Makes sense when you consider what type of data Google had available in abundance. Natural written language (e.g., Docs, Gmail, Books) and natural spoken language (e.g., YouTube).
One could argue that Google Colab would supply the training data for better coding performance. I would argue that Colab is mostly used for non-complex (e.g., small number of variables) and self-contained (i.e., runnable in one page) code that can’t train a model for multi-folder and multi-page projects that rely on global connections, which real-life coding would often require.
Google also has millions of lines of code in several languages written over decades. Probably access to more non-public (quality) code than most other companies in the world.
For real, the "Claudish" has become so painful to read that it just takes me out of whatever task I was working on.
When prompted to use simple English without jargon, it's still filled with load bearing honest caveats in every footgun seam it talks about — what I should have led with. <Insert whatever other Claude cliche you prefer>
And I'm not the only one to notice this. Next time it's up for renewal, my team is abandoning it for GH Copilot in order to use literally any other frontier model.
Yes, Claude speaks Claudish but at the end of the day I care about the Ruby, Python, JS it writes. It still does a good job at it even if maybe I prefer the way DeepSeek talks. I did not use other models in an agentic harness.
The code is fine, yes. But now that I am dabbling in spec-driven development (unsure whether I like it) I have to read a lot of prose and I simply cannot get myself to read a page of claudisms. It is that painful.
The odd phrases are one thing, what numbs my brain is how everything is evenly bombastic and lacks any sense of rhythm. Technical documents should not read like catchphrases strung together.
That claim about load bearing is doing a lot of work there!
I'm curious to know how "Claudish" emerged during the training process. Why each AI has a particular voice if much of the training material is the same across AIs?
They train Claude on its own output and conversations with users, so tics like this are going to get amplified by virtue of being more common in the training set.
That, and my conspiracy hat says it's a way of watermarking the output.
From my own tests, the best model for writing complex, nuanced prose is Opus 4.6. All the next versions are impossible to coax into good writing. Gemini is OK, GPT ok but requires significant prompt tuning.
So, given that developers these days mix and match models anyway with harnesses like Pi, has anyone tried letting Claude or GPT do the coding, and Gemini do the comments and documentation? Maybe even asking it to "translate" Claude's output messages to better human language for the developer or subagents?
when i use gemini i ask it to stop asking me questions, to stop showing me media and just use text, and be concise in output. with these directions it’s pretty useful
Having coworkers who use it and thus unfortunately needing to read its output, Claude's "English" is very obviously unnatural-sounding, and extremely distinctive in a bad and irritating way. It's almost like another dialect.
...and of course this article itself has a bit of AI-ish tone to it.
You'll find some paragraphs are half written by Ai and some written totally by me. It's heavily edited from its original form (as it was a data report by codex on our db) - but some paragraphs which were good enough stayed.
E.g. Contrast my human written paragraph vs the AI written first paragraph
Human written:
"The three most popular AI models used by college students are ChatGPT, Gemini, and Claude. As of August 2026 the data on StudyArena shows they prefer Gemini.
"
vs
AI Written "Most AI comparsions are written like wine reviews. Claude is subtle. ChatGPT is dependable.."
Given that this is increasingly the go-to for a college degree, college needs to rethink its cirricula and place in the world. Or at least get rid of the essay.
Lest it become a place where student and teacher ais go to play pay-to-win social deduction video games.
The homework essay is dead. High schoolers in my home state were just relieved of any take-home assignments because it was pointless now, I guess universities won't be far behind.
My professor and teacher friends are painfully aware of how many students submit AI generated essays.
They're adding steps like having the students discuss and defend their essay, which immediately reveals the people who had AI write something and thought they could bluff. This triggers complaints about social anxiety and such, which are unfortunately becoming the go-to defense when unable to discuss the work.
They're also moving toward more in-person writing. Instead of long essays, shorter writing segments as part of the test. Submitting a written essay earns you feedback from the professor and a better understanding of the topic, but that's it.
I think it's less about curricula and more about how professors should eval their students. In previous era's essays are a proxy of the students ability to reason, remember and argue certain points - but its clear they fall short now.
I suspect the best schools into the future will integrate lots of socratic defenses of theses, building real things in real time or solving problems with a professor in a case study manner. My last company was a good hint to the future.
TBH i did a bit of both - we used AI to get us insights in the db, we then wrote and rewrote the article to be readable. It's really hard because usually when i write reports they're so terse its not fun to read
GPT gets the most out there, but creates interesting nuance that turn an idea into a more creative exercise. Claude is like a more grounded GPT but may miss the nuance. Gemini is my last pick, but does better than the rest for making something clear and understandable. It gets to be exhausting parsing through Claude outputs and breaking it down into something more easily understandable. One way I use to improve this is to ask the LLM to pull upstream ideas from prior work on the topics. This makes me feel better about the possibility of hallucination, gives me alternate places to look, but the model still may pull things out of context or fall over on the interpretation.
Given all that, I can definitely see how Gemini would be preferred. And good for Google, because I would rather my offering be the top choice for the most people rather than better serving a small subset of users.
I'd love to see the same experiment with responses normalized for length, and with actual essay quality scored separately from how helpful the model's feedback felt
The spread isn't as large as I thought from the headline. It's closer to a toss-up than I would have expected.
The length of the response is a huge factor:
> Students tended to prefer longer responses. The selected answer was 37% longer on average than the alternatives. The longest response won 47.7% of decisive writing comparisons. The shortest still won 25.0%.
So the score is partially a proxy for longest responses.
Makes me wonder how much the reviewers actually read the text. Were lazy evaluators picking the text that looked the longest or most structured without reading it all?
Yeah it's hard to get good data on what's best. We did read the a good sample amount of essays. Lots of arguments about what made them better, but its uncontroversial that longer ones were more preferred.
Interestingly we trained a simple LORA layer on top of Inkling and it turns out a model can smell which model wrote a response 70% of the time. I wonder if the smell of gemini is just more preferred by students.
Matches my experience. When I need to think or reason about something, between Clause and ChatGPT, the latter is my go to. With more to read, there’s just more to work with. For the same reason it’s bonkers for tech issues. How many times did I get a ChatGPT reply a mile long, do the first thing, and then read more after it didn’t work. Only then realize chatgpt didn’t offer the best answer first.
>Makes me wonder how much the reviewers actually read the text.
How many of the college students voting have years of ai use under their belt, where ai voice itself has shaped and influenced their stylistic choices of language preference?
Way back when I was in high school, the most important part of essay writing was figuring out how to expand the topic I cared nothing about to the required X pages. I'm unsurprised that college students would default to the same thing.
Interestingly, the smartest students I've worked with do use AI - but more in the sense that AI is a good comparison tool and a good bottom ceiling of the quality of work they should bring in.
Lots of research shows being able to see different answers improves the quality of a student's output - especially as the good ones are able to pick out what's good from the other work and then add their own insights or takes on top.
I use Fable for writing code and some planning. I use GPT for planning/roadmaps and code review, it checks Fable. I use Gemini for stray conversations. Gemini has a better conversational style than GPT, less robotic; it hallucinates more unfortunately, it has plainly fallen quite a bit behind, but it's still highly useful to converse with, research with, etc. And it spares me wasting usage of GPT or Fable. I use Gemini for the 'everything else' category, basically. Gemini never goes anywhere near anything serious.
Fable & Claude 4.x or 5 are terrible to talk to about anything. I gave up on that entirely and just use Anthropic's models for work.
Any less serious technical work I'll use GPT for, as the usage limits are quite fantastic.
Students do have different incentives in writing than SWE's. There's the habit of reaching word counts for assignments, some social signalling of how intellgent you are with essay length etc.
The data we have is just there to compare for the student base. I'd love to try it out on other cohorts - but the acquisition of such users and the product to make them happy is hard to achieve!
Been using Gemini for about a year for code (much cheaper and actually sticks to your prompt so savings are many multiples of; I work with Salesforce implementations and Google is a user for Salesforce so I think their code might have went into training data, coupled with their code guidelines it's been a bliss for me) and for other uses for maybe 9 months.
I do go back to ChatGPT for things that need to be calculated, but _Gemini simply hallucinates less_. IMO that's whats important for students.
I did get suckered into extending my Grok subscription which is really fun for images/videos. Grok in car is a must too (my jaw dropped when I asked what is pantsula music and it added multiple albums into playlist for me).
> “The best response must be complete without becoming shapeless, structured without sounding mechanical…”
Anyone else scratching their head at these descriptions? Uh, your writing is shapeless. You’re 5% too mechanical. Who talks like this? Fiction writers and editors??
Slip from where? Who talks like this putting these semantic concepts into this space? Somebody’s vector, but I don’t recall this in my college education about English composition.
74 comments
[ 0.28 ms ] story [ 33.9 ms ] threadOne could argue that Google Colab would supply the training data for better coding performance. I would argue that Colab is mostly used for non-complex (e.g., small number of variables) and self-contained (i.e., runnable in one page) code that can’t train a model for multi-folder and multi-page projects that rely on global connections, which real-life coding would often require.
When prompted to use simple English without jargon, it's still filled with load bearing honest caveats in every footgun seam it talks about — what I should have led with. <Insert whatever other Claude cliche you prefer>
And I'm not the only one to notice this. Next time it's up for renewal, my team is abandoning it for GH Copilot in order to use literally any other frontier model.
The odd phrases are one thing, what numbs my brain is how everything is evenly bombastic and lacks any sense of rhythm. Technical documents should not read like catchphrases strung together.
I'm curious to know how "Claudish" emerged during the training process. Why each AI has a particular voice if much of the training material is the same across AIs?
That, and my conspiracy hat says it's a way of watermarking the output.
...and of course this article itself has a bit of AI-ish tone to it.
E.g. Contrast my human written paragraph vs the AI written first paragraph
Human written:
"The three most popular AI models used by college students are ChatGPT, Gemini, and Claude. As of August 2026 the data on StudyArena shows they prefer Gemini. "
vs
AI Written "Most AI comparsions are written like wine reviews. Claude is subtle. ChatGPT is dependable.."
Given that this is increasingly the go-to for a college degree, college needs to rethink its cirricula and place in the world. Or at least get rid of the essay.
Lest it become a place where student and teacher ais go to play pay-to-win social deduction video games.
They're adding steps like having the students discuss and defend their essay, which immediately reveals the people who had AI write something and thought they could bluff. This triggers complaints about social anxiety and such, which are unfortunately becoming the go-to defense when unable to discuss the work.
They're also moving toward more in-person writing. Instead of long essays, shorter writing segments as part of the test. Submitting a written essay earns you feedback from the professor and a better understanding of the topic, but that's it.
Why did this ever go away? That was a completely regular part of college a decade plus ago.
I suspect the best schools into the future will integrate lots of socratic defenses of theses, building real things in real time or solving problems with a professor in a case study manner. My last company was a good hint to the future.
Given all that, I can definitely see how Gemini would be preferred. And good for Google, because I would rather my offering be the top choice for the most people rather than better serving a small subset of users.
The length of the response is a huge factor:
> Students tended to prefer longer responses. The selected answer was 37% longer on average than the alternatives. The longest response won 47.7% of decisive writing comparisons. The shortest still won 25.0%.
So the score is partially a proxy for longest responses.
Makes me wonder how much the reviewers actually read the text. Were lazy evaluators picking the text that looked the longest or most structured without reading it all?
Interestingly we trained a simple LORA layer on top of Inkling and it turns out a model can smell which model wrote a response 70% of the time. I wonder if the smell of gemini is just more preferred by students.
How many of the college students voting have years of ai use under their belt, where ai voice itself has shaped and influenced their stylistic choices of language preference?
Lots of research shows being able to see different answers improves the quality of a student's output - especially as the good ones are able to pick out what's good from the other work and then add their own insights or takes on top.
Fable & Claude 4.x or 5 are terrible to talk to about anything. I gave up on that entirely and just use Anthropic's models for work.
Any less serious technical work I'll use GPT for, as the usage limits are quite fantastic.
at most, the result could be useful for fellow students
I have no doubt other cohorts would rate differently
it is known (on HN at least) e.g. that SWEs tend to prefer brevity, contrary to these students apparently
The data we have is just there to compare for the student base. I'd love to try it out on other cohorts - but the acquisition of such users and the product to make them happy is hard to achieve!
I do go back to ChatGPT for things that need to be calculated, but _Gemini simply hallucinates less_. IMO that's whats important for students.
I did get suckered into extending my Grok subscription which is really fun for images/videos. Grok in car is a must too (my jaw dropped when I asked what is pantsula music and it added multiple albums into playlist for me).
Anyone else scratching their head at these descriptions? Uh, your writing is shapeless. You’re 5% too mechanical. Who talks like this? Fiction writers and editors??