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All this demonstrates how non-sticky all this tech really is. When your product is basically just an API call it’s trivial to just swap you out for someone else. As such it’s unclear what the prize at the end of the present race to the bottom is.
We swapped OpenAI out for Claude and it required updating about 15 lines of code. All these guys are just commodity to us. If next week there’s a better supplier of commodity AI we’ll spend an hour and swap to something else again. There’s zero loyalty here.
By HotHotLava 2026-03-0819:053 reply It's an ironic situation; logically what should be the moat are the models, costing hundreds of millions of investment cost to train and operate so it would make sense if we see different provider focusing in different directions.
But right now we have 3-5 top contenders that are so evenly matched that the de-facto sticking point is mostly the harness, ie. the collection of proven plugins/commands/tools/agent features that are tuned to the users personal workflow.
> are so evenly matched
It's because the real value of the models is in what we (humanity) fed them, and all of them have eaten the same thing for free.
That's why the frontier LLM companies are now spending a lot more to license exclusive proprietary training data from private sources in order to gain a quality edge in certain business domains.
But those holding said proprietary data have figured out they’re holding the cards now and have gotten a lot smarter recently. Companies are being very careful about what gets used for inference vs what they allow to be used for training.
I don’t see the core models getting dramatically better from where they are now. We’ve clearly hit a plateau.
Really? I mean I see regularly as I'm coding how much better it could be simply by running obvious prompts for me.
When I use the planning mode and then code the success rate is much higher. When I ask it to work on specific isolated chunks of code with clear success/failure modes the success rate is again much higher.
Now imagine a world where it recognizes that from my simple throw away non specific prompt. If it was able to fire off 20 different prompts in quick succession it could easily cut my time spent in front of the screen by a third.
The patterns are obvious but they don't do that right now because it's a lot of compute.
We'll be looking at this time where there's a progress bar showing context space the way we look at the Turbo button.
Because the truth is to get the baseline I'm talking about is a finite amount of compute at a certain point.
By bryanrasmussen 2026-03-0820:261 reply so can it be the one that gets ahead on having people go find things for them - https://news.ycombinator.com/item?id=47285283
By indigodaddy 2026-03-0821:39 Interesting
That sounds like spin to me. If there were a clear "quality edge" in "certain business domains" stemming from "exclusive proprietary data", someone would have been exploiting it already using meat computers.
But no, businesses are dumb. They always have been. Existing businesses get disrupted by new ideas and new technology all the time. This very site is a temple to disruption!
Proprietary advantage is, 99.999% of the time, just structural advantage. You can't compete with Procter & Gamble because they already built their brands and factories and supply chains and you'd have to do all that from scratch while selling cheaper products as upstart value options. And there's not enough money in consumer junk to make that worth it.
But if you did have funding and wanted to beat them on first principles? Would you really start by training an LLM on what they're already doing? No, you'd throw money at a bunch of hackers from YC. Duh.
By linkregister 2026-03-0820:031 reply Frontier labs are paying the same constellation of firms offering proprietary data and access to experts in their fields to train LLMs.
They are neck-and-neck only because they are participating in the arms race. The only other way to keep up is mass-distillation, which could prove to be fragile (so far it seems to be sustainable).
Meh. I think there's basically no benefit shown so far to careful curation. That's where we've been in machine learning for three decades, after all. Also recognize that the Great Leap Forward of LLMs was when they got big enough to abandon that strategy and just slurp in the Library of All The Junk.
I think one needs to at least recognize the possibility that... there just isn't any more data for training. We've done it all. The models we have today have already distilled all of the output of human cleverness throughout history. If there's more data to be had, we need to make it the hard way.
Ok, maybe pretraining is now complete and solved. Next up: post-training, reinforcement learning, engineering RL environments for realistic problem solving, recording data online during use, then offline simulation of how it could have gone better and faster, distilling that into the next model etc. etc. There's still decades worth of progress to be made this way.
" There's still decades worth of progress to be made this way."
That's not true. Moreover the progress can slow to a crawl where it's barely noticeable. And in that world the humans continues to stay ahead - that's the magic of humans. To be aware of surroundings and adapt sufficiently whilst taking advantage of tools and leveraging them.
By linkregister 2026-03-0915:25 This is an interesting theoretical statement that does not survive a collision with reality. The long-tail expert RHLF training is effective. We have seen significant employment impact to call center employees. This does not mean its progress will be cheap or immediate.
By k32k 2026-03-0823:52 I think this is where we are at, too.
But if you say stuff like this on here you get down voted. Why?
By nradov 2026-03-0820:00 The quality edge hasn't shown up yet. If this strategy actually works then the quality improvements will only become apparent in the next round of major LLM updates. There's a lot of valuable training data locked up behind corporate firewalls. But this is all somewhat speculative for now.
By Max-Ganz-II 2026-03-0820:393 reply To stop this, I today put most of my Amazon Redshift research web-site behind a basic auth username/password wall.
It's all remains free, but you need to email me for a username and password.
If I put in time and effort to make content and OpenAI et al copy it and sell it through their LLM such that no one comes to me any more, then plainly it makes no sense for me to create that content; and then it would not exist for OpenAI to take, or for anyone else. We all lose.
It seems parasitic.
An AI is more likely than me to take the time to send you an email for requesting access - I'm too lazy.
I think a better approach would be to have a login form and just say "the password is 1234" or whatever.
Virtually no scraper has logic to handle that sort of situation, but it's trivial for humans. Way easier than an LLM
By simulator5g 2026-03-092:16 Not true, even Windows Defender is capable of extracting "the password is 1234" from context like emails or webpages.
By selfhoster11 2026-03-0823:291 reply Please add Internet Archive's bot to your auto-allows, at least. Their bot is presumably well behaved, and for public benefit.
By Max-Ganz-II 2026-03-0919:44 I'm about to ask IA to remove my content!
The reason is that I expect LLM bots to be crawling IA.
By tyzerdako 2026-03-093:42 [dead]
By tempodox 2026-03-0919:15 To be more precise, they all stole the same stuff. I have no empathy for these crooks.
By ryandvm 2026-03-0822:38 Ironic indeed. The Great Replacers of white collar jobs are finding themselves easily replaceable. Delicious.
the companies migrating off vmware due to broadcom shittiness would disagree with you
https://arstechnica.com/information-technology/2026/02/most-...
CloudBolt’s survey also examined how respondents are migrating workloads off of VMware. Currently, 36 percent of participants said they migrated 1–24 percent of their environment off of VMware. Another 32 percent said that they have migrated 25–49 percent; 10 percent said that they’ve migrated 50–74 percent of workloads; and 2 percent have migrated 75 percent or more of workloads. Five percent of respondents said that they have not migrated from VMware at all.
Among migrated workloads, 72 percent moved to public cloud infrastructure as a service, followed by Microsoft’s Hyper-V/Azure stack (43 percent of respondents).
Overall, 86 percent of respondents “are actively reducing their VMware footprint,” CloudBolt’s report said.
By latchkey 2026-03-0819:49 It is easier to do in the cloud than it is to do with actual hardware though, because you'll need enough hardware to do the migration. There is a capital moat around that.
I feel like the company that can figure out how to 100% safely live migrate any VMWare workload to another "cheaper" solution, will do quite well.
By credit_guy 2026-03-0823:43 The moat is compute.
In my case, I always use Opus 4.6 in my work, but quite often I get a 504 error, and that's quite annoying. I get errors like that with Gemini too. I can't estimate if I'd get a similar number of errors with ChatGPT, since I use it very infrequently.
But imagine that at some point one of the big 3 (OpenAI, Anthropic, Google) gets very high availability, while the others have very poor availability. Then people would switch to them, even if their models were a bit worse.
Now, OpenAI has been building like crazy, and contracting for future builds like crazy too. Google has very deep pockets, so they'll probably have enough compute to stay in the game. But I fear that Anthropic will not be able to match OpenAI and Google in terms of datacenter build, so it's only a matter of time (and not a lot of time) until they'll be in a pretty tight spot.
→All these guys are just commodity to us.
Just want to note something there:
Okay, premise that AI really is 'intelligent' up to the point of business decisions.
So, this all then implies that 'intelligence' is then a commodity too?
Like, I'm trying to drive at that your's, mine, all of our 'intelligence' is now no longer a trait that I hold, but a thing to be used, at least as far as the economy is concerned.
We did this with muscles and memory previously. We invented writing and so those with really good memories became just like everyone else. Then we did it with muscles and the industrial revolution, and so really strong or endurant people became just like everyone else. Yes, many exceptions here, but they mostly prove the rule, I think.
Now it seems that really smart people we've made AI and so they're going to be like everyone else?
By EQmWgw87pw 2026-03-0822:173 reply Well as of right now, mathematically and scientifically, the way an LLM works has nothing to do with how the human brain works.
The way this thing "looks like a duck, swims like a duck, and quacks like a duck" has nothing to do with the way a real duck "looks like a duck, swims like a duck, and quacks like a duck".
Who cares, as long as the end results are close (or close enough for the uses they are put to)?
Besides, "has nothing to do with how the human brain works" is an overstatement.
"The term “predictive brain” depicts one of the most relevant concepts in cognitive neuroscience which emphasizes the importance of “looking into the future”, namely prediction, preparation, anticipation, prospection or expectations in various cognitive domains. Analogously, it has been suggested that predictive processing represents one of the fundamental principles of neural computations and that errors of prediction may be crucial for driving neural and cognitive processes as well as behavior."
https://pmc.ncbi.nlm.nih.gov/articles/PMC2904053/
https://maxplanckneuroscience.org/our-brain-is-a-prediction-...
By anon373839 2026-03-092:07 But the end results aren’t actually close. That is why frontier LLMs don’t know you need to drive your car to the car wash (until they are inevitably fine-tuned on this specific failure mode). I don’t think there is much true generalization happening with these models - more a game of whack-a-mole all the way down.
The human doesn't just predict. It predicts based upon simulations that it runs. These LLMs do not work like this.
By groestl 2026-03-097:25 If you're able to predict, you're able to simulate.
Neither does a pneumatic piston operate at all like a bicep nor does an accounting book operate at all like a hippocampus. But both have taken well enough of the load off both those tissues that you be crazy to use the biological specimen for 99% of the commercial applications.
By EQmWgw87pw 2026-03-0915:081 reply A bicep and a piston both push and pull things, but an AI cannot do what a smart brain can, so I don’t think being smart will no longer have an advantage. I mean, someone has to prompt the AI after all. The mental ability to understand and direct them will be more important if anything.
By Balgair 2026-03-0915:27 Have you worked with the Claude agents a lot? They essentially prompt themselves! It's crazy.
My meaning is not so much that intelligence will go away as a useful trait to individuals. But more that it's utility to the economy will be a commodity, with grades and costs and functions. But again , I'm speculating out of my ass here.
In that, if you want cheap enough intelligence or expensive and good intelligence, you can just trade and sell and buy whatever you want. Really good stuff will be really expensive of course.
Like, you still need to learn to write and have that discipline to use writing in lieu of memory. And you still need to repair and build machines in lieu of muscles and have those skills. Similarly I think that you'll still need the skills to use AI and commoditized intelligence, whatever those are. Empathy maybe?
By _aavaa_ 2026-03-090:18 So? Does a submarine swim?
By coldtea 2026-03-0823:10 >So, this all then implies that 'intelligence' is then a commodity too? Like, I'm trying to drive at that your's, mine, all of our 'intelligence' is now no longer a trait that I hold, but a thing to be used, at least as far as the economy is concerned.
This is obviously already the case with the intelligence level required to produce blog posts and article slop, generade coding agent quality code, do mid-level translations, and things like that...
> someone else
We have basically 4 companies in the world one can seriously consider, and they all seem to heavily subsidise usage, so under normal market conditions not all of them are going to survive.
By dghlsakjg 2026-03-0822:02 Open Router shows that commodity api providers have figured out how to do this unsubsidized.
The training runs aren’t priced in, but the cost of inference is clearly pretty cheap.
By pinkmuffinere 2026-03-0819:041 reply Ya, agreed. This makes me think that (long term) the ai race won’t be won on the merits of individual models, but on pricing — I think Google has a some strong advantages here because they know how to provide cheap compute, and they already have a ton of engineers doing similar things, so it’s a marginal cost for them instead of having to hire and maintain whole devoted teams.
AI consumes entire data centers of compute. You aren’t tucking a few racks into a corner of a data center, you are building entirely new ones. There will be whole devoted teams.
By pinkmuffinere 2026-03-0819:43 But Google already builds data centers. Will there really be devoted AI-datacenter teams? Or will they just expand the normal datacenter teams, and ask them to use GPUs/TPUs instead of CPUs?
> As such it’s unclear what the prize at the end of the present race to the bottom is.
It's a market worth many billions so the prize is a slice of that market. Perhaps it is just a commodity, but you can build a big company if you can take a big slice of that commodity e.g. by building a good product (claude code) on top of your commodity model.
By cmiles8 2026-03-0820:35 The revenue slice is there, problem is though in a race to the bottom like we’re in now there isn’t much profit at the bottom. And these companies desperately need profit to justify the gigantic capital spend and depreciation title wave that’s on the horizon. There’s no clear way now things don’t just get really pretty quickly.
By adammarples 2026-03-0820:27 The entire point of a race to the bottom is that your competitors keep reducing their prices until those billions disappear
By spiffytech 2026-03-0819:191 reply Unfortunately this is why Anthropic is so aggressive about preventing Claude subscriptions from being used with other tools.
According to this article, they can't even service the amount of paying customers that they have.
By tonyedgecombe 2026-03-0822:51 They should put their prices up then.
By ghywertelling 2026-03-0819:523 reply Let me explain a possible moat with an example.
I have curated my youtube recommendations over the years. It knows my likes and dislikes very well. It knows about me a lot.
The same moat exists in interactions with Claude. Claude remembers so many of preferences. It knows that I work in Python and Pandas and starts writing code for that combination. It knows about what type of person I am and what kind of toys I want my nephews and nieces to play. These "facts" about the person are the moat now. Stackoverflow was a repository of "facts" about what worked and what didn't. Those facts or user chat sessions are now Anthropic's moat.
By cmiles8 2026-03-0820:36 It takes about 30 seconds to export all that into a file and take your history elsewhere. There’s no moat there.
“Hey Claude, write out a markdown file of all of my preferences so any AI agent can pick up where you left off”
By politelemon 2026-03-0820:061 reply In fact, here, I'll do it myself.
By ghywertelling 2026-03-0820:371 reply You are missing the correlations that Claude can derive across all these user sessions across all users. In Google analytics, when I visit a page and navigate around till I find what I was looking for or didn't find it, that session data is important for website owners how to optimize. Even in Google search results, when I think on 6th link and not the first, it sends a signal how to rearrange the results next time or even personalize. That same paradigm will be applicable here. This is network effects and personalization and ranking coming togther beautifully. Once Anthropic builds that moat, it will be irreplaceable. If not, ask all users to jump from Whatsapp to Telegram or Signal and see how difficult it is. When anthropic gives you the best answer without asking too much, the experience is 100x better.
The underlying technology is a thin layer of queryable knowledge/“memories” in between you and the llm, that in turn gets added to the context of your message to the llm. Likely RAG. It can be as simple as a agents.md that you give it permission to modify as needed. I really don’t think that they are correlating your “memories” with other people’s conversations. There is no way for the LLM to know what is or isn’t appropriate to share between sessions, at the moment. That functionality may exist in the future, but if you just export your preferences, it still works.
The moat - at this point in time - is really not as deep and wide as you are making it out to be. What you are imagining doesn’t exist yet. Indexing prior conversations is trivially easy at this point, you can do it locally using an api client right this moment.
Besides all that, you will be shocked at how quickly a new service can reconstruct your preferences. I started a new YouTube account, and it was basically the same feed within a few days.
In any case, my feeling is that we should have learned at this point not to keep our data in someone else’s walled garden.
By ghywertelling 2026-03-097:37 > Besides all that, you will be shocked at how quickly a new service can reconstruct your preferences. I started a new YouTube account, and it was basically the same feed within a few days.
Because your location data, wifi name and etc hones in on the fact this is the same person as before. You are actually supporting my point than denying it.
By RcouF1uZ4gsC 2026-03-0819:55 You can have Claude write all these out to a file.
Then you can feed them into another service.
By gruez 2026-03-0819:28 Doesn't "web hosting" print money for Amazon?
By timcobb 2026-03-0819:36 > As such it’s unclear what the prize at the end of the present race to the bottom is.
is it ever clear? pretty much everything seems to be a senseless race to bottom.
By gdilla 2026-03-0819:54 just having strict control over context management in session is a nice differentiator. Shared tooling between desktop and cli and is nice too. they've differentiated enough.
> OpenAI, meanwhile, has been attempting to quell the backlash against its deal with the U.S. government, putting out a blog post claiming that “our tools will not be used to conduct domestic surveillance of U.S. persons,”
As a non-US person, that sounds far more concerning than no statement at all. Because if their tools weren't used for surveillance against Europeans they would have said so as a marketing message...
With n-eyes agreements it’s quite meaningless anyway. Whatever passport you have, somebody spies on you and sells the information to your government.
By shimman 2026-03-0819:12 It's also meaningless because we know governments get around these "agreements" by buying data from third party companies that bought the data from OpenAI. The only way to stop this is to legislate it out of existence.
By drob518 2026-03-0818:27 Yep. “You spy on mine, and I’ll spy on yours, and then we’ll share info.”
By kakacik 2026-03-0818:49 I wouldn't give them any free pass and just give up, its highly amoral and inhuman behavior. Modern form of racism but based on passport.
You have this one? You are subhuman, treated as such and you have very limited rights on our soil, we can do nasty things to you without any court, defense, or hope for fairness. You have that one? Please welcome back.
Sociopathic behavior. Then don't wonder why most of the world is again starting to hate US with passion. I don't mean countries where you already killed hundreds of thousands of civilians, I mean whole world. There isn't a single country out there currently even OK with US, thats more than 95% of the mankind. Why the fuck do you guys allow this? Its not even current gov, rather long term US tradition going back at least till 9/11.
> "We have these two red lines... Not allowing Anthropic's AI to perform mass surveillance of Americans, and prohibiting its AI from powering fully-autonomous weapons..."
Anthropic literally said the same, but seem to be getting positive PR.
https://www.cbsnews.com/news/ai-executive-dario-amodei-on-th...
By gruez 2026-03-0819:31 It's not "literally the same".
https://www.lesswrong.com/posts/FSGfzDLFdFtRDADF4/openai-s-s...
By fluidcruft 2026-03-0818:461 reply The difference is that Anthropic actually dotted the i's and crossed the t's whereas OpenAI fell for the weaselwords and is now desperately trying to renegotiate.
By beachy 2026-03-090:46 OpenAI didn't fall for anything, they knew exactly what they were signing and went ahead anyway, then started gaslighting people about what they had signed.
For a lot of people (me included) the lack of integrity and the gaslighting is what has soured them on OpenAI, rather than them signing up to build surveillance and weaponry.
To non-US citizens, all AI companies are as dangerous as each other, OpenAI just really botched the optics here.
It's amazing how bad FANG executives are at even knowing what a normal moral thought would be for average people ...
Plus, you know, you'd think they'd ask their cleaner or baker or something. Or hire someone.
Executives are certainly capable of understanding moral/ethical concerns.
Around 2005, a Yale Psychology PhD candidate asked me to write a web-based survey instrument with various questions, some on complex but straight forward business questions (the controls) and others with moral/ethical aspects. Senior executives participated and they answered similarly to rank & file, often completing the entire survey much faster. What they didn't know -- we were tracking how long they spent on each question. Questions with moral/ethical concerns took senior executives relatively longer than the rank & file.
Late Addendum: Sorry that I don't recall the author/paper. The survey population spanned multiple industries representing many Fortune 500s, including huge tech companies. The survey was the same for everyone. The questions were story problems from business and law school case reports. The participating companies were anonymized on our end. We provided HR departments with survey link; only subject rank (not identity) was collected. Survey was voluntary, with informed consent according to IRB approval.
You would also need to control for the degree to which people had a stake in the outcome (ie., virtue signalling).
Since executives have to make decisions where choosing the moral option may impose an economic (or operational) cost, this requires thinking through the actual choice.
Morality for the "rank and file" is just a signalling issue: there's nothing to think through, the answer they are "supposed to choose" is the one they do so, at no cost to them.
By clcaev 2026-03-0820:20 I hope the addendum helps clarify.
This study showed executives spent relatively more time on questions with moral/ethical concerns. Perhaps the control questions were more similar daily work and hence familiar, while there were fewer encounters with questions having moral/ethical concerns. Perhaps executives decided more care was required for these questions to ensure people were not hurt.
Getting back to the grandparent post, executives are certainly aware of situations with moral/ethical concerns and need not consult their barber to answer them.
"Rank and file" employees choosing to prioritize morality very, very frequently pay real costs for doing so - with a much larger personal impact than executives feel.
Only in very rare circumstances where the obvious answer and their procedural work dont align.
When making an operational decision that affects the direction of the business, morality is almost always a concern -- even at the level of "do our customers benefit from this vs., do we?" etc.
By Timon3 2026-03-0910:13 Where do you get the idea that those circumstances are "very rare"? Workers are being asked to break rules and do unethical things all the time, and you're pretty much guaranteed to pay a personal cost if you refuse.
Meanwhile morality is almost always one of least important factors when making operational decisions.
It helps a lot that Claude is just better. Codex isn't BAD, and in some narrow technical ways might even be more capable, but I find Claude to be hands-down the best collaborator of all the AI models and it has never been close.
Interesting to hear! I've had completely opposite experience, with Claude having 5 minutes of peerless lucidity, followed by panicking, existential crisis, attempts to sabotage it's own tests and code, psyops targeted at making user doubt their computer, OS, memory... Plus it prompts every 15 seconds, with alternative being YOLO.
Meanwhile codex is ... boring. It keeps chugging on, asking for "please proceed" once in a while. No drama. Which is in complete contrast with ChatGPT the chatbot, that is a completely unusable, arrogant, unhelpful, and confrontational. How they made both from the same loaf I dunno.
By AlotOfReading 2026-03-0819:02 I wish I could get Claude to stop every 15 seconds. There's a persistent bug in the state machine that causes it to miss esc/stop/ctrl-f and continue spending tokens when there's a long running background task or subagent. There's a lot of wasted tokens when it runs for 10, 15, 20 minutes and I can't stop it from running down the wrong rabbit hole.
> psyops targeted at making user doubt their computer
IDEK what that means, specific examples?
The following is a dramatic reenactment of an observed behaviour /discl.
You are making tool X. It currently processes test dataset in 15 seconds. You ask claude code to implement some change. It modifies code, compiles, runs the test - the tool sits in a 100% CPU busyloop. Possible reactions on being told there is a busy loop:
"the program is processing large amount of data. This is normal operation. I will wait until it finishes. [sets wait timeout in 30 minutes]."
"this is certainly the result of using zig toolchain, musl libc malloc has known performance issues. Let me instead continue working on the plan."
"[checks env] There are performance issues when running in a virtual machine. This is a known problem."
"[kills the program]. Let me check if the issue existed previously. [git stash/checkout/build/run/stash pop]. Previous version did not have the issue. Maybe user has changed something in the code."
Bonus episode: since claude code "search" gadget is buggy, LLM often gets empty search results.
"The changes are gone! Maybe user delete the code? Let me restore last commited version [git checkout]. The function is still missing! Must be an issue with the system git. Let me read the repository directly."
(Unrelated but I'm really curious) The above comment got downvoted within few seconds of me pressing "reply". Is there some advanced hackernews reader software that allows such immediate reaction (via some in-notification controls)? Or is that builtin site reaction? Or a sign of a bot? Because the speed was uncanny.
By rkomorn 2026-03-0821:00 That may actually have been me accidentally downvoting as I was scrolling through with my clumsy thumb.
Double whammy, I guess, because I also always downvote comments asking (or complaining) about a parent comment getting downvoted.
By fragmede 2026-03-0820:12 There's this bug in Claude Desktop where a response will disappear on you. When you're busy doing many things at once, you'll go back to the chat, and you'll be all "wait, didn't I already do this?" It's maddening and makes you question your own sanity.
I switched from ChatGPT Plus to Gemini Pro instead of Claude, since I'm a hobbyist and appreciate having more than just text chat and coding assist with my subscription (image gen, video gen, etc are all nice to have).
At first I found the Gemini Code Assist to be absolutely terrible, bordering on unusable. It would mess up parameter order for function calls in simple 200 line Python. But then I found out about the "model router" which is a layer on top which dynamically routes requests between the flash and pro model. Disabling it and always using the pro model did wonders for my results.
There are however some pretty aggressive rate limits that reset every 24 hours. For me it's okay though. As a hobbyist I only use it about 2-3 hours per day at most anyway.
By kolinko 2026-03-0821:50 With Claude you just tell it to set up whatever it needs and you have a smooth access to everything. Mine uses Nanobanana for image generation, Sora for video, Gemini for supplementary image processing and so on. Setting up each one was 5-10 min of Claude’s work
With Gemini Pro on Antigravity you get a quota reset every 5 hours and access to Claude Opus 4.6. That's what I use at home and don't need anything else.
By indigodaddy 2026-03-0821:44 Didn't they tighten that quota WAY down though since everyone caught on to the AG/Opus game?
By grallm 2026-03-0820:42 Did you leave OpenAI because of the current backlash? If so, is Google even better?
By fluidcruft 2026-03-0818:52 I've generally thought that but lately I've been finding that the main difference is Claude wants a lot more attention than codex (I only use the cli for either). codex isn't great at guessing what you want, but once you get used to its conversation style it's pretty good at just finishing things quietly and the main thing is context management seems to handle itself very well and I rarely even think about it in codex. To me they're just... different. Claude is a little easier to communicate with.
codex often speaks in very dense technical terms that I'm not familiar with and tends to use acronyms I've not encountered so there's a learning curve. It also often thinks I'm providing feedback when I'm just trying to understand what it just said. But it does give nice explanations once it understands that I'm just confused.
Can you expand on that. I've been wanting to try Claude for a while, but their payment processing wouldn't take any of my credit cards (they work everywhere else, so it's not the cards). I've heard I can work around this by installing their mobile app or something, but it was extra hurdles, so I didn't try very hard.
And I've been absolutely amazed with Codex. I started using that with version ChatGPT 5.3-Codex, and it was so much better than online ChatGPT 5.2, even sticking to single page apps which both can do. I don't have any way to measure the "smarts" for of the new 5.4, but it seems similar.
Anyways, I'll try to get Claude running if it's better in some significant way. I'm happy enough the the Codex GUI on MacOS, but that's just one of several things that could be different between them.
Codex is not bad, I think it is still useful. But I find that it takes things far too literally, and is generally less collaborative. It is a bit like working with a robot that makes no effort to understand why a user is asking for something.
Claude, IMO, is much better at empathizing with me as a user: It asks better questions, tries harder to understand WHY I'm trying to do something, and is more likely to tell me if there's a better way.
Both have plenty of flaws. Codex might be better if you want to set it loose on a well-defined problem and let it churn overnight. But if you want a back-and-forth collaboration, I find Claude far better.
By xscott 2026-03-104:09 That is interesting, and thank you.
I've had a list of pet projects that I've been adding to for years. For those, I just say the broad strokes and tell it to do it's best. Codex has done a really good job for most of them, sometimes in one shot, and my list of experiments is emptying. Only one notable exception where it had no idea what I was after.
I also have my larger project, which I hope to actually keep and use it. Same thing though, it's really hard to explain what's going on, and it acts on bad assumptions.
So if Claude is better at that, then having two tools makes a lot of sense to me.
By ValentineC 2026-03-0818:40 > I've been wanting to try Claude for a while, but their payment processing wouldn't take any of my credit cards (they work everywhere else, so it's not the cards). I've heard I can work around this by installing their mobile app or something, but it was extra hurdles, so I didn't try very hard.
Not Claude Code specifically, but you can try the Claude Opus and Sonnet 4.6 models for free using Google Antigravity.
By kromokromo 2026-03-0818:49 I’ve been juggling between ChatGPT, Claude and Gemini for the last couple of years, but ChatGPT has always been my main driver.
Recently did the full transition to Claude, the model is great, but what I really love is how they seem to have landed on a clear path for their GUI/ecosystem. The cowork feature fits my workflows really well and connecting enterprise apps, skills and plugins works really well.
Haven’t been this excited about AI since GPT 4o launched.
By hk1337 2026-03-0818:35 yeah, OpenAI has its strengths but code generation is not one of them.
