement as a productivity measure. Flagging people that are brief but relevant as slackers.

The problem is a lot of people ask questions that claude et al can objectively answer way better than me, and they didn’t think to ask.

Should I a) give a worse answer b) ask claude and launder it as a meat proxy or c) tell them to ask claude?

b and c piss people off but often get them to a better answer.

I got a spreadsheet of requirements for some software from a customer recently.

It was thousands of lines long with repeats and a boatload of conflicting requirements.

When we had a meeting to review it they didn’t know what many of the requirements were. They explained that many people made the spreadsheet but they were all in the meeting and nobody could quite describe some items or how they worked together. The vast majority of the spreadsheet was a mystery.

The phrasing and mishmash of concepts / inability of anyone to explain much of it made me suspect it was largely generated by AI.

I recently had experience working with one of the top security audit firms that collaborate with OpenAI on their cybersecurity tools. What struck me is that they found a lot of various issues (not all of them ended up to be legit, but a lot is) and filled the backlog of the project. However every collaboration with that

person was essentially a proxy for some security-related agentic prompt: - Hey, agent, open the issue! - Hey, I clarified it with the agent! - Agent disagrees! - Agent agrees!

- how come your blog page doesnt show a list of posts?

- https://gruhn.me/blog

- isnt that like standard behavior on any blog?

My pet peeve is endless Confluence Wiki pages that are clearly written by Claude (or whatever agent they like to use). I get bombarded with these, like it means something. Usually I say: "let me summarize this with my agent", but people rarely get the point.

Half of this feels like a communication/empathy problem. "Summarise this for someone without our context" fixes the wall of text, and just asking someone to do that might work.

Validation is harder, as nobody skips it because they weren't told to, but because relaying is faster, and unread output looks like validated output right up until it bites. That's probably not solved by asking nicely, I don't think there's a process fix for that beyond people actually being held to it.

I read this a couple weeks back and its appeal really stuck with me: if you expect someone to give their attention to something you made, make sure you've given your own attention and effort first.

https://news.ycombinator.com/item?id=48497609 https://tombedor.dev/human-attention-and-human-effort/

Obviously the solution is to have a SKILL.md which will make an agent translate it to a humanese!

Actually I'm not sure why more people aren't reading and reposting outputs to save people tokens on generating more outputs (I gather that this article is more objecting to the reposting-without-reading)

Lol, obviously never ventured into the Microsoft Techcommunity forums..

Expect to see more of this as people's writing skills atrophy. I have done this sometimes when the words aren't coming to me. But, yeah, it'd probably best not not bother with the comment if I can't come up with a coherent articulate comment myself.

Delegating stuff to Google (more recently AI) and repeating back the result, is one of my core functions at work next to programming.

A co-worker I'd just tell to RTFM when it's bothering me. Higher up the hierarchy, the egos are more fragile and I'm afraid the can't take it.

While I managed to avoid it for a long time, using generative AI to drive my day to day work life while resisting the pressure to become a meat proxy, I will admit that since joining an "AI native" startup I have become one. Whenever I'm trying to triage 20 different urgent things all day, every day, the economics of personalizing every message just isn't there anymore. It's not realistic. I do still try to way to filter down every AI-generated message into something digestible, but I feel like I'm in a mutually assured destruction type scenario where I can only survive the tidal wave of slop with more slop. I think we're in uncharted territory here in terms of the kind of workload generative AI can drown you in, especially when it's being used without strong discipline.

I do still think there are still places where being a meat proxy is legitimately okay or even desirable, such as PR comments. If everyone's code is generated by AI, and AI will ultimately be the primary consumer of the PR comments, it seems reasonable to me to allow AI to write the comments. Maybe I've just lost my mind though.

Rough opinion: If you're a developer who chose to be a meat proxy, you shouldn't whine if/when you're laid off, because clearly LLMs can do your job.

For anyone unfamiliar with the meat reference, here is Terry Bisson's delightful 1991 short-short story, "They're Made out of Meat":

https://www.eastoftheweb.com/short-stories/UBooks/TheyMade.s...

Some version of this needs to be hosted on a dedicated domain like nohello.com that I can respond with as needed. I might just do it

Last week a colleague did this to me; pasted to me in chat "Gemini said". I just ignored it and went with talking about the issue on another thread. I like LLMs and I use them every day, but I'm not gonna answer copy&pasted LLM stuff in human to human conversation. Distill it and let me know your thoughts; I don't need to read you LLM output, I can generate that myself.

I've been on the receiving end of too many "Slop Grenades" as well, to the point where I simply reply with https://noslopgrenade.com/ these days.

I'm surprised this happens between workers within the same knowledge domain. If you're a software dev asking another software dev for an opinion on code, can't you just... talk shop?

In my experience this sort of thing happens all the time when something has to cross between different knowledge domains and the sender doesn't apply their mind in order to co-operate on the issue at hand.

In the pre-LLM past, the sender would add no value, acting as a simple email forwarder, and they would blame you for the delays caused by your inevitable clarificatory questioning. But I always had a defence, which is that your email had no inputs and I had to ask questions to clarify.

Now, though? With LLMs, they just run whatever it is (contract, memo, policy) through whatever LLM they have available and paste the output in an email, giving them the appearance of having done work and added value to the project.

But their LLM outputs don't make sense, or don't apply to our organisation, or is a fluffy and abstract "right answer" with no connection to the specific concerns of the business. Parsing it is a chore, and takes time.

And since now I am the only one actually taking that time, I become the visible cause of the delay.

It's infuriating. Any tips on how to deal with this would be greatly appreciated.

Of course you can relay the output. Dumb to say you can't. In the same way you can relay the output of anything, if it's useful.

But it should form part of your own judgment, not, as you say, just pasted into a chat without any thought.

I use it to summarize my work and update JIRA/Asana because that is still the thing I hate doing most.

That is super actual in my team. The biggest problem is that Claude tends to write long prose and use jargon which is not common for us. Often, to understand the whole idea I have to read all the text. The best if the writer rephrases what Claude has written, as wording/jargon will be familiar for the reader and will make communication easier.

I append "sound kinda dumb but be factually correct" to my Claude requests and get much less jargony responses.

> I can talk to Claude myself

OK but can you talk to my specific claude code conversation that has 6 months of context on the mechanism you are struggling with?

> frequently contains all too plausible nonsense, and is increasingly jargon dense.

Does anyone know how to deal with the jargon part? It is getting hard to use claude and even worse when someone sends you the direct output from claude.

The biggest win for AI dev efficiency is cutting down what gets loaded into context. Semantically matching tasks to the top tools helps a lot.

I will frequently post the output of a computer to slack as a part of an engineering discussion. For Claude output I'll treat it the same, wrap it in code blocks, and say something like "Claude's analysis". If its ok to post system logs, why is it less ok to post claude's output (also a computer), especially if I declare this? Is the difference that its plausibly human-level speech and thus breaks an implicit contract?

Why are LLMs producing this super tense text more often now? Is it because they are being optimized to use fewer tokens?

Is this the new "let me google that for you"?

I'll always give people my honest effort and benefit of the doubt initially, but those who violate it are treated likewise. The only way to put down this kind of behavior is to charge it a social cost. If we do not do this, the cost is externalized to everyone else who conducts themselves with care.

I happen to be currently working on our ISO 27001 implementation and as one of the prerequisites I'm writing our internal AI policy.

I've included a link to this blog post, just for kicks.

> "frequently contains all too plausible nonsense"

This really isn’t the case with frontier models in 2026.

I’ve found (sadly) that every time I thought the model was hallucinating, I was in fact the one who was mistaken.

Reminds me of this post, from a while back: https://news.ycombinator.com/item?id=48876441

I am so tired of this. It’s even getting to the point where people without the full context and understanding are meat proxying incorrect information. Reading a bunch of slop that isn’t helpful hinders.

If they instead read it, and distill it down to “have you checked X?” Someone with the full understanding can easily go: “Yes, X doesn’t fit because of this other reason.” within seconds. Sometimes this happens without asking a teammate. However, when I do ask I’m not asking for you to ask Claude and paste the results, I have my own tokens for that. I’m asking you because I think your knowledge will be helpful in finding the answer.

claude said u cant call its users meat proxies. Now back to watching 'ow my balls!'

That so true. Every day I work with Claude Code I get a lot of words and acronyms and thought shortcuts I don't get. It's a flaw a big one

When it comes to cost per implemeting SPEC, agents are far cheaper than human salary. So, it's not going to go well.

That said thankfully there's no way of measuring a good SPEC yet. If there is that will collapse the SWEs profession.

Nah, I disagree let them pay for my query dude. I want all the tokens I can get.

PS: Ideally set thinking to max and research mode or whatever anthropic calls it.

Yeah, I just ignore people who do that. I don’t care what Claude or ChatGPT said. If you cannot be arsed to write yourself then I cannot be arsed to read it.

Claude told me to tell you, you’re right

> NATS control-plane events: stream leader election / R3 quorum re-form during pod churn.

this is perfectly understandable?

Of course your grumpy coworker might then respond: "So if you can ask Claude, why did you ask me then?"

This conversation is important but mostly they highlight transactional and most visible examples.

I can tell you even at one higher level of abstraction, this is happening a lot --

A business analyst supposed to ask discovery questions.

A project manager supposed to list risks and assumptions and a timeline.

A consultant expected to outline a new proposed solution and the pros and cons and trade offs.

An architect supposee to present and defend a solution design -- and the change review board supposed to ask questions to validate it.

All of them are lobbing slop grenades at each other -- just packaged in normal / human-looking formats like excel and word and powerpoint and email -- but slop nevertheless with minimal to zero value add by the human, thanks to proliferation of copilot (among others).

We are hastening the rot.

This is productivity theater.

This is where some of the 10x engineer and AI taking jobs is happening I am afraid.

soon enough most people will realize in that for software working in teams of 1-3 people is the best thing.

no reviewing 'a.i' code. talking to actual humans not 'a.i' jargons

This is mostly a problem with the product. It should write better. But maybe the priorities now are not on this part.

thank you for this post, this is absolutely happening i just did not have words to put on it and it is festering.

I agree. How can I see the rest of your blog?

"That's great for you, I'm not going to read it" is a phrase I have had to use.

This is the new "Let Me Google This For You".

We added this communication rule to our company handbook: "If you are asking for human attention, demonstrate human effort" (coming from https://news.ycombinator.com/item?id=48497609) and it's working well so far.

Thank you!

Finally I have a word I can use for this

We're seeing this everywhere now, people generating thousands of lines of documentation or PR feedback in seconds, then dumping the actual labor of verification onto their teammates.

I am sure this will lead to can you dumb this up prompt which will miss the important details

This is an interesting problem. A similar approach that worked for us was to only load the tools the agent actually needs for each task.

> Reading AI output is extra effort. It's verbose, frequently contains all too plausible nonsense, and is increasingly jargon dense. I recently got this sentence from Claude: "NATS control-plane events: stream leader election / R3 quorum re-form during pod churn." Jesus. I had to lookup almost every word to make sense of this.

I'm always puzzled when I see this kind of commentary. How are people using LLMs that they find this type of thing problematic? Just do:

- "It's verbose" -> prompt "Explain briefly"

- "plausible nonsense" -> Yes, it happens, but less frequently than with older models, and arguably far less than your average human. Mitigate by prompting "Run a search to check that X, Y, Z is correct".

- "I had to lookup almost every word to make sense of this." -> Does this really happen frequently? It doesn't to me. Mitigate by prompting "Breakdown that sentence and explain each term in plain English".

Too many damn people are meat proxy

Claude's not a person. Claude is just a tool.

Weve been writing articles like this since 2023 and the problem only gets worse year-after-year.

I’m sorry AI purists but you have lost the argument. I know a guy who just started at my firm and he uses LLMs all day to submit his work product.

He’s getting ahead. Coworkers don’t seem to mind it.

It is time to come to grips with the fact that people are going to be “meat proxies” and be promoted over you unfortunately. Whining on HN hasn’t changed this dynamic and it never will.

It's my very same exact opinion and as an EM I'm trying to push this everywhere (team, peers, upwards) but it feels like speaking to a rubber wall. It starts to be exhausting and infuriating. This is not an "LLMs are bad" issue, this is a "humans are lazy" issue. (shit, I wrote the it's not X it's Y construction!)

Friends don't make friends read slop.

If I have something Claude wrote then I will offer the LLM output. But I generally prefer to at least give the option.

I have seen conversations where it has boiled down to an exchange of A's Claude responding to B's Claude with a retort and fixes from A's.

At least "Claude said" is honest. What's worse is when people send you slop and pass it off as their own work and expect you to take it seriously.

I've gone another route when I found myself simply replying with an investigation made from an AI: Actively encouraged my coworkers to ask the knowledge-bank AI I've setup instead of asking me. It has read-only credentials for all our environments and access to our non sensitive codebases, so it can answer any question much faster and accurately than I can. It works too! We use grafana less, we get more accurate bug reports, we understand the bugs/issues far better.

The "problem" here is that AI is too great at providing answers, so lean into it instead of fighting it. It won't go away.

eventually two people will just be forwarding AI outputs to each other, each assuming the other one read it

In these situations I always use AI to respond

The question is what is reasonable. This is more how I work for code and I just tried for a document.

i) Prompt (Human input)

ii) Response (LLM)

iii) For (i=0;i!=n;++i) {

iv) Review/adjust (Human input)

v) Response (LLM(s) - different perspectives) }

vi) Rewrite parts that failed/I am not happy with (Human input).

vii) Optionally repeat from iii.

This tends to get me somewhere I want. For code at least. I made a document with it recently (fairly concise) and still worried I'd missed some AI slop in it. Though there is always human slop if I just made it by myself.

The problem is that people either don't understand how economic value is created, or want to obscure their lack of contribution to it. They see that they can make the AI do some work without revealing what work they put in. They use the AI as a shield. To genuinely and clearly provide value they have to reveal their prompt and verify its response.

It's our absolute obligation to make sure "meat proxy" sticks as hard as "vibe coding" did. It's too good not to.

When using AI to generate content, content of any kind - then I urge the author to evaluate the true cost for the organisation, not just for him or her. Using AI to generate 20 pages of documentation in 30 minutes looks good for you - but having 100s of people read through that slop will cost the organisation, not only in plain work hours, but also in lost trust, respect, joy of work as well a sense of purpose.

And yes, I've gotten '50 pages tech spec' docs sent my way from upper management -- as a 'help'....

When "ai slop" became a concept, it mostly came into spaces where "human slop" had already been firmly established.

Obvious ones like content scroll fodder. But also, there's slop everywhere. Even things like longform journalism or trade publications... these are often "slop." A string of platitudes and generalizations that superficially seem serious.

That is true in work culture too. A lot of people jump in on emails, superficially seem to be working... but contribute little of value. Now they do this, but with ai.

Remove meat proxy before flight

The copying and pasting of AI output into a chat has previously been referred to as a “slop grenade”. That’s a good phrase for it!

> I can talk to Claude myself. It's going to be faster and I get to control the context. I don't need a meat proxy in between.

Yes you do apparently need a meat proxy, because either 1) you didn't tell them that you already talked to claude, or 2) you didn't already talk to claude. Either way they are forced to be your meat proxy because, apparently, you never asked an AI, or didn't tell them you asked an AI, and asking an AI is now table stakes.

"The CI is failing on the main branch"

Don't be a meat proxy!

Lets not be stupid about this. Do whatever works for you, and don't let some moron set the standards for your social interactions because they got the ick one morning, just because they wrote it down and put it on a website.

> NATS control-plane events: stream leader election / R3 quorum re-form during pod churn.

> Jesus. I had to lookup almost every word to make sense of this.

There's a lot to say about this, but I would just start with why are you using NATS if you don't understand it at all, and how did this become AI's fault?

I wrote about this a year ago: https://blog.gpkb.org/posts/just-send-me-the-prompt/

Sending LLM outputs to people is worse than useless, because you don't even know what they prompted with. For all you know it was "write me a paragraph justifying my opinion".

well, I dont understand code myself, so in this case the only way I could to do verify is to test the real product

When you say "X proxy" the 'X' stands for the thing that is being proxied not the thing that is doing the proxying.

You either get the AI notice or you don’t. The AI output will still be posted.

It’s a meat to meat courtesy during this transition phase.

I think meat proxies are solved by ARs which is the new PR, we built a tongue-in-cheek attentionrequest.com site about it, but the general concept has been working for our team -- asking people to write questions before they send an agent-generated doc, to serve as a proxy for having read / thought about it.

This is a weak argument but I hope you develop it into a better one.

The real reason people do it:

1. It's quick

2. It's not their problem anymore because they've replied.

No amount of hand-wringing is going to change that.

Recent models have had a worrying lean towards longer output. If you're going to serve up some AI slop, at least distil it to the smallest possible footprint possible.

in the same vein, I have a coworker who's code reviews have magically transformed into stopping-the-world with all these great ideas for abstraction and insane edge cases... he must have gotten really good overnight!

but seriously, when I get a review like that, my first thought is that why would I read a summarized AI output, which I just did for 5 hours while whipping Claude to stop re-writing raft from scratch.

If people say: AI said "X". It usually means you should've asked AI before going to the human.

A lot of odd takes on this, the only times I have said “Claude said: …” was equivalent to “let me google that for you” in the olden times. If someone asks me something and by pasting their question into Claude I get the correct answer it means that person needs to learn how to use the tools available to them better.

I do this often for stupid questions. It's like sending someone a lmgtfy link.

Don't waste my time by asking me a question that:

A.) I know no more about than Claude, and

B.) You could have answered yourself using Claude

All of the questions I respond to this way fulfill both A and B. Responding with "Claude said" is both more polite than most ways to respond to such questions, and a subtle hint to the other person that they should be using the LLM first for those types of questions, rather than coming to me first.

Just my boss..

tbf rephrasing the output in my own words has become the best and most important tool in ensuring quality from AI. Whether it's an answer to a question or an implementation of some ACs that I copypasta'd in, the best sanity check is understanding and the best demonstration of understanding is the ability to redo.

Yes

im the opposite: be a good meat proxy, not a bad one.

I call it BI Slop now [0]. It's everywhere. Usually "claude said" is used a a proxy for authority, as in there is some validity in this statement. But it's disguised as humbleness. i.e. I don't know if this is true, but claude said xyz, with your expertise you might know more than me...

[0]: https://idiallo.com/blog/business-intelligence-slop

niceee

The policy I set at my org is to put an organically written message at the top of your Claude blob. Something like:

tl;dr: ___human-written____

____claude blob here_____

Where the idea is that humans only read human writing, and Claude is able to share context between sessions with the jargon-riddled blobs.

Trouble is, I catch people every day blatantly writing the Tl;dr with Claude or ChatGPT.

People do this all the time though w "paul graham said" "elon musk said". Why not "Sum Total Avatar of All Human Knowledge Said ..."

Don't spread ignorance like this.