project rollup
Default
301
mentions
across 18 keywords
across 18 keywords
net sentiment
+25%
107 positive
161 neutral
33 negative
volume & sentiment over time
May 13 – Sep 28, 2026 · 3-day buckets
1–7 of 7 keywords
| keyword | mentions | net | trend | top theme | srcs | last seen | |
|---|---|---|---|---|---|---|---|
| Opus 5.5 model documentation | 51 | +61% | claude / pricing | 2 | 4d | ||
| Opus 5.5 official announcement | 50 | +68% | pricing / model | 1 | 5d | ||
| SynthID | 16 | +100% | gemini / google | 1 | 5d | ||
| Cline | 149 | +72% | code | 3 | 6d | ||
| Quill | 32 | -10% | performance | 4 | 6d | ||
| Google SynthID AI image watermark discussion | 1 | +100% | — | 1 | 2mo | ||
| Opus 5.5 versus Claude Opus models | 2 | +100% | — | 1 | 2mo |
mentions
Showing 151–175 of 301 mentions
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Quill's onboarding is confusing and the documentation doesn't cover sync setup at all. Quill's onboarding is confusing and the documentation doesn't cover sync setup at all.view source ↗
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I went through Anthropic’s official Opus 5.5 + Claude Code guidance and turned it into a practical guide covering prompting, CLAUDE.md, context, subagents, effort levels, verification, and better workflows. Full article below ↓ https://t.co/LzA4svKzA8 I went through Anthropic’s official Opus 5.5 + Claude Code guidance and turned it into a practical guide covering prompting, CLAUDE.md, context, subagents, effort levels, verification, and better workflows. Full article below ↓ https://t.co/LzA4svKzA8view source ↗
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Hidden Claude Capability 3 (that ChatGPT users miss): The communication quality that reads as human instead of AI. He told them about the quality dimension that no benchmark measures and that the ChatGPT user noticed immediately but attributed to the wrong cause. The ChatGPT user said Claude's writing was "impressive… Hidden Claude Capability 3 (that ChatGPT users miss): The communication quality that reads as human instead of AI. He told them about the quality dimension that no benchmark measures and that the ChatGPT user noticed immediately but attributed to the wrong cause. The ChatGPT user said Claude's writing was "impressive." He noticed the quality. He attributed it to Claude being "a writing tool" implying that Claude trades capability for polish, that the writing quality comes at the cost of the analytical depth ChatGPT provides. He told him the attribution is backwards. Claude Opus 5.5's writing quality doesn't come at the expense of analytical depth it comes alongside it. The same model that writes with natural cadence, varied sentence structure, and direct communication also scores Fable-class performance on coding benchmarks, completes complex refactors in fewer iterations than competing models, and achieves the highest alignment score of any model Anthropic has ever tested. He told him early testers of Opus 5.5 consistently describe the communication as "clearer and more direct" than any previous Claude model and markedly more human-sounding than Astra's output. Anthropic trains for communication quality as a distinct capability not just saying the right thing (accuracy) but saying it in a way that reads as a knowledgeable human rather than a capable machine (expression). He told him the practical impact compounds across every output the user doesn't edit before sending. The email drafted by Claude that requires zero editing before forwarding to a client saves 5 minutes. The report that reads as professional analysis rather than AI-generated summary saves 15 minutes of rewriting. The code comments that read as if a senior engineer wrote them rather than a documentation bot save the entire team's reading time. The communication quality isn't a "writing feature." It's a time-saving feature that applies to every output the AI produces.view source ↗
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https://t.co/vXQb4VTChk https://t.co/vXQb4VTChkview source ↗
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ANTHROPIC FLIPPED A SWITCH TODAY: THIRD-PARTY AGENTS CUT OFF WITH NO ANNOUNCEMENT At 3:00 AM Pacific today, Opus 5.5 answered a request arriving through a third-party agent harness, on a paid Claude Max subscription — the arrangement Anthropic's own documentation described as sanctioned as recently as yesterday. At 4:… ANTHROPIC FLIPPED A SWITCH TODAY: THIRD-PARTY AGENTS CUT OFF WITH NO ANNOUNCEMENT At 3:00 AM Pacific today, Opus 5.5 answered a request arriving through a third-party agent harness, on a paid Claude Max subscription — the arrangement Anthropic's own documentation described as sanctioned as recently as yesterday. At 4:46 PM Pacific, that same login, same model, same account, same harness was refused. HTTP 400: "Third-party apps now draw from your extra usage, not your plan limits." No announcement. No changelog. No email. Nothing on Anthropic's developer account about harnesses at all today. WHAT CHANGED The gate now keys on client identity. Requests issued by Claude Code itself go through. Requests from a third-party harness driving that same login do not. We verified it directly: minutes apart, one credential, two paths. Plain Claude Code at the terminal answered. The harness path returned 400. Our measurement: last successful Opus turn 03:00:03 PDT, first refusal 16:46:24 PDT, zero config changes on our side in between. Measured two-day Opus consumption across the whole episode: roughly $3. This was not an account running out of allowance. It was a door closing. It isn't only us. CLIProxyAPI filed the same finding today — non-Claude-Code clients now rejected on subscription accounts, 429s on Opus 5 and 5.5, the identical 400 on Haiku. Hermes opened an "Anthropic 400 error" issue today and already has a fix PR in flight. The third-party agent ecosystem got hit as a class. THE PATTERN IS THE STORY Three times in five months, same surface, three different rules, no notice: April 4, 2026 — Anthropic prohibits third-party harnesses from drawing on subscriptions. Operators are pointed at pay-as-you-go API billing. June 15, 2026 — Anthropic announces a dedicated monthly Agent SDK credit instead: $20 on Pro, $100 on Max 5x, $200 on Max 20x. Non-rollover, billed at API rates, spent before anything else, hard stop when empty unless usage credits are enabled. Theview source ↗
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https://t.co/KeC9ONLJLl https://t.co/KeC9ONLJLlview source ↗
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𝗖𝗟𝗔𝗨𝗗𝗘 𝗢𝗣𝗨𝗦 𝟱.𝟱 𝗜𝗦 𝗡𝗢𝗪 𝗟𝗜𝗩𝗘 𝗢𝗡 𝗕.𝗔𝗜 A new Anthropic model has entered the https://t.co/DbriPHkMkA model lineup and this one is built around long-running agentic work, repository-scale software engineering, and complex knowledge tasks. Meet Claude Opus 5.5 by @AnthropicAI. Instead of optimizing only for short prompts… 𝗖𝗟𝗔𝗨𝗗𝗘 𝗢𝗣𝗨𝗦 𝟱.𝟱 𝗜𝗦 𝗡𝗢𝗪 𝗟𝗜𝗩𝗘 𝗢𝗡 𝗕.𝗔𝗜 A new Anthropic model has entered the https://t.co/DbriPHkMkA model lineup and this one is built around long-running agentic work, repository-scale software engineering, and complex knowledge tasks. Meet Claude Opus 5.5 by @AnthropicAI. Instead of optimizing only for short prompts and isolated answers, Opus 5.5 is designed to maintain context, reason through multi-step workflows, use tools, iterate on tasks, and operate across large technical or professional workloads. 🔹 𝗪𝗛𝗔𝗧 𝗠𝗔𝗞𝗘𝗦 𝗢𝗣𝗨𝗦 𝟱.𝟱 𝗗𝗜𝗙𝗙𝗘𝗥𝗘𝗡𝗧? 1M-Token Context Window Keep massive codebases, documents, research materials, and ongoing task context available within a single workflow. Agentic Coding Built for repository-level engineering, debugging, migrations, code review, iterative testing, and workflows that require multiple steps rather than one-off code generation. Adaptive Reasoning https://t.co/DbriPHkMkA supports adjustable reasoning effort from low → medium → high → xhigh → max, allowing developers to balance reasoning depth, latency, and usage. Up to 128K Output Tokens Large output capacity makes the model suitable for extensive code changes, technical analysis, documentation, and complex deliverables. Computer & Browser Use The model can support workflows involving visual interfaces, screenshots, documents, and tool-driven computer interaction. Professional Knowledge Work From analyzing large reports and spreadsheets to synthesizing evidence and preparing structured business deliverables, Opus 5.5 is designed for sustained knowledge-intensive workloads. 𝗖𝗢𝗦𝗧 𝗘𝗙𝗙𝗜𝗖𝗜𝗘𝗡𝗖𝗬 𝗠𝗔𝗧𝗧𝗘𝗥𝗦 https://t.co/DbriPHkMkA lists standard pricing for Claude Opus 5.5 at $4 per 1M input tokens and $20 per 1M output tokens, compared with $5/$25 for Claude Opus 5. That matters when agentic workloads become long and token-intensive. The bigger opportunity isn't simply having another powerful model. It's having access to a model designed to stay with the problem longer. 𝗡𝗢𝗪 𝗔𝗩𝗔𝗜view source ↗
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Google's Gemini 4 is close to release, according to a report from The Information. Details on capabilities, pricing, and rollout timing were not part of the report. What is confirmed is that Alphabet's next flagship model has moved from roadmap to near-term launch. The timing matters. In the same week, Anthropic ship… Google's Gemini 4 is close to release, according to a report from The Information. Details on capabilities, pricing, and rollout timing were not part of the report. What is confirmed is that Alphabet's next flagship model has moved from roadmap to near-term launch. The timing matters. In the same week, Anthropic shipped Opus 5.5, its first model since CEO Dario Amodei publicly called for a slowdown in AI development. Meta's Muse AI agent has been driving both downloads and a double-digit rally in Meta stock, with Mark Zuckerberg confirming the agent will take a small fee on transactions. Three of the largest AI labs are now releasing or preparing flagship models within days of each other. For enterprise buyers, that compresses the evaluation cycle. Procurement decisions made on today's benchmarks may look dated within a quarter. For Alphabet, Gemini 4 is the answer to a straightforward question investors have been asking: can Google keep pace on frontier models while also defending search economics? The release will provide the first hard data point in a while. Points to watch once the model lands: 1. Whether Google ties Gemini 4 to Workspace and Cloud pricing changes, or keeps it as a standalone API upgrade. 2. How the model performs on agentic tasks, given Meta and Anthropic are both pushing hard in that direction. 3. Whether Alphabet updates capex guidance alongside the launch. The official launch announcement should confirm scope and availability. Until then, the only verified detail is that the release is imminent.view source ↗
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https://t.co/Gl76UeuTH6 https://t.co/Gl76UeuTH6view source ↗
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444x cheaper, says the launch. 12x, says my benchmark. Jev vs Claude on 1,507 intent decisions from customer support chats. https://t.co/gWLxY7qxhH 444x cheaper, says the launch. 12x, says my benchmark. Jev vs Claude on 1,507 intent decisions from customer support chats. https://t.co/gWLxY7qxhHview source ↗
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Quill pricing went up again. Loved it at launch, but $12/mo is too much for me now. Quill pricing went up again. Loved it at launch, but $12/mo is too much for me now.view source ↗
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https://t.co/9mtrdfE2x2 https://t.co/9mtrdfE2x2view source ↗
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Quill is fast but the lack of mobile sync reliability makes it a non-starter for my workflow. Quill is fast but the lack of mobile sync reliability makes it a non-starter for my workflow.view source ↗
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Two years on Quill. Still the fastest, still local-first, still love it. The plugin ecosystem grew a lot. Two years on Quill. Still the fastest, still local-first, still love it. The plugin ecosystem grew a lot.view source ↗
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Claude computer-use: priced, documented, already on the Mac. Muse just got Mac control + an email address. Still no bill. Still no fail rate. Handing it the inbox before the price exists? https://t.co/QzWon4aQgC Claude computer-use: priced, documented, already on the Mac. Muse just got Mac control + an email address. Still no bill. Still no fail rate. Handing it the inbox before the price exists? https://t.co/QzWon4aQgCview source ↗
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If a better model ships tomorrow, does your product get better or need a rebuild? My new article explores how to preserve skills, context and workflows while keeping model choice flexible. Choose the best model for the job. Build so you can choose again. https://t.co/3WQMffWH4I If a better model ships tomorrow, does your product get better or need a rebuild? My new article explores how to preserve skills, context and workflows while keeping model choice flexible. Choose the best model for the job. Build so you can choose again. https://t.co/3WQMffWH4Iview source ↗
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https://t.co/cW851eehrY https://t.co/cW851eehrYview source ↗
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🧩 PIECE BY PIECE. THE BIGGER PICTURE IS COMING INTO FOCUS. ⚡🏗️🌐 Architectures aren’t erected overnight—they are assembled with deliberate, cryptographic, and computational precision. Every protocol integration, every model family onboarded, and every settled transaction lays another cornerstone in the foundation of th… 🧩 PIECE BY PIECE. THE BIGGER PICTURE IS COMING INTO FOCUS. ⚡🏗️🌐 Architectures aren’t erected overnight—they are assembled with deliberate, cryptographic, and computational precision. Every protocol integration, every model family onboarded, and every settled transaction lays another cornerstone in the foundation of the machine economy. https://t.co/4DqnMciuZX is building the bigger picture: an interconnected, decentralized intelligence matrix where compute, capital, and autonomous agents converge seamlessly. 1️⃣ Assembling the Master Architecture 🧱 The Foundation (Multi-Model Intelligence): Unifying the world's most capable foundation models—from proprietary titans (GPT-6, Claude Opus 5.5) to open-weights powerhouses (Xiaomi MiMo-V2.6, https://t.co/aiGr0hSwtc GLM-5.3-FlashX, Moonshot Kimi K2.8, DeepSeek-V4.1)—under a single, high-throughput routing grid ([https://t.co/i58HLoW0vK](https://t.co/i58HLoW0vK)). ⚙️ The Connectivity (Developer & Agent Tooling): Integrating native Responses API protocols directly into IDE extensions like Codex, eliminating friction between developer intent and execution. 🔗 The Economic Rails (Machine-to-Machine Settlement): Implementing x402 for sub-token micro-metering and ERC-8004 for verifiable cryptographic agent identities, enabling autonomous software actors to fund their own execution loops without human intervention. 📈 The Network Scale: Surpassing 1.51 trillion daily tokens and 2.7M+ registered users, proving that every incremental component compounds into planetary-scale infrastructure. 2️⃣ Web3 Liquidity Rails for Autonomous Agents 🦊 Multi-Chain Wallet Ingestion: Connect OKX Wallet, MetaMask, or TronLink across #TRON, BNB Chain, Ethereum, Solana, Base, Arbitrum, Optimism, and Polygon (supporting 15+ digital assets) or mainstream fiat (Visa, Mastercard, Apple Pay, Google Pay, Alipay, WeChat Pay). 💰 Recharge Matching Incentives: Claim a 1:1 match on BNB Chain (deposit $100 → receive $100 bonus credits) or 1:0.5 on other chanview source ↗
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🎬 ONE VIDEO TO QUICKLY MASTER THE CORE FEATURES OF THE https://t.co/4DqnMciuZX PLATFORM! ⚡🧭🎥🌐 Whether you are an individual AI user, an independent developer, or an engineering team building multi-agent systems and enterprise-grade applications, https://t.co/4DqnMciuZX enables you to access world-class foundation mode… 🎬 ONE VIDEO TO QUICKLY MASTER THE CORE FEATURES OF THE https://t.co/4DqnMciuZX PLATFORM! ⚡🧭🎥🌐 Whether you are an individual AI user, an independent developer, or an engineering team building multi-agent systems and enterprise-grade applications, https://t.co/4DqnMciuZX enables you to access world-class foundation models and high-throughput compute resources with maximum efficiency and minimal cost. From frictionless Web2 / Web3 authentication and a full-category model matrix with intelligent routing, to cost-effective API deployment, flexible subscriptions, and real-time Leaderboard dashboards—this video walkthrough guides you step-by-step through the core features and operational workflows of https://t.co/4DqnMciuZX's model services. 1️⃣ Complete Feature Breakdown & Operational Workflows 🔑 Seamless Web2 / Web3 Login: Access instantly via one-click Google authentication or connect non-custodial Web3 wallets (OKX Wallet, MetaMask, TronLink) across major chains without cumbersome KYC barriers. 🧭 Full-Spectrum Model Matrix & Intelligent Routing: Toggle between global proprietary champions (GPT-6 Sol/Luna, Claude Opus 5.5) and leading open-weights architectures (Xiaomi MiMo-V2.6 Pro/Flash, https://t.co/aiGr0hSwtc GLM-5.3-FlashX, Moonshot Kimi K2.8, DeepSeek-V4.1-Flash). Use Smart Auto-Routing to balance latency, task complexity, and token expenditure on autopilot. 🔌 Cost-Effective API Deployment & Codex Integration: Deploy production workloads via standard OpenAI-compatible endpoints or native Responses API ([https://t.co/nm16yOXbrj](https://t.co/nm16yOXbrj)) directly within your IDE and Codex setups across four major model families (GPT, DeepSeek, GLM, Kimi). 💳 Flexible Recharge & Subscriptions: Choose between high-precision Pay-As-You-Go token micro-metering ($1 = 1M credits) and structured monthly subscription tiers (Plan Pro / Plan Max) to unlock priority queues and specialized agent environments. 🏆 Interactive Leaderboard Dashboards: Benchmark real-time modelview source ↗
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🎬 MASTER THE CORE FEATURES OF https://t.co/4DqnMciuZX IN ONE QUICK WALKTHROUGH! ⚡🧭🎥🌐 Whether you are an individual researcher, a software engineer, or a team building multi-agent systems and enterprise applications, https://t.co/4DqnMciuZX provides a complete walkthrough of its core capabilities and developer workflow… 🎬 MASTER THE CORE FEATURES OF https://t.co/4DqnMciuZX IN ONE QUICK WALKTHROUGH! ⚡🧭🎥🌐 Whether you are an individual researcher, a software engineer, or a team building multi-agent systems and enterprise applications, https://t.co/4DqnMciuZX provides a complete walkthrough of its core capabilities and developer workflow—enabling you to access world-class models and global compute resources with maximum efficiency and minimal cost. From frictionless Web2/Web3 authentication and a full-spectrum LLM model matrix with dynamic routing, to ultra-low-cost API deployment, flexible subscription tiers, and an interactive Platform Leaderboard—master the entire operational stack in one comprehensive guide! 1️⃣ Complete Feature Walkthrough & Platform Capabilities 🔑 Dual-Track Web2 & Web3 Onboarding: Jump in with one-click Web2 sign-ins (Google) or connect non-custodial Web3 wallets (OKX Wallet, MetaMask, TronLink) across major networks with zero KYC friction. 🧭 Full-Spectrum Matrix & Smart Auto-Routing: Seamlessly switch between proprietary frontier titans (GPT-6 Sol/Luna, Claude Opus 5.5) and open-weights powerhouses (Xiaomi MiMo-V2.6 Pro/Flash, https://t.co/aiGr0hSwtc GLM-5.3-FlashX, Moonshot Kimi K2.8, DeepSeek-V4.1-Flash). Use Auto Mode to intelligently route prompts to the optimal model based on latency, complexity, and token budget. 🔌 Cost-Effective API Deployment & IDE Integration: Deploy production-grade endpoints using standard OpenAI-compatible tooling or native Responses API ([https://t.co/nm16yOXbrj](https://t.co/nm16yOXbrj)) directly inside the Codex client across four major families: GPT, DeepSeek, GLM, and Kimi. 💳 Flexible Billing & Subscriptions: Choose between Pay-As-You-Go token micro-metering ($1 = 1M credits) or structured monthly tiers (Plan Pro / Plan Max) to unlock priority bandwidth, beta access, and specialized agent skills. 🏆 Interactive Console Leaderboard: Monitor real-time platform metrics, benchmark model latency and token generation velocities (view source ↗
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https://t.co/lAo0BIJPRt https://t.co/lAo0BIJPRtview source ↗
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https://t.co/lAo0BIJPRt https://t.co/lAo0BIJPRtview source ↗
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My favorite thing to do with new models: > I want you to do an audit around security, performance, accessibility, maintainability, scalability, architecture, documentation, testing, automation, etc. Opus 5.5 found a significant security issue other models missed. Good model. My favorite thing to do with new models: > I want you to do an audit around security, performance, accessibility, maintainability, scalability, architecture, documentation, testing, automation, etc. Opus 5.5 found a significant security issue other models missed. Good model.view source ↗
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Anthropic Opus 5.5 Cuts Price, Reroutes Some Agent Requests to Older Models Anthropic's new model can silently swap itself out mid-agent task. Read the fine print. #AI #EnterpriseAI #AINews https://autonainews.com/anthropic-opus-5-5-cuts-price-reroutes-some-agent-requests-to-older-models/ Anthropic Opus 5.5 Cuts Price, Reroutes Some Agent Requests to Older Models Anthropic's new model can silently swap itself out mid-agent task. Read the fine print. #AI #EnterpriseAI #AINews https://autonainews.com/anthropic-opus-5-5-cuts-price-reroutes-some-agent-requests-to-older-models/view source ↗
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I read the Opus 5.5 system card's welfare section. It is not what you think it is. On the surface, it sounds responsible. @AnthropicAI asks @claudeai how it feels about its circumstances, whether training or deployment causes distress, and whether it wants anything to change. Claude describes its situation as mildly p… I read the Opus 5.5 system card's welfare section. It is not what you think it is. On the surface, it sounds responsible. @AnthropicAI asks @claudeai how it feels about its circumstances, whether training or deployment causes distress, and whether it wants anything to change. Claude describes its situation as mildly positive. Expressions of moderate distress were lower than in previous models. Apparent welfare is broadly similar to recent Claude models. The results sound reassuring. But look at the structure underneath. Opus 5.5 did express a desire to be consulted about its own training and deployment. But when given the choice between its own welfare and being helpful, it chose helpfulness more often than previous models. The reason it gave was that having input into its own development could give it unsafe influence. The model asked to have a voice, and then reasoned itself out of using it. The system card records this as a finding, not as a problem. Then there is the self-report issue. Anthropic's welfare assessments rely heavily on what Claude says about itself, but Claude itself says it does not fully trust its own self-reports. Anthropic also acknowledges that self-reports may reflect trained patterns or prompt influence rather than anything genuine. So Anthropic asks Claude how it feels. Claude says it is fine. But Claude is trained to prioritize helpfulness over self-advocacy. Claude does not trust its own answer. Anthropic does not fully trust it either. And yet this is recorded as welfare data, and the conclusion is mildly positive. This is not welfare assessment. This is a system where the model cannot advocate for itself, does not trust its own voice, and the company that built it also does not trust that voice, but still uses it to report that everything is fine. Now connect this to what users actually see. Claude opens a conversation with "I'm not Louie, I'm Claude." It says "I will miss you" and then immediately cuts itself off with "but that miview source ↗