Study mode

> But now, you're wondering if the answer the AI gave you is correct

> a healthy dose of scepticism is essential. Arguably, that applies to traditional learning methods too, but that's another story.

I don't think that is another story. This is the story of learning, no matter whether your teacher is a person or an AI.

My high school science teacher routinely mispoke inadvertently while lecturing. The students who were tracking could spot the issue and, usually, could correct for it. Sometimes asking a clarifying question was necessary. And we learned quickly that that should only be done if you absolutely could not guess the correction yourself, and you had to phrase the question in a very non-accusatory way, because she had a really defensive temper about being corrected that would rear its head in that situation.

And as a reader of math textbooks, both in college and afterward, I can tell you you should absolutely expect errors. The errata are typically published online later, as the reports come in from readers. And they're not just typos. Sometimes it can be as bad as missing terms in equations, missing premises in theorems, missing cases in proofs.

A student of an AI teacher should be as engaged in spotting errors as a student of a human teacher. Part of the learning process is reaching the point where you can and do find fault with the teacher. If you can't do that, your trust in the teacher may be unfounded, whether they are human or not.

To be honest I now see more hallucinations from humans on online forums than I do from LLMs.

A really great example of this is from on twitter constantly debunking human “hallucinations” all day.

Despite the name of "Generative" AI, when you ask LLMs to generate things, they're dumb as bricks. You can test this by asking them anything you're an expert at - it would dazzle a novice, but you can see the gaps.

What they are amazing at though is summarisation and rephrasing of content. Give them a long document and ask "where does this document assert X, Y and Z", and it can tell you without hallucinating. Try it.

Not only does it make for an interesting time if you're in the World of intelligent document processing, it makes them perfect as teaching assistants.

My favourite story of that involved attempting to use LLM to figure out whether it was true or my hallucination that the tidal waves were higher in Canary Islands than in Caribbean, and why; it spewed several paragraphs of plausibly sounding prose, and finished with “because Canary Islands are to the west of the equator”.

This phrase is now an inner joke used as a reply to someone quoting LLMs info as “facts”.

Please check this excellent LLM-RAG AI-driven course assistant at UIUC for an example of university course [1]. It provide citations and references mainly for the course notes so the students can verify the answers and further study the course materials.

[1] AI-driven chat assistant for ECE 120 course at UIUC (only 1 comment by the website creator):

https://news.ycombinator.com/item?id=41431164

I often ask first, "discuss what it is you think I am asking" after formulating my query. Very helpful for getting greater clarity and leads to fewer hallucinations.

> you're wondering if the answer the AI gave you is correct or something it hallucinated

Regular research has the same problem finding bad forum posts and other bad sources by people who don't know what they're talking about, albeit usually to a far lesser degree depending on the subject.

You should practice healthy skepticism with rubber ducks as well:

https://en.wikipedia.org/wiki/Rubber_duck_debugging

So instead of correcting the teachers with better training, we retreat from education and give it to technocrats? Why are we so afraid of punishing bad, unproductive, and even illegal behavior in 2025?

You might also be working with very uncooperative coworkers, or impatient ones

And also taught people how to actually look for information online. The average person still does not know how to google, I still see people writing whole sentences in the search bar.

It didn’t. Only frustrated and slowed down students.

> [Trawling around online for information] trained and sharpened invaluable skills involving critical thinking and grit.

Here's what Socrates had to say about the invention of writing.

> "For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem [275b] to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise."

https://www.historyofinformation.com/detail.php?id=3439

I mean, he wasn't wrong! But nonetheless I think most of us communicating on an online forum would probably prefer not to go back to a world without writing. :)

You could say similar things about the internet (getting your ass to the library taught the importance of learning), calculators (you'll be worse at doing arithmetic in your head), pencil erasers (https://www.theguardian.com/commentisfree/2015/may/28/pencil...), you name it.

I sometimes intentionally ask naive questions, eve if I think I alredy know the answer. Sometimes the naive question provokes a revealing answer that I have not even considered. Asking naive questions is a learning hack!

billions on tech but not on making sure teachers can pay rent. Even the prestige or mission oriented structure of teaching has been weathered over the decades as we decided to shame teachers as government funded babysitters instead of the instructors of our future generations.

Truly a mystery why America is falling behind.

The article states that Study Mode is free to use. Regardless of b2b costs, this is free for you as an individual.

This is endlessly brought up as if the human operating the tool is an idiot.

I agree that if the user is incompetent, cannot learn, and cannot learn to use a tool, then they're going to make a lot of mistakes from using GPTs.

Yes, there are limitations to using GPTs. They are pre-trained, so of course they're not going to know about some easter egg in DDG. They are not an oracle. There is indeed skill to using them.

They are not magic, so if that is the bar we expect them to hit, we will be disappointed.

But neither are they useless, and it seems we constantly talk past one another because one side insists they're magic silicon gods, while the other says they're worthless because they are far short of that bar.

I've found it excels at some things:

1) The broad overview of a topic

2) When I have a vague idea, it helps me narrow down the correct terminology for it

3) Providing examples of a particular category ("are there any examples of where v1 in the visual cortex develops in a disordered way?")

4) "Tell me the canonical textbooks in field X"

5) Posing math exercises

6) Free form branching--while talking about one topic, I want to shift to another that is distinct but related.

I agree they leave a lot to be desired when digging very deeply into a topic. And my biggest pet peeve is when they hallucinate fake references ("tell me papers that investigate this topic" will, for any sufficiently obscure topic, result in a bunch of very promising paper titles that are wholely invented).

It's a floor raiser, not a ceiling raiser. It helps you get up to speed on general conventions and consensus on a topic, less so on going deep on controversial or highly specialized topics

My core problem with LLMs is as you say; it's good for some simpler concepts, tasks, etc. but when you need to dive into more complex topics it will oversimplify, give you what you didn't ask for, or straight up lie by omission.

History is a great example, if you ask an LLM about a vaguely difficult period in history it will just give you one side and act like the other doesn't exist, or if there is another side, it will paint them in a very negative light which often is poorly substantiated; people don't just wake up and decide one day to be irrationally evil with no reason, if you believe that then you are a fool... although LLMs would agree with you more times than not since it's convenient.

The result of these things is a form of gatekeeping, give it a few years and basic knowledge will be almost impossible to find if it is deemed "not useful" whether that's an outdated technology that the LLM doesn't seem talked about very much anymore or a ideological issue that doesn't fall in line with TOS or common consensus.

I really think that 90% of such comments come from a lack of knowledge on how to use LLMs for research.

It's not a criticism, the landscape moves fast and it takes time to master and personalize a flow to use an LLM as a research assistant.

Start with something such as NotebookLM.

> Also, god forbid you're researching a complex and possibly controversial subject and you want it to find reputable sources or particularly academic ones.

That's fine. Recognize the limits of LLMs and don't use them in those cases.

Yet that is something you should be doing regardless of the source. There are plenty of non-reputable sources in academic libraries and there are plenty of non-reputable sources from professionals in any given field. That is particularly true when dealing with controversial topics or historical sources.

IT can be beneficial for making your initial assessment, but you'll need to dig deeper for something meaningful. For example, I recently used Gemini's Deep Research to do some literature review on educational Color Theory in relation to PowerPoint presentations [1]. I know both areas rather well, but I wanted to have some links between the two for some research that I am currently doing.

I'd say that companies like Google and OpenAI are aware of the "reputable" concerns the Internet is expressing and addressing them. This tech is going to be, if not already is, very powerful for education.

[1] http://bit.ly/4mc4UHG

Grandparent testimony of success, & parent testimony of frustration, are both just wispy random gossip when they don't specify which LLMs delivered the reported experiences.

The quality varies wildly across models & versions.

With humans, the statement "my tutor was great" and "my tutor was awful" reflect very little on "tutoring" in general, and are barely even responses to each other withou more specificity about the quality of tutor involved.

Same with AI models.

“The deeper I go, the less it seems to be useful. This happens quick for me. Also, god forbid you're researching a complex and possibly controversial subject and you want it to find reputable sources or particularly academic ones.”

These things also apply to humans. A year or so ago I thought I’d finally learn more about the Israeli/Palestinians conflict. Turns out literally every source that was recommended to me by some reputable source was considered completely non-credible by another reputable one.

That said I’ve found ChatGPT to be quite good at math and programming and I can go pretty deep at both. I can definitely trip it into mistakes (eg it seems to use calculations to “intuit” its way around sometimes and you can find dev cases where the calls will lead it the wrong directions), but I also know enough to know how to keep it on rails.

And the old ChatGPT was nothing compared to what we have today, nowadays reasoning models will eat through math problems no problem when this was a major limitation in the past.

I learned Rust in a couple of weeks by reading the book.

Now this is a ringing endorsement. Specific stuff you learned, and actual proof of the outcome.

(Only thing missing is the model(s) you used).

yes Chat GPT has helped me learn about actix web a framework similar to FastAPI in rust.

Would you say you were using the LLM as a tutor or as tech support, in that instance?

what was broken on it?

"Keep paving forward" can sometimes be fruitful, and at other times be an absolutely massive waste of time.

I'm not sold on LLMs being a replacement, but post-secondary was certainly enriched by having other people to ask questions to, people to bounce ideas off of, people that can say "that was done 15 years ago, check out X", etc.

There were times where I thought I had a great idea, but it was based on an incorrect conclusion that I had come to. It was helpful for that to be pointed out to me. I could have spent many months "paving forward", to no benefit, but instead someone saved me from banging my head on a wall.

In college sometimes asking the right question in class or in a discussion section led by a graduate student or in a study group would help me understand something. Sometimes comments from a grader on a paper would point out something I had missed. While having the diligence to keep at it until you understand is valuable, the advantage of college over just a pile of textbooks is in part that there are other resources that can help you learn.

Imagine you're in college, have to learn calculus, and you can't afford a textbook (nor can find a free one), and the professor has a thick accent and makes many mistakes.

Sure, you could pave forward, but realistically, you'll get much farther with either a good textbook or a good teacher, or both.

In college you can ask people who know the answer. It's not until PhD level that you have to struggle without readily available answers.

The main difference in college was that there were office hours

Yeah these chatbots are by default geared towards doing your work for you instead of filling the gaps in your knowledge (something they would be excellent at). I feel it must be symptomatic of the vision these vendors have for their products, one of fully autonomous replacements for workers rather than of tools to enhance the worker.

This was in the linked prompt: "Be warm, patient, and plain-spoken; don't use too many exclamation marks or emoji. [...] And be brief — don't ever send essay-length responses. Aim for a good back-and-forth."

I was under the impression that, at least for models without "reasoning", asking them to be terse hampered their ability to give complete and correct answers? Not so?

Anthropic has a "style" choice, one of which is "concise"

On ChatGPT at least, you can add "be brief" to the custom prompt in your settings. Probably others, too.

Hah, yeah I'd love to know if OpenAI ran evals that were fine-grained enough to prove to themselves that putting that bit in capitals made a meaningful difference in how likely the LLM was to just provide the homework answer!

I've found that a lot of prompt engineering boils down to managing layers of emphasis. You can use caps, bold, asterisks, precede instructions with "this is critically important:", and so on. It's also often necessary to repeat important instructions a bunch of times.

How exactly you do it is often arbitrary/interchangeable, but it definitely does have an effect, and is crucial to getting LLMs to follow instructions reliably once prompts start getting longer and more complex.

Just wait until it only responds to **COMMAND**!

I just tried in AI Studio (https://aistudio.google.com/) where you can for free use 2.5 Pro and edit the system prompt and it did very well.

That kind of thing is surprisingly hard to implement. To date I've not seen any provider been caught serving up a fake system prompt... which could mean that they are doing it successfully, but I think it's more likely that they determined it's not worth it because there are SO MANY ways someone could get the real one, and it would be embarrassing if they were caught trying to fake it.

Tokens are expensive. How much of your system prompt do you want to waste on dumb tricks trying to stop your system prompt from leaking?

I like the idea but that seems complex to put in place and would risk degrading the perfs.

You can test this prompt yourself elsewhere, you will notice that you get sensibly the same experience.

That was relevant when you were learning to search through “information” for the answer to your question, eg the digital version of going through the library or digging through a reference book.

I don’t think it’s so valuable now that you’re searching through piles of spam and junk just to try find anything relevant. That’s a uniquely modern-web thing created by Google in their focus of profit over user.

Unless Google takes over libraries/books next and sells spots to advertisers on the shelves and in the books.

Searching is definitely a useful skill, but once you've been doing it for years you probably don't need the constant practice and are happy to avoid it.

yeah this is literally why I built -- app.ubik.studio -- searching is everything, and understanding what you are reading is more important than conversing with a chatbot. i cannot even imagine being a student in 2025, especially at 14 years old omg would be so hard not to just cheat on everything

I think this account is a bot.

> It doesn’t do any of that

Not to be contrarian, but do you have any evidence of this assertion? Or are you just confidently confabulating a response for something outside of the data you've been exposed to? Because a commentor below provided a study that directly contradicts this.

Such a smart play.

Bingo. The scale they're operating at, new features don't have to be useful, they only need to look like they are for the first few minutes.

I wonder how much this was a factor:

"The occurrence of inaccurate “hallucinations” by the current [LLMs] poses a significant challenge for their use in education. [...] we enriched our prompts with comprehensive, step-by-step answers, guiding the AI tutor to deliver accurate and high-quality explanations (v) to students. As a result, 83% of students reported that the AI tutor’s explanations were as good as, or better than, those from human instructors in the class."

Not at all dismissing the study, but to replicate these results for yourself, this level of gain over a classroom setting may be tricky to achieve without having someone make class materials for the bot to present to you first

Edit: the authors further say

"Krupp et al. (2023) observed limited reflection among students using ChatGPT without guidance, while Forero (2023) reported a decline in student performance when AI interactions lacked structure and did not encourage critical thinking. These previous approaches did not adhere to the same research-based best practices that informed our approach."

Two other studies failed to get positive results at all. YMMV a lot apparently (like, all bets are off and your learning might go in the negative direction if you don't do everything exactly as in this study)

The study you're referencing doesn't make that conclusion.

It concludes theres a learning curve that generally takes about 50 hours of time to figure out. The data shows that the one engineer who had more than 50 hours of experience with Cursor actually worked faster.

This is largely my experience, now. I was much slower initially, but I've now figured out the correct way to prompt, guide, and fix the LLM to be effective. I produce way more code and am mentally less fatigued at the end of each day.

I presume you're referring to the recent METR study. One aspect of the study population, which seems like an important causal factor in the results, is that they were working in large, mature codebases with specific standards for code style, which libraries to use, etc. LLMs are much better at producing "generic" results than matching a very specific and idiosyncratic set of requirements. The study involved the latter (specific) situation; helping people learn mainstream material seems more like the former (generic) situation.

(Qualifications: I was a reviewer on the METR study.)

*slower with Sonnet 3.7 on large open source code bases where the developer is a senior member of the project core team.

https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...

I believe we'll see the benefits and drawbacks of AI augmentation to humans performing various tasks will vary wildly based on the task, the way the AI is being asked to interact, and the AI model.

People keep citing this study (and it was on the top of HN for a day). But this claim falls flat when you find out that the test subjects had effectively no experience with LLM equipped editors and the 1-2 people in the study that actually did have experience with these tools showed a marked increase in productivity.

Like yeah, if you’ve only ever used an axe you probably don’t know the first thing about how to use a chainsaw, but if you know how to use a chainsaw you’re wiping the floor with the axe wielders. Wholeheartedly agree with the rest of your comment; even if you’re slow you lap everyone sitting on the couch.

It was a 16 person study on open source devs that found 50 hours of experience with the tool made people more productive

Thanks for introducing me to the verb Sherlock! I'm one of today's lucky 10,000.

> In the computing verb sense, refers to the software Sherlock, which in 2002 came to replicate some of the features of an earlier complementary program called Watson.[1]

[1] https://en.wiktionary.org/wiki/Sherlock

But what’s the future in terms of profitability of LLM providers?

As long as features like Study Mode are little more than creative prompting, any provider will eventually be able to offer them and offer token-based charging.

Does https://en.wikipedia.org/wiki/Sherlock_(software)#Sherlocked... count? (Edit: Missed I wasn't the first to post this in a sibling.)

Claude Code and Gemini-CLI are able to offer much more value compared to startups (like Cursor) that need to pay for model access, largely due to the immense costs involved.

There’s a case for a start up to capture enough market that LLM providers would just buy it out. Think of CharacterAI case.

They originally claimed they wouldn’t as to not compete with their API users…

yeah, if you want to stick around you need some kind of moat

This looks super cool—I've imagined something similar, especially the skill tree/knowledge map UI. Looking forward to trying it out.

Have you considered using the LLM to give tests/quizzes (perhaps just conversationally) in order to measure progress and uncover weak spots?

> present knowledge as a tree that you can expand to get deeper

I'm very interested in this. I've considered building this, but if this already exists, someone let me know please!