So I guess everyone uses LLMs to think now

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 project and was like write the PR description for me with like one sentence of background, no Claude.md, no context other than the repo and it completely nailed the description. Most of my apps are in the tens of thousands of lines, so nothing huge but still the capabilities of the frontier models is crazy good. They've come a long way from even a year ago.

Last week and tonight I tried asking a frontier model a couple of basic questions about a language with 60-70 million speakers with that I'm an expert on. It gave absolutely brutal, confidently wrong answers. It was completely confused and about the basic structure of the language.

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 15" in a discussion on LLMs is approaches zero. Because it's such a generically applicable response.

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 Google

2. 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 for.

3. ChatGPT free tier.

For a while you’d find someone who got assigned an AI tool at work but their administrator limited them to the cheapest model for cost savings, but most companies are wising up.

I also talked to a developer last month whose company had never let them use anything beyond Sonnet. When I told him I used Opus for everything his eyes went wide because he assumed I was spending thousands of dollars per month. However now that the latest Sonnet is very good, even this category of exposure is decreasing.

I think in 2027 as advanced models become more common we’ll see less of these claims about AI not working well when they tried it. There will be holdout group of people who refuse to try anything new, but the world is moving on.

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

I think the places the average person starts out with AI do look like this. Most people are not paying a $20 a month Anthropic subscription just to try it out. They're using free chat apps, reading the garbage llm summary Google puts at the top of every search page, dealing with the low quality tools foisted on them in their email app or word processor.

Have all these gotten a lot better in the last year? Sure! But there's still a several-orders-of-magnitude difference in quality between whatever garbage tier of GPT-6 Luna you can use for free on `duck.ai` (just for one example) and Opus 5.5. Or even GLM 5.3 Flash. It's a way bigger difference than the improvement in ~free models has made up for in the last year, even though those improvements have been substantial.

I think a certain sort of person, if they do try to use something better along with a coding harness, as also immediately inclined to read along with the reasoning traces - and understandably gets freaked out by the nonsense it contains. That's a mistake, I think; not just because models behaving "reasonably" doesn't depend on the rationality of their reasoning traces, but also because I think if you transcribed my brain activity into a serial stream of text, I'm not convinced it would be more coherent.

just starting to read all these; that specifically was both Claude Opus 4.8 and GPT 5.6 Sol and GPT 6 Astra

the 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 LLM

and what i'm describing specifically there is the concept of the CoT and the tools it's executing. i see it doing something stupid and my instinct is to stop it, it does usually eventually get there in the end

as i point out right below, llms are super powerful. i'm not arguing that. i'm arguing that we should stop disregarding ethics for marketing and also generally have fun ourselves without llms in personal projects (not work) specifically.

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.

How long until people genuinely don’t know how to check if the LLM is wrong?

(I use LLMs for lots of things. They’re useful for lots of things. Gemini 3.8 also feeds me lines of complete bullshit every couple of days.)

I've been on leave and since my work subscription would go to waste otherwise I've decided to go completely silly and vibecode (truly vibecode) a big project from scratch. Opus 5.5 with xhigh reasoning was repeated firing off hour-long test runs, of tests it had written itself from scratch on code it had written from scratch, until I finally noticed and said "hey, couldn't we run some of these in parallel?" and then the execution time dropped to under 10 minutes. So yes, even recent models do utterly stupid shit pretty frequently (this isn't the only example from this project, but it's the easiest to explain)

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.

> It's been decades since beating the best computer at chess was possible.

LLMs can do an impressive job of writing code that meets some specification-but they still can’t beat humans at deciding what that specification should be. That’s especially true when it comes to non-functional requirements, e.g. what constitutes good coding style or good architectural choices.

> The major difference being that winning a chess game doesn't yield a permanent artifact that is useful, generally.

Chess has a single clearly defined “win condition”; coding doesn’t.

> They clearly aren't writing for others to read their work.

I don't know, the prose and material is fine in my opinion. I do find the uncapitalized style a bit weird, but it's not something that stops me from reading it.

I still write better code than LLMs. It's just slower, and the quality difference is not usually worth the human effort.

i'm not gonna let my typing style be criticised when it's been a typing style i've used for previous very popular (even on HN!) articles about vuln research.

it's a choice of typing this way, i don't like typing super formally, just not my thing, i'd rather type casually and most of my articles are sort of braindumps of what i think as i go, but historically i've been complemented very much on this style and i like doing it

>They clearly aren't writing for others to read their work.

The author of the blog post and the OP who submitted the article are the same person.

but also, throw a weird variation of the game at the computer and it falls apart. Need something novel? llm's wont cut it. Doubly so if what is being done goes against established conventions, even if those are demonstrably wrong, to keep an llm from undermini g everything you first need to show it all the proof and evidence before it can be trusted to help, which for a complex problem can eaisly be 30-50% of co text limits.

LLM's are good at solved problems applied to known or similar to known applications, otherwise they're not going to match humans.

I feel like the AI backlash is creating a rise in "authenticity signaling", cheap public displays of not using AI. Much like virtue signaling, it's lacking in substance and presents as an annoying affectation to people outside of the target in-group.

I guess it's a way to convey informality and rejection of "the norm" sacrificing legibility.

It's probably a way to express freedom, like the freedom of just refusing to consume unreadable walls of text that disrespect the reader. Freedom goes both ways.

The journal is about a thing this person does privately for fun.

The writing style is clearly not meant for others to read either. They just did stream of consciousness out of their brain and didn't proofread. It's not meant for external consumption.

Capitalization is something you do out of respect for your reader, to make things easier for them. If you aren't intending others to read your writing, then there's no one to disrespect, so why bother?

.and some are putting the dot at the beginning of sentences with all lower case, like in Lojban .it makes much more sense if you think about it

(but i'm half joking here. normally i just don't capitalize, only the names.)

Let's say the average sentence is 17.5 words, with the average word length being 4.5 characters. Not capitalizing the first word is only a 1.27% character error rate, on average. Not too bad. ;)

it's an intentional display of informality by the writer, i imagine. i do the same a lot of the time.

I guess we’re so used to autocorrect doing that, so that disabling it is a flex now?

that's model talk! get 'im boys!

The people who have this "hobby" attitude of really appreciating the well made steps are the ones that are making deep advances and truly solid things that are used in the long term.

Not at all. We have lots of products (corrugated steel, yoghurt, microwave ovens) that were part of the process of getting somewhere (else) and became the end product. Lots of engineers involved.

as pointed out in the conclusion! that is about specifically the fact even an engineer, who i assume got into this job because they liked doing it as a hobby, should still have some fun with engineering in their personal projects themselves instead of offloading it to an LLM.

i agree that LLM use in work as a software engineer is fully inevitable at this point, because we are all expected to move so fast

i mean; no, this isn't the conclusion i want someone to takeaway from this article. the part about me not wanting to use LLMs again is purely so i stop getting the question of "why don't you?" and having to explain each time

the takeaway i want is a. i would like people to still have fun and tinker around with things in their personal time instead of making an LLM do it all themselves b. i think we should stop compromising ethics for marketing

> i cannot handle something being that confidently wrong

I don’t know how these people have stayed so oblivious to it happening all around them for decades. LLMs didn’t invent it.

My work pays me the same if I kick off a Codex session and go practice guitar. My workflow now is like, prompt LLM, answer some emails or review some code, get a coffee, see what it barfed out.

> (even though it'll probably still get there in the end)

Burning up tokens/credits needlessly as it does so. That might be a non-issue for people using LLMs through their work but as someone doing AI on a limited budget that's an issue that drives me up a tree!

I'd argue the improvement has come not so much from fixing hallucinations, but more in getting LLMs to successfully run for longer, which lets them more effectively fix their own hallucinations. This is still an improvement, but at the cost of bigger models, with more tokens, running for longer.

I'd be interested to see benchmarks for this sort of thing plotted against cost, power usage, and elapsed time. If these are all sub-linear then that's great, but if some aren't that could be a real problem for LLMs in the long run.

fully responded to with a comment above but, Claude Opus 4.8, GPT 5.6 Sol and GPT 6 Astra

also, they all get there in the end (as mentioned), but the CoT and command calls and tool calls they do get to me and my instinct is to just stop it right there

the takeaway i want isn't my personal reason on why i don't use ai but rather why people should still not use ai for personal projects, or hobbies. to have fun tinkering with things and coding still, outside of work!

No? LLMs have been outputting more text ever since chain of thought became a thing, and multiple researchers shown thinking traces are outright confabulations, only serving as more memory for latent processing. The tool calls too I believe have gotten more frequent since labs reward tool use regardless of practical value. The net effect is more total intermediate bullshit, even with more results.

OpenAI's harness can solve frontier math problems but the model alone is still a clofabulation machine. Its "intuition" did for a while get better from sheer scale, but we reached the optimum frontier for non-thinking models years ago.

In which ways are you forced to use it though?

as mentioned in the article; i totally get using llms for work, but for personal projects i think you should spend some time to tinker with it yourself

Author goes by it/she

The bad keys weren't added to the Chrome trusted certs. They were intermediate keys, signed by a key that was trusted.

You joke but when I first picked up C, I did find it quite helpful to write it in a plain text editor and write my own Makefiles to understand what project setup the IDEs would abstract away - our uni also had pen-and-paper exams where relying on autocomplete would have been difficult :)

(Likewise I can see "you should have read through your generated code and understood the key points yourself" becoming the rule of thumb for keeping maintainers accountable in a project, keeping the pace of changes manageable, and keeping the codebase from becoming a rat's nest _only_ agents can work with)

If you think it's more fun that way, sure. Sometimes (often?) satisfaction is about friction.

And I've seen the /s, but your comment seems to mock OP's point more than just trying to be funny.

Even if we're in the same boat, I'm now actually cheering for AI replace my job, purely so people like you will be out on the streets with me and my "I told you so".