Researcher rejects LLMs for her work, citing confident errors and loss of creative control
A security researcher explains why she refuses to use AI models for her published work despite industry pressure to adopt them.
What to know
- A researcher refuses to use LLMs for published work, citing their confident hallucinations and her inability to ethically credit AI authorship.
- She argues AI companies have oversold their role in security research, using php2shell as an example where vendors spun the same work with competing narratives.
- Hacker News discussion reveals sharp splits: some commenters embrace LLMs as productivity multipliers for specific tasks; others report being forced to adopt them despite reservations; some share her frustration with LLM errors.
- Core tension: whether outsourcing research and coding to LLMs represents genuine productivity gain or loss of intellectual autonomy and expertise development.
The dispute Whether LLMs increase productivity net or create hidden work in review and correction, and whether the pressure to adopt them reflects genuine technological advantage or industry desperation to recover capital. · positions read across 23 posts and comments
LLM adoption should match the task: they excel at specific research or coding assistance, but fail catastrophically when used as a replacement for thinking.
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“The people I work with outsourcing their research to LLMs are doing wonders. The people I work with outsourcing the line-by-line level of coding to LLMs are hugely productive.”
danpalmer · Hacker News ↗
LLMs are fundamentally unreliable due to confident hallucinations and should not be used for research or expert work.
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“i cannot handle something being that confidently wrong (even though it'll probably still get there in the end)”
xyzeva · Personal blog (eva.ac) ↗
Workers are under economic pressure to adopt LLMs regardless of their actual value or their personal views on AI.
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“I would like to not use an LLM too, but I'd soon be out of a job if I didn't. It's an exhausting place to be and I wish I were closer to retirement.”
micromacrofoot · Hacker News ↗
xyzeva Security researcher and developerOpenAI AI companyAnthropic AI companyWiz Security company
How it unfolded 3 developments, newest first · click a bar or a number to jump articlespostscomments
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Commenters divide on LLM confidence errors and adoption pressure
Discussion on Hacker News reveals multiple positions: some share the author's frustration with LLM hallucinations, others report strong productivity gains from selective AI use, and some express resignation about being forced to adopt LLMs to remain employable. One commenter notes that LLM output errors are widely documented online, while another defends LLMs' utility when applied to specific tasks rather than wholesale thinking.
“The people I work with outsourcing their thinking to LLMs are struggling, and if I'm not careful they're creating more work for me in review and feedback.”
— danpalmer -
I think there is a lot of interesting discussion around the topic of offloading thinking to AI and the consequences, but blogs like this don’t scratch that itch. This falls more into the category of virtue signaling and pick-a-side division that does well on social media but has little relevance to real life.The core piece of this blog post is…
2 more of the top 3 · 23 posts in this stretch
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Every time I get pulled into a conversation with someone who is an extreme AI skeptic in this latter half of 2026, it’s eventually revealed that their only experience is one of:1. The AI box at the top of Google2. The voice assistance on their phone when they tried it a long time ago. Some question they asked Siri in 2025 and got a bad answer…
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> i truly have tried to use llms before, just to try it out. nothing i was going to publish as research, but i really couldn't and it left me never wanting to use an llm again>> i don't know how more people don't experience this, but staring at an llms output be confidently wrong eventually to get there in the process, or looking at the commands…
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Author critiques AI companies' cybersecurity marketing narratives
The essay argues that AI companies have exaggerated their role in vulnerability discovery using the php2shell project as an example, where Anthropic, OpenAI, and Wiz each released different narratives about the same work. She contends that LLMs still require human expertise to guide them and cannot independently discover vulnerabilities in major projects like the Linux kernel.
“if you threw an llm at the linux kernel and told it to find an rce without any other guidance, it probably couldn't. you still need skill and experience to guide an llm at the current state…”
— xyzeva -
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Researcher publishes essay rejecting LLMs for her work
A developer and security researcher posted an essay titled "So I guess everyone uses LLMs to think now" explaining why she has never used AI models for any published research despite repeated suggestions to do so. She cites loss of enjoyment, inability to take credit for AI work, and frustration with LLMs' confident errors.
“i do this for fun, and i don't find giving an ai all the fun at poking at something instead of doing it myself fun. put it another way, i like using my brain…”
— xyzeva -
first by HN Frontpage, 10d ago
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What people are saying 20 voices from 1 site · best of 23 · verbatim
- How do you determine when an LLM's output is correct versus confidently wrong without expert knowledge in the domain?
- Is the author's position sustainable if industry-wide adoption of LLMs changes what employers and clients expect as baseline productivity?
- Nov 2
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> When was the last time that they used an LLM?And also, which one? There is a very large difference between Google AI mode in the browser, Claude Sonnet, Claude Opus, running Qwen 3.x locally...even running the same version of Qwen 3.8 27B locally with different configuration can lead to wildly different results.
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I mean... this has been the most common response to pretty much all LLM criticism since GPT 3? I have yet to see any substantial critique of LLMs that isn't immediately met with "but have you tried the latest models? they're so much better now!"The article is also clear that it doesn't really matter whether the thing "works" or not - the process…
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My wife is a historian. She and her colleagues are generally skeptical of AI but have also given these tools serious attempts at improving their work. In the last six months she has made serious attempts to use these tools for paliography and transcription, identifying likely productive archives to visit, and for synthesizing the state of prior…
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The only thing that changes over time is that you need to know more about the topic in order to be able to spot it.
- Nov 1
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The author is clearly opposed to progress as hen does not use capital letters.I'm somewhat surprised that there are punctuation and spaces between words.It makes me wonder if there is a logical consistency
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Not everyone uses LLM to think.I will frequently ask LLM to do research. But I do that because I'm looking to learn from the process LLM implements, as well.This became a problem recently when I started using Opus 5.5 for a project. It is able to take hundreds of step to (apparently) flawlessly execute a large/complex part of spec. But very recent…
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author is describing the experience of someone with poor prompting skills. when my prompting was poor, I felt the same way. It’s GI-GO. I worked hard to improve my prompting, using a wider range of subject matter, and got a lot better at using the tool. I don’t have that experience ever now, and it was all about becoming a better tool-user.
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just starting to read all these; that specifically was both Claude Opus 4.8 and GPT 5.6 Sol and GPT 6 Astrathe main point of the article isn't this and a lot of people seem to be focusing on it though, it's me describing why i personally don't want to use an LLMand what i'm describing specifically there is the concept of the CoT and the tools it's…
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I'll call myself a late adopter. I tried early models and wasn't impressed, work has made some things available but wasn't forcing us so Ive been keeping my fingers on the pulse for a bit but watching from the sidelines. In October I decided to give it another shot and Opus 5.5 has blown me away, I've written a whole PR for a sparsely documented…
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This is always the first response to criticism of LLMs, and it's starting to feel banal, because it's a counter that you can pull reflexively from your back pocket at any time without engaging with the actual content of the criticism. I'm not saying it's wrong necessarily, but rather that the added information value of "have you tried GPT Cosmica…
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"for me, at least, the process of getting somewhere is more interesting then the end product." -- that's perfectly fine for a hobby, but not for an engineer job.
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The people I work with outsourcing their research to LLMs are doing wonders. The people I work with outsourcing the line-by-line level of coding to LLMs are hugely productive. It's honestly amazing to see what is possible.The people I work with outsourcing their thinking to LLMs are struggling, and if I'm not careful they're creating more work for…
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Last week I tried asking a frontier model a couple of basic questions about a (lower resource) language that I'm an expert on. It gave absolutely brutal, confidently wrong answers.
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They are still confidently wrong often. It’s harder to spot with Opus 5.5 effort medium+ but AI search overview is rife with this
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Why does that matter? The argument still stands, they are still dumb. We learned some ways to bypass the dumbness and automate some major workflows, and we still see them fail at random things.
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When as an industry you are collectively doing a trillion in CapEx every year, you are just going to do your best to brainwash the living hell out of everyone to adopt your crap because you really want your money back. Everyone (and their agency and their ability to think even) be damned. The consequences for society? Whatever. There's money you…
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i don't know how more people don't experience this, but staring at an llms output be confidently wrong eventually to get there in the process, or looking at the commands its running and see some really stupid things its doing drives me crazy to the point i will just stop it before it answers, i cannot handle something being that confidently wrong…
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I have the same thought on all these "I don't use AI" posts: I would like to not use an LLM too, but I'd soon be out of a job if I didn't. It's an exhausting place to be and I wish I were closer to retirement.
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Coding is now a lot like playing chess.It's been decades since beating the best computer at chess was possible. But people still play, because they find it fun to get better at.The major difference being that winning a chess game doesn't yield a permanent artifact that is useful, generally.It's fine this person wants to journal about the things…
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> don't know how more people don't experience this, but staring at an llms output be confidently wrong eventually to get there in the process, or looking at the commands its running and see some really stupid things its doing drives me crazy to the point i will just stop it before it answers, i cannot handle something being that confidently wrong…