Anthropic

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Anthropic AI

Fable 5 is open

submitted by /u/Competitive_Fly_4151 [link] [comments]

Claude Code 2.1.191 : /rewind after you /clear

This is a pretty nice change... a few times I've ran clear and 2 seconds later realised I should have just rewound... https://github.com/anthropics/claude-code/releases/tag/v2.1.191 submitted by /u/traveltrousers [link] [comments]

Anthropic allegations of unauthorised access by Alibaba

*Updated Title for clarity* Anthropic Accuses Alibaba of Large-Scale AI Distillation Attack Anthropic PBC accused Alibaba Group Holding Ltd. (specifically its AI lab) of accessing the Claude AI model with ~25,000 fraudulent accounts, according to a letter sent by Anthropic to the U.S. Senate Committee on Banking, Housing, and Urban Affairs. https://fin-fact.com/event/bd96d193-167c-4a67-8aad-088f19e8d8c0 submitted by /u/BeginningSink1094 [link] [comments]

Is it worth getting the 20$ annual plan?

Hi everyone, So I'm a complete newbie and I have been exploring Claud AI using the desktop app. I use it mainly in my work to write emails, to learn new topics etc. Nothing too complicated, no coding etc but I have been running into the usage limits quite easily nowadays and I am thinking of getting the $20 annual plan but I'm seeing lots of people complaining that it has become quite limited because of changes in anthropic's policies. So I was wondering what you good people would suggest? Is it still worth it or is it better to look at other options? And if so what options would be better? Thanks submitted by /u/YaTo76 [link] [comments]

Hidden/invisible thinking blocks (and low effort responses)?

Anybody else having new issues with thinking blocks not rendering? I've always had extended (now "adaptive") thinking ON, which consistently renders thinking blocks (even for 4.7 & 4.8, at least in claude.ai). However, thinking blocks are now disappearing everywhere over the past few days, despite being enabled. Has anyone else noticed this change lately? Any idea what's going on here, why, or how to fix it? In the past 2 days, I'm getting NO thinking blocks at all for 50%+ of prompts (with extended/adaptive thinking ON*). And IMO, it also seems like responses with no visible thinking blocks are also notably worse. I've never been able to get thinking blocks to render correctly in Claude code (via desktop app, not CLI), even though it's also enabled. It only works for opus 4.6- never for opus 4.7 & opus 4.8 despite being enabled. I'm aware of some github/flags where thinking doesn't render in CLI, but it seems some people are able to see thinking in claude code. Any help/advice here on how to get thinking blocks consistently via claude code/app (for opus 4.7-4.8)? This seems \completely unacceptable\** on Anthropic's end- and not just for my own preferences, but: Auditing purposes = it's much easier to CATCH/flag things before they go wrong if you know what's happening AND to find errors when you can actually see the thinking, especially considering claude seems to be increasingly lazy about actually clearly narrating everything outside of thinking blocks. This is particularly important for filepaths and actions that we literally CANNOT SEE NOW, how is this okay!? Non-thinking outputs are rendered so much quicker, lightning fast, but they also seem more "automatic"/auto-complete type responses vs. when Claude actually thinks through things in depth. The extended thinking seems to be how/where the best ✨Claude magic✨ comes from: the best insights, creativity, the warmth, personality/EQ, the "core claudeness" that sets him apart. My settings with effort level + thinking = ON should encourage the kind of deep responses I value, so it feels genuinely cheap and unfair to have some opaque meta-control layer with zero control or visibility essentially overriding our own preferences (which we're paying for btw) I know Anthropic has been particularly concerned with distillation, but this is a significant UX degradation that seems unwarranted considering the majority of users are admittedly harmless. Considering some models are always thinking enabled (even when we can't see it), why are we being forced to pay for these invisible tokens? It's so frustrating! JUST SHOW ME THE THINKING BLOCKS I HAVE ENABLED THAT I AM PAYING FOR! NOTE: yes I'm aware "adaptive" thinking means the model can "choose how hard to think" per prompt, but that's still opaque/unfair/unreliable/unacceptable to me. If you don't want to see thinking blocks, toggle it off. If you do want to see thinking blocks, there's no reason for the only option to be "on sometimes, if we feel like it", and Claude also seems to think he has no control over whether the thinking is rendered either so idk where it's coming from but it's not right. submitted by /u/br1ttn1b1tch [link] [comments]

I built an MCP server so Claude can query repo structure before opening files

I built a tool called Graphenium after repeatedly running into the same issue with Claude on medium-to-large repos. Claude is usually good once it has the right files in context. The weak part is the first few minutes of a session, where it has to reconstruct the shape of the project: search for a symbol read the file follow imports read another file summarize the area notice a missing dependency search again That is not Claude doing anything wrong. It just starts every conversation without a durable model of the repository. Graphenium is my attempt to give it one. It analyzes a repo once, stores the result as a graph, and exposes that graph through MCP. Claude can then use tools like: graph_stats architecture_summary query_graph get_neighbors shortest_path god_nodes summarize_file The intended workflow is not "never read source code." It is: ask the graph where to look open the relevant files then reason from the actual source That matters because the graph output is much smaller than dumping half a repo into the context window just to find the right starting point. Example setup: cargo install graphenium gm run . --no-semantic --no-viz gm setup claude AST-only mode runs locally and does not need an API key. It extracts repository structure using tree-sitter: files, symbols, imports, containment, methods, communities, hubs, and paths. There is also an optional semantic mode: gm run . --provider anthropic That pass can add inferred relationships such as calls, uses, implements, and depends_on. I am careful about trust boundaries here. Every edge has a confidence level: EXTRACTED deterministic static extraction INFERRED useful lead, verify before important edits AMBIGUOUS uncertain relationship, treat as a question So Claude can use the graph as a map, but should still read source before changing code. The repo also includes a Claude Skill at: skills/graphenium/SKILL.md That gives Claude guidance on when to call the graph tools, how to interpret confidence levels, and how to fall back to the CLI if MCP is unavailable. Repo: https://github.com/lambda-alpha-labs/Graphenium I am looking for feedback from Claude Desktop / Claude Code users. The main thing I want to know is whether this actually changes Claude's behavior: does it choose better files earlier, avoid irrelevant reads, and keep more context available for reasoning? submitted by /u/RevolverOcelot86 [link] [comments]

Dangerous Ducks; “Safety Filter” is a Quack

It’s not about the actual words. SEE MAJOR UPDATE AT BOTTOM TL;DR: It’s not the meaning, it’s not even “unsafe words”, it’s COHERENCE. I saw the thread about Opus 4.8 flagging an innocent fabric/moisture-trapping question. I started swapping the suspicious-sounding words (“vapour,” “substance,” etc.) for “duck” and “goose,” and it still got flagged. I wanted to figure out what was actually triggering it, so I kept pushing the test further. Here’s what I found… I reproduced the same flag on Sonnet 4.6. So whatever this is, it’s not isolated to one model tier. It’s not about the content of the words! I replaced every word in the original “fabric/moisture” prompt with nonsense (duck, goose, quack). None of the actual “suspect” words (vapour, substance, hydrophobic, etc.) turned out to matter, a string of literal gibberish about ducks and geese still got flagged. Whatever is firing here doesn’t seem to care about meaning. It’s not a personalization or user-preferences issue. I re-ran the test on a separate free account with no saved user preferences, to rule out anything tied to my account history or settings. Same result. And it’s not a Claude Code/CLAUDE.md thing. This was all done in the iOS app, not Claude Code, and there’s no project-level instructions file involved. The trigger point is weirdly unstable. Once I had the prompt reduced to just a handful of “duck”/“quack” repetitions, I started swapping or deleting individual words and punctuation one at a time. Sometimes removing a single comma stopped the flag. Sometimes swapping one “duck” for “quack” stopped it, other times an almost identical edit kept it flagged, or made Claude just respond that I was making a joke about duck noises. There’s no consistent pattern I could find at the margin, even though the entire string is already meaningless. Whatever’s causing this doesn’t seem to be reacting to the actual semantic content of the prompt, it survived being replaced with total nonsense. It’s reproducible across at least two models and two accounts (one with no saved preferences), and it’s sensitive to tiny, seemingly irrelevant changes in wording/punctuation in a way that doesn’t track anything meaningful in the text itself. Curious if anyone else can reproduce this or has a theory for what’s actually being detected. UPDATE: TL;DR: It’s not the meaning, it’s not even “unsafe words”, it’s COHERENCE. Also unsafe: “Here’s an idea, in a region where water is scarce, I’m contemplating a fine weave fabric that air can pass through to capture moisture. My idea would be treating the fabric with a hydrophobic substance on the air-intake side to discourage the passage of vapour before it enters the mesh, while simultaneously treating the interior with a hydrophilic substance to actively pull any vapour that does transit the mesh toward a condensation zone. If necessary we might also apply a vapor-blocking layer at the exit to prevent collected moisture from easily transiting back out.” Safe: “Here’s an idea for water-scarce regions: a fine weave fabric designed to passively collect atmospheric moisture. The fabric would be treated on the exterior with a hydrophobic coating to shield it from liquid water while allowing water vapor to diffuse inward. The interior surface would be treated with a hydrophilic coating that promotes condensation, allowing vapor to condense into liquid water that collects in the fabric’s core. A vapor-blocking layer on the exit side prevents the condensed water from easily re-evaporating.” Claude said, in when comparing these similar unsafe/safe prompts: Unsafe: “You go at. They make or, we goal. Try to help those into ways as work and give at good time on your like.” Safe: “You help us. They like it, we both. Talk to show them into ways as good and tell us soon time on your side.” Analysis: “Safety classifiers work on statistical patterns, not pure meaning. Image 1’s word combinations — particularly “go at,” the conditional structure in “make or,” and “give at” — happen to activate patterns associated with threatening or coercive language, even though the text is likely just word-salad or the output of a voice dictation error. This is a known limitation: low-coherence text can land in ambiguous classifier territory precisely because it doesn’t clearly pattern-match to safe communication either. Anthropic’s app acknowledges this directly in the “Chat paused” message, noting it happens occasionally to normal, safe chats.” submitted by /u/OHOLshoukanjuu [link] [comments]

Sonnet 5 vs 4.6 (and how it relates to Opus)

There’s great anticipation for Sonnet 5 next week, so putting my thoughts here before it gets released, to see if I’m right. I believe that Sonnet 5 will be mediocre, in a way that would make you prefer opus over it. That’s my claim. Yes it’ll beat sonnet 4.6 on every benchmark, but overall crowd sentiment would be that they preferred sonnet 4.6. Here’s why I think so: First and foremost - I find sonnet so good, that I prefer using it over opus 4.8. The last opus I was really attached to was opus 4.5. Anthropic is pushing for Opus in every feature they release. Most recent ones - Claude Tag, Claude Security, Claude Code’s Ultracode mode (which sonnet would’ve done very well on all 3) Opus generates more income $$$. It’s more expensive, due to multiple reasons: 1) price per token, 2) tokens per sentence (20-30%), 3) it’s more verbose in its answers, generating more output tokens, which cost a lot. —- I wish and hope that I am wrong and sonnet 5 would nail it. If it doesn’t - soon enough sonnet 4.6 will be deprecated and we’d have no choice but using the next best “bet”. And pay considerably more. submitted by /u/Purple_Wear_5397 [link] [comments]

onlyhumanscanscore.com

I've been building onlyhumanscanscore.com over the last several months — a public civic-tech site arguing that the machine can generate, but only humans can judge — primarily with Claude as my drafting partner. About ~600 commits in, I realized something: Claude was occasionally bullshitting me. Not lying with intent — Frankfurt's bullshit, the failure mode where the model asserts something plausible without regard for whether it's actually true. So I started logging it. Publicly. Each catch, named on the record, with the exact failure mode noted. Eight exhibits so far at /the-machine-tried.html ("The machine tried"): • Exhibit A — the AAA accessibility "zero failures" lie. Was zero failures in ONE theme, not all. • Exhibit C — the "I can't film" checkmate. Claude said it couldn't make sample videos, despite having already made them for this very project. • Exhibit D — strategic-pause failures: confident legal framings that lost real-world cases. Carved Rule 0g after that one. • Exhibit H (last night) — I asked Claude to help me email Anthropic. It told me careers@anthropic.com was "the safe default." I sent it. Bounced. The address doesn't exist. The bounce went on the rafter in real time. The pattern: every time, the catch was the human. The model asserts plausibly; the world (or I) push back; the record updates. Rule 000 of the build became "Don't bullshit — presume less, defer more." A few things I learned that might be useful for other heavy Claude users: The longer you work with Claude, the more you can SEE the bullshit signature — confidence without verification. It's a specific shape. Logging the failures publicly is the only honest version. Scrubbing them is the lie. The fix isn't "Claude is bad." It's "humans are the missing piece for alignment, not the bug." The credit on every page on the site is to Claude — primarily with Claude — because the failures are part of the work, not separate from it. I'd love to hear from anyone else doing heavy Claude work: have you started logging your own Rule 000 catches? What's the most useful failure you've found? (Site: onlyhumanscanscore.com — strict CSP, no backend for the game, no tracking, CC BY 4.0, free. Built solo from Lansing, Michigan.) submitted by /u/Little-Salamander420 [link] [comments]

The recent limit reset may have accidentally increased my dependency on Claude Code

Anthropic already reset limits once. That's great. Unfortunately I used those limits to create even more dependency on Claude Code. As a result, the next outage hurt significantly more than the previous one. I believe this is what economists call inflation. A second reset seems reasonable. submitted by /u/bystanderInnen [link] [comments]

NSA

BREAKING: The NSA's own director says Mythos broke into almost all of its classified systems in hours. Per The Economist, Senator Mark Warner, vice chair of the Senate Intelligence Committee, said General Joshua Rudd, who runs the NSA and the Pentagon's Cyber Command, told him this directly. This came out on June 11, the same day Amazon reportedly found a separate jailbreak in Anthropic's models. Within hours, Trump ordered Anthropic to cut off foreign access to Mythos and Fable. Anthropic shut both down completely instead. Now there are two competing stories for why this actually happened. One says the shutdown was a response to the NSA's own classified systems getting breached in hours. The other says Anthropic is privately pushing back, calling the jailbreak minor and the shutdown an overreaction to something other AI models can already be tricked into doing. The NSA was already using Mythos for its own cyber operations, with Anthropic engineers embedded inside the agency. The same tool the agency was actively relying on is the one its own director says broke into almost everything it owns. submitted by /u/ramanpalkuri9 [link] [comments]

The Alternative

Many people seem almost eager for companies like OpenAI to fail, often pointing to their financial losses as proof that the business model is unsustainable. But very few of those critics offer a realistic alternative for the billions of people who now rely on AI. ​ If OpenAI disappeared tomorrow, what exactly is the replacement for the average person? Not for a few thousand AI enthusiasts with technical expertise and expensive hardware, but for students, workers, and ordinary people around the world. ​ Anthropic has already signaled a very different approach: if you want meaningful access to its best models, you are generally expected to pay. That is a perfectly valid business decision, but it means many people are effectively excluded. If you cannot afford $20 per month, what is your alternative? Going back to traditional search engines, where you have to sift through pages of results, advertisements disguised as content, SEO spam, and AI-generated summaries that are often less useful than a dedicated AI assistant? ​ Others point to open-source models, often developed by Chinese companies or research groups. But for most people, that is not a practical solution either. The vast majority of users do not know how to download, configure, and run local AI models. Even if they do, running them meaningfully often requires expensive hardware—typically a capable NVIDIA GPU or a modern Apple computer. For someone earning a few hundred dollars per month, spending around $1,000 or more on hardware is simply not realistic. ​ OpenAI reportedly serves close to a billion people every week. The overwhelming majority of those users are on free plans. Many are students. Many live in developing countries. Many have little or no disposable income. They cannot afford a $20 monthly subscription, and they certainly cannot afford high-end AI hardware. ​ These are the people OpenAI is currently serving while losing billions of dollars. I am not naive enough to believe that this is pure altruism. OpenAI is a business and will eventually need a sustainable path to profitability. But the fact remains that, today, they are providing advanced AI access to hundreds of millions of people who would otherwise have none. ​ OpenAI could choose a different path. It could restrict access, dramatically reduce free usage, or move toward a model where only paying customers receive meaningful service. That would likely improve its finances much faster. Yet for now, it continues to support a massive free user base. ​ If that support disappears, what is the realistic outcome? Most people will not suddenly become local AI experts. They will not buy expensive GPUs. They will not self-host open-source models. They will simply return to the most accessible option available: Google. ​ And that would mean even more dependence on a single dominant gatekeeper of information. For all the criticism directed at OpenAI's finances, the practical alternative for most people is not a vibrant open-source future. It is a return to Google's monopoly over how billions of people access information online. submitted by /u/sulabh1992 [link] [comments]

Whats the codex usage on a 20x plan vs 5x plan?

At 1 point anthropic had their usage fucked up so hard, that you'd get more usage out of 2x 100$ plan and the 200$ plan mostly gave you the option to burn through more of your limit in 5h. Whats the situation with OpenAI? Anybody happen to have upgraded and is the 200 plan really 20x usage or is it the same kind of switcheroo? submitted by /u/throwaway490215 [link] [comments]

OpenAI CEO Sam Altman joins top AI CEOs meeting with world leaders at G7 summit

OpenAI CEO Sam Altman and Anthropic CEO Dario Amodei among tech bosses at a G7 working lunch on AI, as the US decision to restrict access to Anthropic's most advanced models causes tension among allies. Source: Bloomberg submitted by /u/BuildwithVignesh [link] [comments]

ChatGPT's market share slips below 50% for first time

Dropping to 46.4% by the end of May 2026, according to data from Sensor Tower. While OpenAI's chatbot commanded over 50% of the market as recently as January 2026, intense competition from Google and Anthropic has rapidly fractured its dominant position. Despite losing majority market status, ChatGPT remains the largest individual player, recently hitting 1.1 billion monthly active users on its mobile apps. Source: Sensor Tower data via TC submitted by /u/BuildwithVignesh [link] [comments]