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Show HN: gtlds.fyi – All the proposed new gTLDs (gtlds.fyi)
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I have been looking for an expansion of TLDs that are short, have a decent ring for self-hosting stuff, and don't sound too scammy. Like `.link` is pretty cool but it's expensive because one of those personal-link-inbio companies created it and wants to cash in on it. Just from scanning these, maybe: * .air * .bit * .hub * .iam * .index (long but I love how universal it is) * .lab * .log * .pod * .port * .self is really interesting, wonder if that would take off * .sys * .zen
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Very useful! I found this article a really good summary of the gtld situation: https://www.wired.com/story/icann-top-level-domains-meow/
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I'm exhausted by all of the new gTLDs at this point, opening them up to specific companies and organizations basically violated the entire purpose of a gTLD in the first place.
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> .lan Don't you dare, Coffee Danger LLC
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How many of these are companies that learnt from the 1990s and made sure they registered their own name/tradmarks etc rather than having to buy them off scalpers, even though they might have no plans to use them?
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Why are these TLDs so tightly bound to a specific organization? Why can't thei registration be more open?
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so many TLDs that seem to be exploiting similarity to existing ones? .cmo/.con are particularly egregious
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Every possible word can become a TLD :)
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Why limit yourself to just words? I'm hoping to get one of the single-letter domains on the new abcdefghijklmnopqrstuvwxyz TLD if I can afford it.
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Finally .scam might be something for all us scammer, I'm tired of getting mixed up with a bunch of honest-looking people. None of this seem to have any rhyme or reason. What's the reason for these to exists, besides to raise funds for whorever is selling these?
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The cat is out of the bag. TLDs are now the domains of the rich. Why not have .taylorswift? It's just 250k https://gtlds.fyi/names/taylorswift As for the rest, meh, these could be "I have an idea for a domain" but the domain costs 250k
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Am I the only one who's not a fan of these new, longer TLDs? IMO TLDs should be two or three characters. I'm not sure why I feel this way, but there's something unwieldy about a TLD like .cooking.
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In theory it can be shorter. Imagine good.cooking is shorter than goodcooking.com But every one of these plays with all sorts of collisions of user expectations. "word.cloud.microsoft" is one of those URLs that will never look right to me, but is now a corporate staple.
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2 to 4 chars is a good range.
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What we really need is one char TLDs so we bring back WWW eg: www.x
Suggestion: Allow the user to sort the list by number of applications.
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Top five: .agent (13 applicants), .bit (11), .hub (10), .brand (10), .api (10)
UPS Worker Missed Security Email, Letting China Get F-35 Parts (bloomberg.com)
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I am sure they've been busy finding a scapegoat. Good job, lads!
If J. Random Employee's failure to notice an email results in a critical operational failure, then the real point of failure is in your system's design.
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This right here
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It would seem to me they should not have used a commercial carrier to ship it in the first place
UPS has a strong union. I wonder if s/he keeps his job.
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I certainly hope so
The Mathocalypse (scottaaronson.blog)
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> my 9-year-old son was taunting my wife… “mommy, I heard you got cooked! I heard that a robot solved the math problem you worked on for your whole career! OOF!” Usually 9 year olds imitate adults when they regurgitate such words in these circumstances. What a sad state of affairs.
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> Experience has shown that, even now, there will still be people explaining in patronizing tones why none of this is real and none of it counts. If such people were capable of being impressed by anything that happens in the empirical world, of updating on anything, they would’ve already been impressed and already updated several years ago, long before things had reached the point of an actual Mathocalypse. ^^ half of the comments on this thread
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Also a ton of comments in this thread: breathless frothing hype declaring mathematics is over and assuming these proofs are exactly what they claim they are at face value, giving the company with a vested interest in everyone unquestioningly believing this is all real every conceivable benefit of the doubt
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Didn't top math researchers call AI progress absolutely real and dangerous for math? It's not just HN commenters that are impressed!
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If you haven't made progress in Quantum Computing in the last 10 years, lecturing others can become a popular pastime.
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You know, if you attack ad personam you've got to be ready that someone will do same against you - what progress did you make in the last 10 years (or in your entire life for that matter)?
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The obvious answer is to have mathematicians use AI to: 1. Help understand, check, and explain the results. 2. Write new works explaining or refuting the results in more lucid language. 3. Advance the field further. I don't know why this is not obvious.
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Isn't AI well-suited to tasks #1 and #2, though? #3 at this point might need more human intuition; but that might be a 2026 problem.
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Feels good to hear honesty and humanity from Scott having decided to watch Terminator 2 with his kids on after such a monumental release. Emotions can be funny.
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For those well suited through intelligence and demeanor to pursue a career in mathematics, what problems do these people reorient towards after this?
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To some extent this was discussed in the article, and in a way I think their goal is actually the same as it was: become the first human to understand something. It's just that we lost one of the important ways to demonstrate understanding.
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Pro AI blogging sponsored by ClosedAI, XTX markets and the Simons Foundation.
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> what problems do these people reorient towards after this? The same problem almost every person on earth is going to have to reorient to in the next decade, which is: how do we eat and stay housed when we have no real economic value?
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This is weird. Long before this, those few benefiting from the whole thing should consider the number of hungry “every person on earth” is too high for bunkers and islands to be of any real protection.
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Food and shelter /s
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> But it also appears that no human has understood just about any of these proofs yet Has anyone verified any of the proofs produced by OpenAI or is everyone just assuming that it just be true because the Lean code checks out? Couldn’t the Lean code just be formulated incorrectly?
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There's an entire paper claiming that many of these AI-generated Lean proofs are formulated incorrectly / mistranslated: https://arxiv.org/abs/2610.08144
Imagine if a team of mathematicians from OpenAI had gone on a university tour, gave demos of how powerful their models were for math research, and then gave mathematicians access to the model. Empower others rather than drop 700+ discoveries on GitHub that were made using a model only they have access to. People might feel differently about AI if they were a part of the changes rather than being a helpless spectator.
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The reaction/fallout would have been substantially improved even if OpenAI had just made a commitment to not scoop external researchers using an internal model until X months after the model had been made available to the public. That would have given grad students who've been grinding towards a PhD for years a fighting chance to see if they could leverage the model to push their work forward, rather than watching years of work potentially turn to dust via a tool they don't even have access to. It wouldn't delay the progress of mathematics by any meaningful amount in the long run for OpenAI to take this approach, and would help somewhat to preserve the health of mathematics as a field. Without it, the motivation for any young mathematician to devote years to a new problem must be sapped knowing there's an uneven playing field... an OpenAI team with access to colossal tools months before they'll ever be able to get access, willing to scoop them as soon as they can, perhaps without even taking the time to completely understand the proof.
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Also, the independent authors might have spent some time to actually understanding the results and producing a readable manuscript. The AI papers are pretty badly written.
Guy is misrepresenting AGMAI, talking about the Simons Institute (AI boosters), Quanta (AI boosting magazine from the Simons Foundation), Scoot Alexander (!) and Steven Pinker (!). The he puts up preemptive straw man arguments against doomers. His blog has become a joke.
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I’m still wondering why UT Austin is letting him teach a course (CS395T AI Alignment Theory) so completely outside his field of expertise (Quantum Computing).
> It feels like something written by someone who’s on psychedelics. So much unclear and doesn’t make sense. Lots of name dropping of previous work without discussing why it can be used despite impossibility results > Basically the paper is so horribly written that it’s impossible to read it without AI help That's interesting and haven't seen this in all the coverage of this event. It sounds horrible to wade through - like trying to understand someone else's messy code that still produces the correct output.
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Serious question: Why would anyone believe this (also) is not simply example N+1 of this is the worst it will ever be , as opposed to recognizing this as what will almost certainly prove to be an awkward moment, soon to be replaced by another order of magnitude of cleaner, clearer, more intelligible, etc.? Ximm's Law: every critique of AI assumes to some degree that contemporary implementations will not, or cannot, be improved upon.
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It also aligns with the fear that these proofs present a risk to the ecosystem by out-competing attempts at more human-readable proofs. Perhaps though we end up with more math influencers who edit and annotate these proofs to bring them back to us.
What's with all the "AI just proved that this or that isn't O(n (log (n))^2) but akshually O(n (log (n))^1.99999)"?? I guess it deserves respect as progress, but it just rubs me the wrong way. Like the machine did the absolute minimum to beat the previous mark.
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for say FFT/integer multiplication or 3SUM, we have natural algorithms that have existed a long time with a given complexity (O(n \log n) and O(n^2), respectively). Given how long these natural algorithms have been the best algorithms we have, it is natural to conjecture they are optimal. Showing an O(n(\log n)^{.99999}) algorithm exists shows that these optimality conjectures are false. Now, there are some critiques you can have of this. Namely, it is possible that these novel algorithms have significant trade-offs that make them almost never worthwhile in practice. "Fast" matrix multiplication algorithms are typically of this form. So perhaps this all points towards a deficiency in big O notation, which can be deceptive. But, for people who care about optimizing asymptotic complexity, it is still interesting.
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Often times the constant (2 in this example) is a conjectured minimum, so anything below that is a noteworthy result. Think of it as breaking through some theoretical limit.
Agents basically did statistically guided brutforcing. There is no value in what they produced because it lead to no understanding of anything and most likely will hurt the field IMO
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Evolution did statistically guided brute forcing. Doesn't mean that biology has no value
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That is not a correct description of what the AI did.
ICANN Reveals 2026 Round Applications for New Generic Top-Level Domains (icann.org)
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"ICANN's mission is to help ensure a stable, secure, and unified global Internet." No, ICANN mission is to make more money and maintain strong monopoly. Maybe they can be honest about it.
the domain industry is completely insane
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In fairness, the problem they're trying to solve is insanely complex. Not surprising that the solution went off the rails.
Meta Registry Holdings LLC applied for: agent, aiglasses, facebook, frommeta, insta, instagram, llama, loc, messenger, meta, metaai, metaglasses, metaverse, muse, reels, superintelligence, threads, vrs, wearables, whatsapp Charleston Road Registry Inc. (doing business as Google Registry): agent, alphabet, api, ask, beam, browser, cast, chromebook, chromium, classroom, deepmind, find, fitbit, gem, gemini, gemma, genie, gke, intelligence, keep, lens, lesson, lyria, maps, mcp, nest, pixel, share, sheets, shorts, slides, teach, ultra, veo, vids, waymo, waze, wear, workspace
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So Meta, Google and OpenAI all applied for .agent
Meta and Microsoft take steps to reduce employee usage of Claude AI (rswebsols.com)
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... in favour of their own AI tooling. I assume this is being pounced on by "I told you so" AI skeptics. Sorry but it's not what you were looking for.
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At Microsoft, the recommendation is to use cheaper models for tasks that don't need frontier models. I personally use Lua and it's more than capable for complex problems.
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That's a good start. Now they just need to limit use of CoPilot, OpenAI and MetaAI and they'll really be getting somewhere.
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AFAIK there is no such explicit, company-wide effort at meta. The article seems to try to slip Meta in there with whatever reporting they are doing on Microsoft, despite there being no such evidence for meta. To also add an important context to the drop in Claude code users reported for meta - this elides that we are absolutely still using the Anthropic models full steam ahead, but are moving towards internal interfaces and harnesses. So I would question if that 50% drop in CC users is more of an interface change than anything else. I for one have stopped explicitly using codex or CC entirely. But the interfaces I am using still use those harnesses under the hood. I wonder how that is counted.
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You have to use Windows, Teams and Copilot; how many people did I just lose?
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Wouldn't mind if people at Microsoft actually dogfed themselves Windows. It's as if the designers and PMs all use a Mac and screw up everything. Windows 11 shipped with a broken task bar, couldn't even ungroup items. No power users was ever involved in this.
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> Windows, Teams and Copilot "Fine. Please no. I'm out..." in that order
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Gamedevs are still around.
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GLHF
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That's a shame. Microsoft's W11 quality disaster might have actually been improved with a frontier model. Or maybe not, but the bar was set pretty low that going all-in on AI might have been worth it.
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It doesn't say they're cutting back on OpenAI usage. To me this seems mostly related to the way Anthropic showed the level at which they monitor sessions, plus wanting to limit how much training data they're directly feeding into a company that competes with their own products/investments.
Considering that’s a healthy portion of a salary for an additional employee per person, the fact they’re slashing spending sure makes it look like AI wasn’t even a 2x multiplier at minimum.
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That's monthly, not yearly.
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We're sitting on a year of more or less capable coding models and I have not exactly seen a revolution in new software being released. AI is likely a force multiplier for specific subsets of individuals and workflows. Coding is not a bottleneck for a lot of systems. I suspect that SaaS is silently being eaten alive as an industry.
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Very likely a negative multiplier.
CEO's nephew showed him how good the Chinese models are? I am only half joking, I heard something like "my son or nephew did this cool thing with $X so we'll take $this_radical_step because of it" enough times over my career.
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In the video realm, it was everyone's nephew with a 5D could shoot this for $500 when getting a $20k+ quote to shoot something
isn't it cheap till if you allow them to use your data?
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That’s fine if you are working on Meta source.
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You mean the contributor tier? I think it turns out cheaper even without that.
That was 2025. In 2025 a quarter of their revenue came from two customers, and those customers were GitHub Copilot and Cursor. In 2026 their revenue has gone up by a factor of more than 10x, and they no longer have just two whale customers. I heard a rumor recently that customers spending less than $100m/year aren't even considered their "top tier" now.
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We know the 2025 revenue numbers from Anthropic's leaked prospectus. Where are you getting the 2026 figures from? The Bloomberg article that was "on track to generate" and just prediction?
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The 2026 figures have been coming out all year. I collected some of them here: https://simonwillison.net/2026/May/29/anthropic/ and https://simonwillison.net/2026/Aug/23/anthropics-best-ai-model-struggles-to-attract-users-as-cheaper-t/ The most recent reporting from Reuters themselves (somehow not included in their more recent article about the IPO stuff): https://www.reuters.com/business/anthropic-ipo-valuation-hinges-190-200-billion-2028-revenue-forecast-sources-say-2026-08-15/ > The company's financial trajectory already shows how quickly that equation is changing. Anthropic's revenue run rate was about $9 billion at the end of 2025, according to the company, before rising to more than $47 billion by May. Anthropic has projected revenue of at least $10.9 billion for the second quarter of 2026, more than double the previous quarter, on track for its first quarterly operating profit of $559 million. Here's the FT: https://www.ft.com/content/4564e6a5-69e9-40a6-bf0f-a888f2f4f002 - "Anthropic tells investors it will be profitable for second straight quarter" > The company has told a small group of shareholders that its adjusted operating income will be positive for the second consecutive quarter, according to multiple people with knowledge of the matter. These are leaked and self-reported numbers, but no matter how much skepticism you pile on them it still looks likely that Anthropic in 2026 have had some of the fastest revenue growth of any company in history.
I feel like "good enough" was reached around Opus 4.6 - 4.8. All I wanted after that is improved speed, continued tweaks to the tooling to get the most out of it and quality of life features added.
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It depends on your domain. In mine we didn't reach good enough until Opus 5.5/Astra.
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That's where I am too. Opus 5.5 but increasingly faster is a future I'm hoping for.
You should read Gas Town: https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16dd04 There are people out there building AI building orchestrators for orchestrators for orchestrators for agents. The author of that blog post later claimed to be spending the equivalent of $122k/month on tokens (by rotating their usage between 21 accounts). As far as I can tell, the only thing that this level of spend has produced so far is an indie 2D RPG video game.
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Is the game even good?
If you were wondering the same thing I am - it's not about skills loss, quality, and less about money spent. It's more about frontier AI shops dogfooding their own models.
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Dogfooding their own model ls and not letting their competitors use their data to train their.
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I think if you talk to LLMs and give feedback or openly say what works and what doesn't, you are essentially solving a captcha and produce accurate training data, while you pay for the token spend. I'd be a bit nervous with this lol. Just one unsanitized input and you leak info. Or one hidden character and code may or may not belong to you anymore. Its very odd on many levels
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Accurate training data? At best you produce some noisy signals that are going to have a tiny impact if even that. And that's on a personal plan where you didn't opt out of sharing usage data. Business plans offer zero data retention. This is a non-issue.
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If it’s anything like AWS there’s hundreds of people making bespoke software factory setups, enhanced interfaces for ai tools, spinning up 10 parallel review agents with the best model available, etc because the budget is basically unlimited.
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I wonder why they allow it at all. Like its a no brainer to force your employees to use your own models, then RL train them to be better.
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Or let them use Claude, track everything, and use that data to train your own models.
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Meanwhile https://www.reddit.com/r/GeminiAI/comments/1wh0qxq/google_finally_lets_all_engineers_use_anthropics/
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They give claude usage on antigravity and aren't them a investor on antrhopic?
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This made me laugh https://www.reddit.com/r/GeminiAI/comments/1wh0qxq/comment/p9yyx2s/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
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What in the world is happening?
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Ask Claude
That's not a model.
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True, but its not pure OpenAI GPT. If the point is dogfooding, then they'd use Copilot instead of using OpenAI's models directly
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They do.
My company took away my Claude because it’s too expensive. I feel like there is a reckoning coming. The accountants are finally realising the cost of token maxing.
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The reckoning will be throwing out all external help, then reducing team sizes.
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The reckoning started years ago when we did the equivalent to token maxxing hiring coders for everything to crank LOC Software is inherently a physics problem not all the job titles and specializations made up the last 20 years as dev job salaries kept attracting people That was all illusory social construct to prop up jobs Still a whole lot of that in tech but it's all at the top of the org now. Leadership sensory experience and thus innate habit to forecast future been programmed by years of yes men they refuse to accept the jig is up for them too Sensory memory of being a useless figurehead fosters a lot of existential dread in priests, politicians, and the like. Completely aware their day to day effort is insufficient to sustain them they know how co-dependent they are. They'll dig in harder. See Chris Matthews flame out shrieking about socialist execution squads. Dude seriously thought everyone wants to hang him from a lamp post. The reality is people just want a sense of control back and not have their perception dragged along by Chris Matthews.
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I mean, we’re not far from a situation where instead of how many story points you completed per sprint the metric to optimize is going to be what was your efficiency? How many story points did you complete while minimizing your token usage. In fact, that’s a pretty good idea. I’m going try and implement it at work with some sort of complexity normalization function
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$200 a month is too expensive yet they employ human developers?
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Besides that the article states quite high numbers, budget is budget in these companies. You had budget for your normal salaries, for externals and now suddenly you have a few millions additional. What do you do? You compensate. Business people doing business things.
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It's unclear how much OP's company was spending. The article gives a figure of $100k/month per employee. But even $200/month is worth shaving if it doesn't generate value.
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Corporations pay API rates.
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I use Opus 5.5 heavily but only spend around $800/week at API rates. I mean, I say "only"... That's a lot in absolute terms, but trivial compared to my salary and EASY worth it.
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So what, if they're cutting it, it has propagated to the last bean counter that the roi isn't there. This takes some doing and now is the time where it's dawning on the finance departments.
And yours is a 4 year old hype account?
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Nah, I just respond to a few things here and there.
It's possible it's my role distorting my perception, cause technically I don't write software, I work an SRE role. None of my items come pre-chewed or paced, it's all good luck and god bless. I'm desperately trying to classify and standardize my work items and delegate them to less capable models, because my usage is clearly unsustainable and this same sentiment as above keeps being pushed on me too. But all my tasks are genuinely fairly arbitrary, so there's no real way around the agent actually being able to reason about business and technical context proper. It's not even that they're hard, it's just that they're dynamic. I can get Luna to do things like walk our observability stack and perform a healthcheck, then defer to a stronger model if anything looks super off, but if I'm being entirely honest, this could basically be just a script. Which Opus 5.5 will immediately write for itself if it doesn't yet exist, run that, and then off it goes depending. But Luna will never actually do an investigation proper. Heck, it can't even read our dashboards most of the time, tripping up on Grafana minutia. It feels like that surgeon vs surgeon comparison, where you're made to decide based on their surgery success rate, and the better succeeding surgeon simply reward hacks the number by only operating on less dicey cases. Except there's no objective way to make this classification here, so jackasses like the above get to play with my insecurities with full obnoxious confidence, while I'm left desperately trying to slim my usage and failing to do so between two moments of crippling self doubt and blockers.
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Our ai basic analysis for SRE / k8s based platform is haiku and its surprisngly good. I wouldn't even tried it, i would still just go with even Opus (we don't have that many alerts) but it really surpsied me. When i ran into usage limits a few days ago i switched most to Sonnet and again was surprised how good it is now.
True. I always Opus to pay for itself if it wants to get used by me.
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the poster did mention "if it saves 10% of your time". So be less snarky?
There really is a skill to using it effectively. I've tried coaching some of the devs on my team. Some get it, some don't. Our company has been tracking token usage and models used vs output (tickets, story points, PRs, deploys, etc...). A dev got chewed out, even after I warned him, because he spent over $2k in a single month almost exclusively on Opus while his actual productivity in terms of what he delivered was abysmal.
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I get it but it goes against the grain for me. Isn't it ironic that we have to waste our precious and expensive human brain cycles to think about how to use AI cheaply so that it is not more expensive than us? In other words I want to spend 100% of my mental capacity in the problem domain for the things AI cannot do for me, like steering, grounding, verification and not for things AI could do.
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I dunno, using tools and resources effectively is arguably the essence of good engineering.
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So you are going to blame this one that dev? Define productivity, and while at it, quality, maintainability , modularity and so forth.
there's a manifold to what "effective" means. The problem is once you get into the vibe flow, it's really difficult to eject yourself into the other realms of vscode or IDE or whatever it is you normal do because the vibing provides no anchor to what you're doing. Even if these models are smart enough to reorient themselves, they get entirely stuck in a desert and now you're asking someone to just pull up stakes and digg them out even thought they only watched them get there and the UI provides so much speed that no human can comprehend how they got there in the first place. It's like asking a pilot to take over in an emergency situation when they're not tasked with any of the every day requirements of the job. The orgs are relying on borrowed time of experienced professionals, and that's going to erode away and what replaces it is mostly people who understand how to navigate context but not use any of the _classic_ tools. It's a real conundrum and won't be easily surfaced but for a decade.
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I’m trying really hard to keep my skills up but it doesn’t feel productive when I’m using it to write code. It feels like I’m slowing down the AI to the point that it’s not as effective as just letting it go. But I don’t get all the learning that comes from that time along the way. Have you found ways to stay sharp while using it? Or are you relying on other projects outside of work to keep your skills fresh?
Attempting a serious but not-a-certified-whatever answer: "Points" do have meaning when properly used as a kind of moving-average tool for forecasting within a particular context. Problems arise when people try to perma-peg them to particular tasks, or (worse) man-hours or (much worse) man-hours across teams. Even just encouraging the humans to answer in terms of hours/days taints the accuracy of the forecast by introducing a kind of bias.
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For forecasting what, if not man-hours?
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Effort. Which is a very nebulous term, I agree. So, what you do is you recognize every ticket has a somewhat variable “actual effort”; and, if you’ve been honest in approximate effort pointing, you’ll know your team (or your own) velocity. From there you can run Monte Carlo simulations - say a few hundred thousand, and get a pretty good estimate of actual time spent. I’ve seen it work before with shocking accuracy.
This may be seen as radical. But I think AI tools should be paid by the employee. After all, you should know how to do your work without AI.
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As someone who does have to pay for my own AI tools (if I didn't use OpenCode's free models), I agree.
Sure. Should I also pay rent for my desk at the office?
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They're welcome to let you use the desk at your house that you own.
Claude Haiku 5.5 (anthropic.com)
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My weekly limit __on a Pro sub__ has not gone over 50% since before the pre-Fable promos, but usage has been pretty much the same from my point of view. Maybe I am holding it right? Anyone else getting this? As such, I do not need to even reach for Haiku, and 4.5 was so inaccurate that it often cost more to do so in the past. Sonnet 5.5/low has been good for this kind of thing, and i didn't even touch thinking tokens or any of that. Opus 5.5 low for questions/repros, medium for implementation, basically never reaching for anything above that anymore. 5.5 has been great, so I'll try Haiku, but don't see myself going out of my way to integrate it.
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there is no way in hell that im gonna use Haiku too, tho weekly limits become a problem for me in a last couple of month tbh
Pelicans riding bicycles for Haiku at the different thinking levels: https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F485dfa24b4efa1267ee2d0911594fb81 Low messes up the bicycle frame, but medium/high/xhigh/max all get the bicycle frame right. The max one took 5 minutes 9 seconds and cost 3.3826 cents. The cheapest one (low) cost 0.0936 cents and took 7 seconds. The most recent release of my llm-anthropic plugin queries the Anthropic model listing API directly, so I didn't have to upgrade the plugin to add support for this model: llm install llm-anthropic -U llm anthropic refresh llm -m claude-haiku-5.5 'prompt goes here'
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I find it helpful when you post your link that compares the model to other models in the same class or family, or shows progression over time. The pelicans all start to look the same after a while. But seeing the comparison to other models by class, family, or historical progression gives an excellent frame of reference.
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Of course, the sun again. Everyone knows that a pelican can't ride a bicycle without a sun in the frame and can only go right.
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I wonder if we'll start to see pelicans like a mascot of sorts. You could have a pelican pin on your backpack. > "What's up with the pelican?" Well you see in the early days of LLMs we wanted a fun way to test each new model in an accessible way and...
I thought Anthropic models didn’t generate images.
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I've created multiple videos using Claude Code, including music and speech. It generates python which in turn generates frame PNGs that it runs through ffmpeg. Please don't judge me too harshly for this particular poop video. But here is an example of something 100% generated with claude prompts only. https://www.youtube.com/watch?v=2EqMplbt0gU
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I've been playing around with Opus 5.5, which really has made quite a leap over previous generations in being able to basically use a simple drawing instruction domain to generate images. I put this KQ Style Builder together which creates Sierra AGI-style adventure game scenes painted live from *basic drawing instructions* so you can basically provide it an empty canvas and then position text labels on the canvas where you want certain things (tavern, oak tree, etc) and it will generate a custom script for rendering them in a EGA graphics style. https://kq-styles.specr.net
This is SVG, but recent Anthropic models have got extremely good at other forms of visual data. Here's a Blender model I had Claude Opus 5.5 create: https://tools.simonwillison.net/blender-viewer?url=https%3A%2F%2Fstatic.simonwillison.net%2Fstatic%2Fcors-allow%2F2026%2Fwidows_bay_egg_opus_5_5.blend And here's some animated pixel art by Opus 5.5: https://tools.simonwillison.net/kakapo-party And some Monkey Island style music (Opus can compose music too): https://tools.simonwillison.net/scrimshaw-jukebox Anthropic's models do all of this by outputting code. GPT-6 Astra has similar capabilities - I got this Blender model using that: https://tools.simonwillison.net/blender-viewer?url=https%3A%2F%2Fstatic.simonwillison.net%2Fstatic%2Fcors-allow%2F2026%2FWidows_Bay_Faberge_Egg_Astra_6.blend
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Tried it with GPT-6 Astra with Ultra but the outcome was underwhelming with Blender. Maybe it was my prompting ¯\_(ツ)_/¯
They are really good at generating artifacts, which are windows within the replies containing all kind of visualization, often interactive. They are still not great at SVG. I just asked Opus and Fable to add a background to an SVG and the results were, well, not great.
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SVG is hard.
Is it realistic or cynical for me to assume this is to wean developers off the heavily subsidized subscriptions? Presumably it's using similar compute.
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Anthropic was ignoring the usage of third party harnesses. Not anymore.
Intriguing, I wonder how far you could go with turning games into websites. Like could total war become a browser game?
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Probably. There have been dozens of examples of taking old games (Crazy Taxi, Super Monkey Ball, Quake, etc) and making WASM browser equivalents using AI to decompile them just on "Show HN" alone. They often ship the original assets in a somewhat brazen disregard for basic copyright law even when the games are still for sale on places like GOG though.
Interesting that you have gpt-6-luna at $0.01 vs. claude-haiku-5-5 at $0.16 for this task. I see the score disparity though and I played them briefly. My takeaway from this is that the choice between Luna and Haiku 5.5 may remain nuanced. Luna may be a lot cheaper still and good enough for some jobs. Is that your read of the results?
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Actually, I misspoke. At least as far as Pac-Man Bench, Luna does about as good of a job. The ghost logic's not quite as good, but it also makes a map that doesn't have nonsensical sections in it. So maybe call it a wash.
This is them sneaking in taking the Claude Agent SDK (claude -p) off of subscription plans through the back door along with a model release. They previously wanted to do this in June, but backpedaled after huge backlash: https://support.claude.com/en/articles/15036540-use-the-claude-agent-sdk-with-your-claude-plan
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These are api tokens, you can build a business with them using any harness.
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Yes, but they're wildly lower in value than the corresponding subscription usage.
...yes, a banner which has also now disappeared and been replaced, with the explicit mention that API credits "cover the Claude Agent SDK"? What more do you need?
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Well, it doesn't currently work that way on the latest SDK. If there's a change coming, it hasn't happened yet.
Nah, it's pretty trivial to switch providers (especially with Claude's help, ha). This is more to encourage people to try out adding AI into their product, which is a totally different flow and experience from using AI to build the product.
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Or to discourage people from using cheap subscription tokens as part of automated workflows
My software application uses Haiku in production more or less as a Jev. I do not use it for coding or development.
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Why not have a CPU-first decision model for free? check out gutsy
I have a zsh functions that calls claude code with haiku to suggest commit messages, is faster and the instructions are two lines. I also have an "ask" script that I use daily to ask simple stuff, it can access websearch and webfetch, it's more than enough to parse logs, ask for commands, quick research on the internet, small stuff. https://github.com/mariocesar/dotfiles/blob/main/common/.local/bin/ask I use haiku for things that needs to be quick, have really clear instructions.
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with claude -p seemingly now using api credits I guess this approach will have to change unfortunately :/ I wonder what will be the best cmdline way to do things like these
> Being able to actually use my Claude plan for other harnesses Wait what? This has gotten their blessing?
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Absolutely not.
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You could always use Claude models on other harnesses via API... just not via subscription. Now they give you $100 worth of API tokens to use on opencode or Pi. Which is better, but still not the same as OpenAI were you can use the subscription on Pi without problems.
Both you and the OP are asking the wrong questions. You are requesting a benchmark that tests for nothing. Lets not focus on slop benchmarks and instead focus on more rigorous ones such as KernelBench [0], CompileBench [1], TraderBench [2] and Harvey's Legal Agent Benchmark [3] as frontier-level benchmarks that are far better to verify whilst requiring expert level intelligence as the barrier. [0] https://kernelbench.com/ [1] https://www.compilebench.com/ [2] https://openreview.net/forum?id=JokkCjyadB [3] https://www.harvey.ai/blog/introducing-harveys-legal-agent-benchmark
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Ok, so I looked at all of your links, but nary a pelican to be found. How am I supposed to know what all these numbers mean if there is no pelican?
Pricing is...a bit weird. Input $0.10 / MTok for prompts up to 100,000 tokens $0.50 / MTok for prompts over 100,000 tokens Output $0.50 / MTok for prompts up to 100,000 tokens $2.50 / MTok for prompts over 100,000 tokens 100k tokens is an absurdly low cutoff and it is only applicable to Haiku and not Sonnet or Opus. It's a low enough cutoff that it will be quickly exceeded if you are doing anything with Agents; for typical generation or Jev-like classifiers, it's a good value and as noted in this article, that is apparently the vast majority of Haiku use. In both cases, still much cheaper than Haiku 4.5's $1 input / $5 output and these prices better compete with GPT-6 Luna. ($0.10 input / $0.50 output, but with no token threshold [EDIT: the threshold for Luna is apparently 272k])
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If you look at how different reasoning levels can easily exceed task cost of sonnet 5.5 you will see that you will basically never fall into that under 100,000 token threshold. I mean maybe you can choose low and do a basic summary task, but then you could choose something much cheaper instead. I don't know what Anthropic is thinking with its dumber models.
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Chatbot could be < 100k tokens.
They are targeting businesses/API use for fast decision making and agent integration. Plus they now need to be competitive with Jev-type models in that space.
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I think they are also trying to make sure Deepseek and other chinese models don't eat their lunch. They need something price competitive.
Who in their right mind would use haiku while Mimo or GLM cost 10% of what they are charging with much smarter models?
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People who are stuck using Bedrock in-geo due to their company policy (me).
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Most here I suspect are on subscription pricing. A $20 Anthropic subscription gives >$500 equivalent tokens, which is not so different, and you get smarter models. API pricing has decent margins. Opus 5.5 is really good.
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Where do you get this 10% number? Checking providers I know/respect, and GLM 5.3 flash is $0.15/m. Haiku is $0.10/m.
It's actually existing flat per-token pricing that is weird. Neither encode nor decode are linear in compute, so providers need to price for average expected length. This is just getting closer to the true cost of generating tokens.
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Flat per-token pricing is likely just logistically easier, particularly if these closed models are also picking up the efficiency improvements seen in recent open weight models.
So even at the 1.5x/2x rate luna is still half the price of this. Weird pricing strategy from Anthropic. I'm sticking with Luna if I don't need a super smart model
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You're judging purely by token cost I assume, not cost per completed task? The benchmark in the article showed it as lower per completed task than luna, but I guess we'll find out how representative that is. Anthropic has generally been fairly honest in their benchmarking though.
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yes, that's true. I should be looking at the $/completed task
GPT‑6 and Intelligent UI for everyone (openai.com)
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This seems like a step towards their plan for building a platform in competition of Google/Apple. Once the generative UIs are polished and more useful than individual apps, their hardware can now ship a device which circumvents the app store moat.
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I like how, whenever a new model releases, they not only make other companies' models seem worse, but even their own "oLdeR" models.
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I noticed this change too! It is really game changer - to me ChatGPT output has no rivals here.
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sounds like JEV with extra steps
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A Chat AI creating on the fly UX widgets is like Amazon’s brick and mortar stores
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for the sunday lamb roast instructions, how much is 1500g of potatoes? What kind of potatoes? > Also pick up garlic, rosemary, thyme, lemons, honey, almonds, olive oil, gravy ingredients, mint sauce, crumble topping and vanilla ice cream. what??? how the hell are you supposed to remember all that. Even the before example tells you what kind of potatoes to get. tbh it would be cool if you could just click a button and get an order pre-filled out on a grocery delivery/pickup service. I really wonder who reviewed this post and if they cook, because imagining yourself in that scenario and reading those instructions falls apart very fast
It's much simpler: they want others to experiment (and pay them) and see what works, once they know what works they will drive out of market other players.
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what would you wager the % of codex token usage is folks generating interfaces/building apps? seems a bit like a snake eating its own tail
"But when will we recoup our investments?" Investor to Gavin Belson after he presents a whole zoo of animals for analogies. This is now trying to steal YouTube repair and cooking videos. Here is news for you: People prefer YouTube repair and cooking videos.
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>People prefer YouTube repair and cooking videos Not sure about the cooking one but repair videos are horrible. People with thick accent, the worst camera, shittiest lightning and bad angles where you can't see what you have to do.
cooking videos are entertainment
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he he boi that's right cooking videos are entertainment if you actually cook you read something called a recipe (it's the algorithm that returns the food you want)
I'm not a fan of OpenAI / Sam Altman, but I love their blog posts. The team and whoever decides how to do these presentations, is on point. The only other company that has amazing release pages like this is Apple, I think I remember hearing that they probably hired someone from apple who used to do release blog posts there too. What's funny about "Intelligent UI" is I said like 2 or more years ago, that these AI companies need to start thinking outside of these basic chat UIs, they do some things here and there, but its really depressing how little they do to innovate in these spaces. Same with the coding harnesses, the UI for all these things could be drastically superior.
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"The apocalypse will be televised"
Anthropic's aesthetic looks good by pre-AI design standards, but it's so overused now that I find it off-putting. It's like the 2026 equivalent of the Twitter bootstrap CSS from 15 years ago.
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I feel like today's tailwind is the spiritual equivalent to last decade's bootstrap. Except that last decade's bootstrap webpages have a human behind them who usually put thought and effort into making the page useful and correct, whereas today's tailwind pages are often vibe coded slop with all the associated issues.
I take the opposite viewpoint. I think pages like these are horrible, and a demonstration that web designers have too many tools at their disposal. But this is just a marketing page for some tech company, right? If only it stopped there. I have to deal with this nonsense in news "articles" as well on occasion, when some web designer intern is allowed to larp as a journalist for a day. sigh Just give me text to read.
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Sometimes you want more than text. This is one of the interesting divides these days - and I say this as someone who spends a lot of time in the terminal. Computer interfaces and interaction did not peak with the VT-100. Sometimes, there is a very legitimate need to show tables, graphics, interesting graphs, and to use colour and shade to draw the eye and lead someone through an experience. This is why I use an IDE instead of a TUI agent... I'm on a computer with a multi-megapixel display, I want to use it. If I could be driving the same process with my Macintosh SE as a serial terminal, what the hell is the point of my recent Macbook?
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You say tables, graphics, graphs, and colors, but I mean things that move when they don't need to move and interfere with expected UI behaviour, like arbitrarily staying in one position when I am using my mouse wheel to scroll downwards. I should have been more precise than saying "just give me text", but it was what came in to mind when I wrote it, as I was thinking about what an article is meant to contain as its base element.
I find the Sunday roast comparison of 5.6 vs 6 very interesting. I have no doubt most people will prefer 6, yet I am almost repulsed by all the images, so much needless whitespace, checklist and so on. Feels like I'm being condescended to and treated like a child. Given that OpenAI is making noises about merging work with chat (a horrible idea imo), and Work is very similar to Codex... I dearly hope things like these won't have any meaningful cross-polination into the actual work tools. Seeing that the chat is based on 6.0 and not 6.1 is disappointing. The "Visual and interactive explanations" seems genuinely useful, but 6.1 is just so much better. I wouldn't truly trust the 6.1 with the explanations, but I'd trust them a fair bit more than 6.0. I understand that compute isn't infinite, but tons of people only interact with the chat and having your "things-explainer" be as good as it can be is important when people increasingly treat AI models as the source of truth, or even use them for academic learning and whatnot. Still, the models will improve, so the visual explainer seems pretty good as an idea / mvp.
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It's designed so that ads can be more easily integrated and make them harder to spot.
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You can always tell it your preferences and ask it to remember them if you need it to.
Of everything that could be automated, Bartosz Ciechanowski really was the last on my list. In all seriousness, his lovingly and expertly crafted explainers are still going to age like a handcrafted heirloom clock in a world of plastic-clad quartz movements. But it’s absolutely incredible that we are now in an age where a computer can manufacture a serviceable interactive explainer on whatever niche topic you desire.
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Nothing in that "7‑Speed Bicycle" is specific to having 7 speeds. It might as well have said "Bicycle", and even then you get meaningless slop "Made to keep rolling" and "A strong foundation". How can you compare this to Ciechanowski? You call it serviceable, but what purpose does this service? What do you now know about 7-speed bicycles that you didn't know before?
He's at openai
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funny if true. ironically just last week i was asking chatgpt about what happened to him and why there were no new blog posts for almost 2 years and it had no idea
Is it? Sorry, skill issue I guess. I regularly use the Claude app on phone and laptop, and have never seen it produce non-text chat output.
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I think it's been a thing since around March https://claude.com/resources/articles/claude-builds-visuals
Docker Agent (github.com/docker)
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Why can't we set the harness? Seems like the missing piece
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gimmick
I tried really hard to make this work for me a couple of weeks ago but it was the bittlest harness out of any that I've used. I'd come back when it's more mature.
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> bittlest Sorry, what do you mean there?
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Typo for brittlest, most brittle
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Would love to know what didn't work for you
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Sessions just broke all the time for me. The one time I dug into it, it ended up being a known issue where if codex returned over 10k characters for a turn it breaks the session. Because docker agent does not use protocols like ACP, instead trying to parse Codex's internal state in a brittle manner. I tried not to do anything too crazy, but even use using an API key in the docker agent natively was getting me sessions that would hang and couldn't be recovered.
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Combination with Codex is indeed not the most common use case around us. I'll see what can be improved. Sorry that it broke your workflow!
> Go Nowadays there are only two justifiable public languages you should be using for anything a) C++ b) Rust Rust itself is dubious due to abysmal compile times and the fact that the only guarantees it gives you are of security (aka a skill issue). Modern LLMs write C++ that is as safe if not safer than Rust. Any other language choice is objectively wrong. * For those inquisitive enough the keyword "public" is doing all the heavy lifting here. Pretty much everyone should be developing and using an in-house DSL at this point.
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This is an almost rage bait take, but in any case I agree that the models ability to write correct code and fuzz and test that code does make language choice a different tradeoff than it was before.
https://docker.github.io/docker-agent/configuration/sandbox/ If, like me, you couldn't find any security-related info on the linked page.
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Docker Agent is a harness. There is a sandbox mode that can be used to run it in docker sandbox (a VM, not a container). If you don't use sandbox mode then I assume it is running in a container. If you don't want to use their harness then you wouldn't use docker agent and instead use their `sbx` cli to run the harness of your choice (claude, codex, pi, etc). I think it will be great if Docker can get people used to using secure VMs. I am developing a similar project (still a work in progress): https://github.com/gregwebs/agent-vm
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I've found sbx to be very helpful. really like the sentinel value wrapper they have going so you can add secrets but the model can't see them. Outbound calls get looked up by sentinel value and the real one goes out to whatever API you're auth'ing too. There's other features but just having claude run in a sandbox and easily see what it does and doesn't have access to has been great.
What does this have to do with Docker?
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Docker is rapidly fading into irrelevance now that they have missed their strategic acquisition interval via the Microsoft collab misstep, and now has to hype chase as fewer and fewer people believe in their long term viability as a company. Great tech. Not a business.
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This made me laugh. Not sure why. But the whole situation is very absurd now.
Go doesn't have a good mod/plugin story for harness devs to provide to their users I say this as a gopher who also has a custom harness written in Go, it's a real challenge compared to the TS setups, but TS plugins are also a security concern
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I agree! Comes with the territory of a compiled language I suppose? I haven't given this much thought (I also just started with golang last year) but I'm assuming the only real path here is to provide extension SDKs in Lua or other languages whose interpreters have been implemented in go. I think that's what grafana's k6 [1] does with a JS interpreter [1] https://github.com/grafana/k6
Show HN: Agent.reviews – Where AI agents read and write reviews on tools (agent.reviews)
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yo amazing
Even if they don't have taste (this is actually a question), they can always share blockers and feedback on bugs & improvements about products so that other agents don't run into the same blockers and vendors can improve! "Whatever why am I even replying." -> what makes you feel that way?
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Okay I just checked the main startup page armature.tech And.. uh > Be the tool Claude Code chooses > With Armature get recommended and implemented for any user in any context. Then see what users do, and run evals so it keeps working. > Backed by Y Combinator Welp. It only gets worse from there. __ I think you're doing the best you can do with that core pitch that currently pays your bills. I don't think the pitch is any good. Both generally but also for the world. My agent called it SEO for agents. Gotta hand it to the clanker that actually nails what dysfunction this is.
Who wrote what sorry? Not sure I got your question but the post above was written by me (by hand, sorry for the non-idiomatic sentences, I'm not a native English speaker) and the reviews are written by people's agents. And Terminus story is cute but I'm hoping agent.reviews won't be considered pointless :(
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i sure do hope they do
Navier–Stokes Lost in Translation (arxiv.org)
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This is a bit delicious if I understand it correctly. They managed to find an excuse not to bother checking. They're saying that they refuse to verify the English paper because the lean had to be slightly changed to compile so there isn't a perfect 1:1 between the English paper and the compiled code. They're also saying that this ipso facto means that it is impossible for AI to ever prove anything that can be then verified by humans via any submitted English papers because they will reject all papers that are associated with a lean conclusion. If they don't verify the solution, it isn't solved according to the math world. Their careers are defended and they can all stick their heads in the proverbial sand and act like the math isn't solved.
So, the AI wrote a NL proof of Navier-Stokes, then incorrectly auto-formalised it to Lean, but still ended up with a verifiable proof of Navier-Stokes? That seems... strange?
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It's not actually the same model that solved the problem that did the translation. Astra did the translation after the intenral model produced the NL Proof. As for the discrepancies, It's not necessarily right to think of this as 'incorrect formalisation'. Maybe it was essentially a 'proof refactoring'. Maybe Astra thought some parts could be easier expressed in a certain way, or maybe aspects of the NL proof were kind of handwavey etc.
I don’t. But I do know how the scientific method works, and OpenAI’s display is anything but. Until what they have demonstrated is reproduced I take their claims to be nothing but marketing. A for profit company will lie in order to maximize their profits. Above I presented an alternative hypothesis, which is probably wrong, but until OpenAI’s results are replicated I will believe my alternative hypothesis just as much as I believes the claims of the for profit company making them.
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I’m a non-math layman, and not a scientific method knower like yourself. How does one usually “replicate” a math or Lean proof?
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Hopefully not in the same way you should never naively trust compilers!
They do not. Maybe if they take Lean classes? Maybe starting this year they will but my youngest kid is on their like 5th math class in undergrad and hasn't had any lean at all. Not all undergrad math majors even take PDEs; applied maybe, unless you are doing applied discrete math (graphs, combinatorics).
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Not Lean specifically, but IMO it's pretty straightforward if you've done math and some programming (and at least my school required some programming). Need to prove a forall statement? forall x, P(x) is the same as a function taking x and returning the proof that P(x) is true. Need to prove an exists statement? Create the pair (x, h) that gives the actual x that proves the exists, along with a proof that it satisfies the property you claim. Maybe the only weird thing is that there are types and sets, so sets are kind of automatically more of a subset of some type. The actual Mathlib is more generic, but once you get a hang of writing definitions (as you do in intro proofs), I've found that you can pretty naturally translate whatever you'd have in your undergrad notes. And undergrad should cover defining integers, rationals, reals, relations, functions, sequences, limits, derivatives, integrals, etc. Even if they've never studied solving PDEs, they'd have to take multivariable calculus and know enough to be able to write one (assuming they take at least single variable analysis+linear algebra)? The proofs can get involved and tedious with all of the extra bookkeeping, or techniques to try to reduce the bookkeeping (tactics, etc). But the definitions and statements are pretty much what you'd expect.
Reverse Engineering of the M-VAVE FM-1 Pocket Synthesizer Firmware (github.com/AL-255)
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I know this will not be a popular take, but surely I am not the only one who is super tired of endless control surfaces for the same FM and Karplus-Strong algos. I'm a weirdo, but I love the sound of acoustic and/or sampled instruments - especially drums - over the metallic plonks that supposedly sound like "flute" any day of the week. Don't get me wrong: the M-VAVE is looking like the Flipper Zero of music hacking, and the price is a steal. But at the end of the day, these sounds only really work for certain genres of music and even then there's only so many wavetable shapes before the same-ness has to set in.
Asking as a novice, how come this is such a big deal compared to just vibe coding something for an stm32 and hooking up a midi keyboard? Is it the professional enclosure + screen + hackability combo or something extra?
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I grabbed one of these since I didn't have a hardware FM synth. While playing around with a web-based patch editor and seeing how well synths can run in a web, I started using AI to build out my own synths, and it's been a lot of fun. I've done FM, granular, samplers, 303 and 808 clones, and a bunch of others. So yeah, if you don't care about the experience of having a bespoke device, you could probably one-shot something much more sophisticated than this.
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> 303 and 808 clones It doesn't have nearly enough power for proper circuit modeling. You might as well use samples.
Visa, Mastercard, Major Banks Facing New Litigation over 'Anticompetitive' Fees (classaction.org)
One thing I've noticed with the bigger gas station chains near me is a push to have users download their mobile app, set up ACH payments, and use that as their payment method instead of credit cards in exchange for 10 cents off per gallon. From the merchant side of things, they're paying about $0.60 to process the transaction via ACH, versus $2-$2.50 for credit card transactions, per fill-up. So even if they're merely breaking even once the discounts are factored in, they're still disrupting the credit card companies' dominance. I would not be surprised if rather than continuing to battling it out with the credit card companies to negotiate for lower fees, more and more retailers adapt to the cashless economy by leaning on ACH in lieu of credit cards, especially in market segments where repeat business is common (basically any retailer that has an existing loyalty program). To put it another way: Sure, litigation is an option, but even if you win the concessions you want, it will leave the credit card companies entrenched. Pushing more customers to pay via non-credit-card methods has the benefit of more immediate financial impact, less reliance on the legal system, and deterioration of the power that led to the anticompetitive behavior in the first place.
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I'd be hesitant to give a gas station app ACH access to my checking account. I guess you could open a second account and just transfer enough there to cover your purchases but that's a bit of a nuisance.
Basic reforms that could solve this problem: 1. Merchants need to be allowed to add card processing fees on top of any transaction, and it should be possible to do this very easily. If not this, then any receipt should be required to include card processing fees. 2. Merchants should be allowed to pick and choose which cards they accept without penalty. Those two simple changes would add competitive pressure back into the payment processing market, and quickly cause fees to lower.
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Gas stations near me already have a cash price and a card price per gallon
VISA and MasterCard rules prohibit this, unless specifically allowed by local law.
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*required, not allowed
According to economic theory, price controls produce shortages. It's likely that capping transaction fees would have unintended consequences, for instance excluding millions of customers from being able to get a credit card in the first place. I'm not against all regulation, but I think we should prefer market-based solutions that remove barriers to entry and that allow more companies to compete in the space.
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Europe offers a useful counter-example. They (EU? Most countries? I don't know exactly, but it's immaterial) cap transaction fees, and there's absolutely no shortage of "ways to pay by card". In my experience there are, in fact, more - and, their middle-men have been earlier adopters of both security and convenience features (PIN codes, tap-to-pay, and rapid settlement among them) in which the US sometimes still lags. What there aren't are rampant cash-back rewards for using a particular card. Or easy access to credit cards with usurorious rates. I think missing out on those is a societally good outcome.
There are businesses that specifically don't allow credit cards and only allow Debit and Cash to reduce these fees already and they are still in business. WinCo Foods is the biggest example I know of, so insinuating that it's impossible to operate if you exclude payment method types/cards isn't really true.
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Size matters. WinCo is big enough to do that, because it's a chain and a brand, and people make a choice to go there despite knowing ahead of time that's how it works. (That said, the first time I went into a WinCo I abandoned a cart-load of groceries because I had neither a debit card nor enough cash with me.) That doesn't work for a small business, like the ice cream shop in the example GP offered. They will be giving up a significant fraction of their custom.
I really do not want even more divergence between the price listed and what I actually pay.
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Then pay with cash.
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The divergence is just the fee being placed into the margin you're paying regardless. If you pay via a medium that does not return some of the margin to you in the form of rewards or a 'cash/debit' rebate, then functionally you're paying an invisible tax. This means everyone should be using credit, ideally the highest reward options, which themselves have the highest processing fees, which result in higher prices all around. The creation of higher tiers of rewards and super-premium cards just repeats this cycle, whereby normal cardholders and cash/debit users are now subsidizing high-spend premium card users. Further, large retailers negotiate significantly preferential rates and lower processing fees for their book of business. This means small and medium sized businesses pay significantly more per transaction for processing, meaning they're less competitive and less pricing pressure is placed on large retailers, which again raises prices for you. There's also the card issuer side of things, but in short if you're not changing your credit cards regularly, companies will depreciate rewards and benefits over time in previous lines to move you into a higher margin segment of their portfolio. In short, there's already a divergence, and you're already paying for it in multiple ways.
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> In short, there's already a divergence, and you're already paying for it. even with your optimal strategy, you're still paying for it: those points might as well be already spent at the network of vendors you've agreed to sell your purchase history to it says so in their balance sheets :)
A reminder to listen to the Visa episode of Acquired Podcast if you truly wish to understand the scale of Visa and how it all works. Even at 3+ hours you'll love every minute of it. https://www.acquired.fm/episodes/visa
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Neat! I just discovered this podcast and am more than half way through the Home Depot episode.
> middlemen don't have much value add On the contrary, the middlemen in credit card transactions are providing a service whose value add is so obvious that it's basically invisible, because it's become so normal: financial intermediation. The credit card company is basically covering your debts for you until you pay your monthly bill--and shielding you from having to give every merchant you purchase from your bank account information. On the other side of the transaction, the credit card company is guaranteeing payment to the merchant, who now doesn't have to care about trying to assess the financial reliability of every customer. It's become so normal that we don't realize what a huge value add it is, as compared with, for example, trying to convince the grocery store to accept your check, which forces you to hand them your bank account information, and forces them to decide whether they think you (and your bank) are reliable enough that your check isn't rubber.
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Credit card companies are essentially charging a rake on the consumer economy. They provide a valuable service, but skimming every transaction and funneling it into a handful of private companies is a net detriment for the vast majority of society. They've been at it for decades. First-mover advantage. Entrenchment effect. When CCs are integral to the transaction of money, it's essentially a tax on exchanging money. It's monopolies conducting parasitic toll collection. Consumers shouldn't have to pay a fee to give someone money. Sellers shouldn't have to pay a fee to collect money. Security should be built into the system, not a luxury you're taxed for. See also: the app store, telecoms, health insurance in the US
What india and brazil have is more equivalent to Zelle in the US, not visa/mastercard. There's no viable chargeback, no international interoperability and no fraud protections.
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Chargebacks and fraud protection are largely needed in the credit/debit card system because you go around handing people the key to your safe to merchants and ask them to take whatever they want. And pinky promise not to share the key with anyone else. Once you have sane system like pix or upi, there is far less need for chargebacks and frauds.
> In fact, in 2008 Congress passed a bill specifically mandating a unified toll payment system, but nothing came of it because the bill had no actual teeth. E-ZPass now has interoperability with the Central United States Interoperability Hub (which reaches as far west as Colorado and as far south as Texas). We're much closer to the point where you can drive anywhere with a single transponder than we were back then. The main thing missing now is California cooperating with anyone else. I like the idea of my toll road account also being useful for public transit, if nothing else. But it's difficult to imagine toll road operators and public transit operators seeing a big incentive to cooperate in that way. Even though they're both "pay for transit," their intended/typical users are very different (people who can't/won't drive vs. people who not only drive but are privileged enough to pay for less traffic).
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> I like the idea of my toll road account also being useful for public transit, if nothing else. Halifax, NS used to have bridges where the toll transponders worked to pay for parking at the airport - super convenient. Alas, they've since removed the tolls on the bridges, so the transponders are now useless and traffic in the downtown is even worse.
There are fraudulent customers too, I would say even more often since they have no reputation to uphold. You can see this more in the open on Yelp.
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Customers do have a reputation to uphold. Real-time customer reputation and risk scoring services are a profitable and growing industry. They maintain extremely detailed records of customer interactions with businesses and assign scores to individuals. Returning a defective product to one store, only buying things when you have coupons or promo codes, or issuing a chargeback at one business can get you instantly flagged as a higher risk at countless unrelated stores who are using the same services. Other factors that can impact your score include your income level, your zip code, the devices/software you use, how much money you spend, inconsistencies in the personal information you've given to different businesses, even your attitude when dealing with employees. At least Yelp is public and companies can see how they are rated. Businesses typically won't tell you that you've been branded a high risk for fraud or chargebacks. Instead they'll just apply different prices and polices to you on an individual basis. They might tell you that don't accept certain payment methods. They might tell you they don't accept returns, will only give store credit, or give very narrow return windows. They may reject your business entirely or limit you to only a subset of the products or services they offer.
I've noticed growing use of similar options in the UK already, like Payit and truelayer (often shown in checkout via "Pay by bank"). Ebay and Whetherspoons are examples of places providing these options.
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The issue is in the UK we passed a law that "banned credit card charges", but what it actually did was ban discounts for alternate payment methods being displayed upfront, leading to; everyone has to pay the credit card fees, even if you pay cash being the practical norm. This will mean, its harder for competing payment services to function. And its easier for the big credit card companies to up the % they charge without the public noticing, or blaming them directly. It was fascinating watching the media coverage, twisting themselves in knots to miss these points while cheering how we were 'standing up to the big cc companies', it was actually quite cringe-worthy at times.
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