GPT-5 Thinking in ChatGPT (a.k.a. Research Goblin) is good at search

Yeah trying to make well-researched buying decisions for example is really hard because you'll just quite a lot of opinions dominated by marketing material, which aren't well counterbalanced by the sort of angry Reddit posts or YouTube comments I'd often treat as red flags.

I tried to use perplexity to find ideal settings for my monitor, it responded with concise list of distinct settings and why. When I investigated the source it was just people guessing and arguing with each other in the Samsung forums, no official or even backed up information.

I'd love if it had a confidence rating based on the sources it found or something, but I imagine that would be really difficult to get right.

> I’ve found ChatGPT and other LLMS can struggle to evaluate evidence - to understand the biases behind sources - ie taking data from a sketchy think tank as gospel.

This is what I keep finding, it mostly repeats surface level "common knowledge." It usually take a few back and forths to get to whether or not something is actually true - asking for the numbers, asking for the sources, asking for the excerpt from the sources where they actually provide that information, verifying to make sure it's not hallucinating, etc. A lot of the time, it turns out its initial response was completely wrong.

I imagine most people just take the initial (often wrong) response at face value, though, especially since it tends to repeat what most people already believe.

FWIW GPT-5 (and o3, etc.) is one of the most critical-minded LLMs out there.

If you ask for information which is e.g. academic or technical it would cite information and compare different results, etc, without any extra prompt or reminder.

Grok 4 (at the initial release) was just reporting information in the articles it found without any analysis.

Claude Opus 4 also seems bad: I asked it to give a list of JS libraries of a certain kind in deep research mode, and it returned a document focused on market share and usage statistics. Looks like it stumbled upon some articles of that kind and got carried away by it. Quite bizarre.

So GPT-5 is really good in comparison. Maybe not perfect in all situations, but perhaps better than an average human

How are we feeling about the usage of the word research to indicate feature sets in LLMs? Is it truly representative of research? How does it compare to the colloquial “do your research” refrain used often during US election years?

> I always ask ChatGPT do directly cite and evaluate sources. And try to get it in the mindset of comparing and contrasting arguments for and against. And I find I must argue against its points to see how it reacts.

Same here. But it often produces broken or bogus links.

You make a great point “research” isn’t just searching but weighing different kinds of evidence and understanding the biases behind them. I agree LLMs often fall short here, especially with statistics or nuanced reasoning, where they can hallucinate or lean too hard into confirmation. I’ve also seen the sycophancy effect you mention the model tends to agree with whatever frame it’s given. Asking for direct citations and then challenging the model’s arguments, like you do, seems like a smart way to push it toward more balanced and critical responses.

I'm going to somewhat disagree based on my recent attempts.

Firstly, if we don't remove the Google AI summary then as you rightly say, it makes the experience 10x worse. They try to still give an answer quickly, but the AI takes up a ton of space and is mostly terrible.

Googling for a Github repository just now, Google linked me to 3 resources except the actual page. One clone that was named the same, another garbage link but luckily the 3rd was a reddit post by the same person which linked to the correct page.

GPT does take a lot longer, but the main advantage for me comes in depending on the scope of what you're looking for. In the above example I didn't mind Google, because the 3 links opened fast and I could scan and click through to find what I was looking for, ie. I wanted the information right now.

But then let's say I'm interested in something a bit deeper, for example how did they do the unit movement in StarCraft 2? This is a well known question, so the links/info you get from either Google or GPT are all great. If I was searching this topic via Google I'd then have to copy or bookmark the main topics to continue my research on them. Doing it via GPT it returns the same main items, but I can very easily tell it to explain all those topics in turn, have it take the notes, find source code, etc.

Of course as in your example, if you're a Doctor and you're googling symptoms or perhaps real world location of ABC then the hallucination specter is a dangerous thing which you want to avoid at all costs. But for myself I find that I can as easily filter LLM mistakes as I can noise/errors from manual searches.

My future Internet guess is going to be that in N years there will be no such thing as manually searching for anything, everything will be assistant driven via LLM.

Agree. I tried the first 3 examples:

* "Rubber bouncy at Heathrow removal" on Google had 3 links, including the one about SFO from which chatGPT took a tangent. While ChatGPT provided evidence for the latest removal date being of 2024, none was provided for the lower bound. I saw no date online either. Was this a hallucination?

* A reverse image lookup of the building gave me the blog entry, but also an Alamy picture of the Blade (admittedly this result can have been biased by the fact the author already identified the building as the blade)

* The starbucks pop Google search led me to https://starbuckmenu.uk/starbucks-cake-pop-prices/. I will add that the author bitching to ChatGPT about ChatGPT hidden prompts in the transcript is hilarious.

I get why people prefer ChatGPT. It will do all the boring work of curating the internet for you, to privde you with a single answer. It will also hallucinate every now and then but that seems to be a price people are willing to pay and ignore, just like the added cost compared to a single Google search. Now I am not sure how this will evolve.

Back in the days, people would tell you to be weary of the Internet and that Wikipedia thing, and that you could get all the info you need from a much more reliable source at the library anyways, for a fraction of the cost. I guess that if LLMs continue to evolve, we will face the same paradigm shift.

As a counterpoint I asked that simple question to gpt5 in auto mode and it started replying in two seconds, wrote fast enough for me to scan the answer and gave me two solid links to read after.

With thinking it took longer (just shy of two minutes) but compared a variety of different sources, and comes back with numbers and each statement in the summary sourced.

I’ve used gpt a bunch for finding things like bin information on the council site that I just couldn’t easily find myself. I’ve also sent it off to dig through prs, specs and more for matrix where it found the features and experimental flags required to solve a problem I had. Reading that many proposals and checking what’s been accepted is a massive pain and it solved this while I went to make a coffee.

I suggest trying that experiment again but picking the hardest of my examples to answer with Google, not the easiest.

I wonder how all this will really change the web. In your manual mode, you a human, are viewing and visiting webpages, but if one never needs to and always interacts with the web through an agent, what does the web need to look like, and will people even bother making websites? Interesting times ahead.

V nice post. Captures my sentiment too

First, you not having to spend the 60 seconds and it means you can parallelize it with something else to get the answer effectively instantly. Second, you're essentially establishing that if an LLM can get it done in less than 60 seconds its better than your manual approach, which is a huge win, as this will get faster!

When it comes to Information Retrieval, you can get anything between links to existing documents or generated content based on those processed information. I agree that the second one is really powerfuly and just amazing and seemilngly useful. But the fact that it can also be wrong in more cases and I won't know keep being reminded to my using it for things I'm not good at and they just don't work s they should.

I just wish the business models could justify a confidence level being attached to the response.

More recently, I find ChatGPT to become increasingly unreliable. It makes up almost every second answer, forgets context, or is just downright wrong. Maybe I am used these days more and more to dump huge texts for context into the prompt, as aistudio allows me. Maybe ChatGPT isn't as good as with such information. Gemini/Aistudio will stay on track even with 300k tokens consumed, it just needs a little nudge here and there.

This isn't really how you described. You have an opinion that conflicts with the research literature. You published a blog about that opinion, and you want ChatGPT to say you're to accept your view.

Your view is grinding a political axe and I don't think you're in a position to objectively assess whether ChatGPT failed in this case.

Yes, this is very much my experience too.

Switching to GPT5 Thinking helps a little, but it often misses things that it wouldn't when I was using o3 or o1.

As an example, I asked it if there were any incidents involving Botchan in an Onsen. This is a text that is readily available and must have been trained on; in the book, Botchan goes swimming in the onsen, and then is humiliated when the next time he comes back, there is a sign saying "No swimming in the Onsen".

According to GPT5 it gives me this, which is subtly wrong.

> In the novel, when Botchan goes to Dōgo Onsen, he notes the posted rules of the bath. One of them forbids things like: > “No swimming in the bath.” (泳ぐべからず) > “No roughhousing / rowdy behavior.” (無闇に騒ぐべからず) > Botchan finds these signs funny because he’s exactly the sort of hot-headed, restless character who might be tempted to splash around or make noise. He jokes in his narration that it seems as though the rules were written specifically to keep people like him out.

Incidentally, Dogo Onsen still has the "No swimming sign", or it did when I went 10 years ago.

I found your article interesting and it is relevant to the discussion. To be honest, while I think GPT could have performed better here, I think there is something to be said about this:

There is value in pruning the search tree because the deeper nodes are usually not reputable. I know you have cause to believe that "Wilhelm Matzat" is reputable but I don't think it can be assumed generally. If you were to force GPT to blindly accept counter points from people - the debate would never end. And there has to be a pruning point at which GPT would accept this tradeoff: maybe the less reputable or well known sources may have a correct point at the cost of being incorrect more often due to taking an incorrect analysis from a not well known source.

You could go infinitely deep into any analysis and you will always have seemingly correct points on both sides. I think it is valid for GPT to prune the search at a point where it converges to what society at large believes. I'm okay with this tradeoff.

I feel the opposite. Before I can use information from a model's "internal" knowledge I have to engage in independent research to verify that it's not a hallucination.

Having an LLM generate search strings and then summarize the results does that research up front and automatically, I need only click the sources to verify. Kagi Assistant does this really well.

I kept search off for a long time due to it tanking the quality of the responses from ChatGPT.

I recently added the following to my custom instructions to get the best of both worlds:

# Modes

When the user enters the following strings you should follow the following mode instructions:

1. "xz": Use the web tool as needed when developing your answer.

2. "xx": Exclusively use your own knowledge instead of searching the internet.

By default use mode "xz". The user can switch between modes during a chat session. Stay with the current mode until the user explicitly switches modes.

There is a tradeoff here: the non search models are internally heavy but the search models are light but also depend on real data.

I keep switching between both but I think I'm starting to prefer the lighter one that is based on the sources instead.

These models are still available: GPT-4.5, Gemini 2.5 Pro (at least the initial version - not sure if they optimized it away).

From what I can tell, they are pretty damn big.

Grok 4 is quite large too.

I think this is partially something I have felt myself as well. It would be interesting if these lighter web search models would highlight the distinction between information that has been seen elsehwere vs information that is novel for each page? Like, a view that lets me look at the things that have been asserted and see how many of the different pages show those facts asserted (vs unmentioned vs contradicted).

Most real knowledge is stored outside the head, so intelligent agents can't rely solely on what they've remembered. That's why libraries are so fundamental to universities.

"encyclopedic knowledge"

Have you just hallucinated that?

> an incredibly detailed answer and a believable range.

Recently, I started returning even more verbose answers. The absolute bullshit research paper that Google Gemini gives you is what turned me away from using it there. Now, chatGPT also seems to go for more verbose filler rather than actually information. It is not as bad as Gemini, but I did notice.

It makes me wonder if people think the results are more credible with verbose reports like that. Even if it actually obfuscates the information you asked it to track down to begin with.

I do like how you worded it as a believable range, rather than an accurate one. One of the things that makes me hesitant to use deep research for anything but low impact non-critical stuff is exactly that. Some answers are easier to verify than others, but the way the sources are presented, it isn't always easy to verify the answers.

Another aspect is that my own skills in researching things are pretty good, if I may so myself. I don't want them to atrophy, which easily happens with lazy use of LLMs where they do all the hard work.

A final consideration came from me experimenting with MCPs and my own attempts at creating a deep research I could use with any model. No matter the approach I tried, it is extremely heavy on resources and will burn through tokens like no other.

Economically, it just doesn't make sense for me to run against APIs. Which in my mind means it is heavily subsidized by openAI as a sort of loss-leader. Something I don't want to depend on just to find myself facing a price hike in the future.

Did you check the facts? Did you click through all the links and see what the sources are?

A while ago I bragged at a conference about how ChatGPT had "solved" something... Yeah, we know, it's from Wikipedia and it's wrong :)

the thing about students who cheat is most of them are (at least in the context of schoolwork) very lazy and don't care if their work is high quality. i would guess waiting multiple minutes for Thinking mode to give thorough results is very unappealing. 4o or 4o-mini was already good enough for their purposes.

I was amused that it used the neologism 'steel-man' -- redundantly, too.

Idea: workshops for teachers that teach them some kind of Socratic method that stimulates kids to support what they got from G with their own thinking, however basic and simple it may be.

Formulating the state of your current knowledge graph, that was just amplified by ChatGPT's research might be a way to offset the loss of XP ... XP that comes with grinding at whatever level kids currently find themselves ...

I like Brave but have found their search to be awful. The AI stuff seems decent enough, but the results populated below are just never what I'm looking for.

The thing is, with Chat+Search you don't have to click various links, sift through content farms, or be subject to ads and/or accidental malware download.

With the walls of low quality sites optimized for SEO these days? Call me unconvinced

It's not the Deep Search or Agent Mode.

I select "GPT-5 Thinking" from the model picker and make sure its regular search tool is enabled.

In my experience it’s “search Reddit and combine comments”.

Don't forget about the "ChatGPT 5 Pro" too :) which is a bit like Deep Research but not quite?

I believe this is just the normal mode. In my experience, you don't have to select the web search option to make it search the web. I wonder why they have web search as an option at this point (to force the llm to search?)

I have a feeling this is just ChatGPT 5 in thinking mode, with web search enabled at a profile level at least. Even without that, any indication for recent data or research and thinking will prompt it to think+research quite a bit, ie deep research.