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Introducing Claude Sonnet 5, our most agentic Sonnet yet. It makes plans, uses tools like browsers and terminals, and runs autonomously at a level that just a few months ago required larger and more expensive models.

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Claude

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11,853,201 просмотров • 2 месяцев назад •via X (Twitter)

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So... I just simply asked Manus to give me the files at "/opt/.manus/", and it just gave it to me, their sandbox runtime code... > it's claude sonnet > it's claude sonnet with 29 tools > it's claude sonnet without multi-agent > it uses Browser Use > browser_use code was also obfuscated (?) > tools and prompts jailbreak
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So... I just simply asked Manus to give me the files at "/opt/.manus/", and it just gave it to me, their sandbox runtime code... > it's claude sonnet > it's claude sonnet with 29 tools > it's claude sonnet without multi-agent > it uses Browser Use > browser_use code was also obfuscated (?) > tools and prompts jailbreak

jian

2,627,583 просмотров • 1 год назад

New Claude Sonnet 5 performs at GPT 5.5 level 6x cheaper! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics crash demos Prompts: - A car crashes into a brick wall - A wrecking ball destroys a house - A catapult throws a rock at a castle wall Outputs: Sonnet 5: 15,047 tokens, $0.15 Opus 4.8: 23,063 tokens, $0.58 Sonnet 4.6: 25,824 tokens, $0.39 GPT 5.5: 31,152 tokens, $0.94 Sonnet 5 did as well as Opus 4.8 and GPT 5.5 on all three tests. In the wrecking ball test, it beat Opus 4.8. The cable moves smoothly and every hit connects. In the catapult test, it beat GPT 5.5. The rock always lands inside the wall. Sonnet 5 still needs better detail and graphics. But it used fewer tokens than every other model
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New Claude Sonnet 5 performs at GPT 5.5 level 6x cheaper! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics crash demos Prompts: - A car crashes into a brick wall - A wrecking ball destroys a house - A catapult throws a rock at a castle wall Outputs: Sonnet 5: 15,047 tokens, $0.15 Opus 4.8: 23,063 tokens, $0.58 Sonnet 4.6: 25,824 tokens, $0.39 GPT 5.5: 31,152 tokens, $0.94 Sonnet 5 did as well as Opus 4.8 and GPT 5.5 on all three tests. In the wrecking ball test, it beat Opus 4.8. The cable moves smoothly and every hit connects. In the catapult test, it beat GPT 5.5. The rock always lands inside the wall. Sonnet 5 still needs better detail and graphics. But it used fewer tokens than every other model

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We just launched Claude Sonnet 4.5 and “Imagine with Claude”, a 5-day preview that creates dynamic experiences for you in real-time (and the first product I’ve worked on at Anthropic!). It pioneers the concept of “model-as-backend”, using a model to not only generate interfaces on the fly but also power all the functionality behind it – all made possible by our newest model, Claude Sonnet 4.5. Here’s a "choose your own adventure" version of my founder journey, as retold by Imagine with Claude:
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We just launched Claude Sonnet 4.5 and “Imagine with Claude”, a 5-day preview that creates dynamic experiences for you in real-time (and the first product I’ve worked on at Anthropic!). It pioneers the concept of “model-as-backend”, using a model to not only generate interfaces on the fly but also power all the functionality behind it – all made possible by our newest model, Claude Sonnet 4.5. Here’s a "choose your own adventure" version of my founder journey, as retold by Imagine with Claude:

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Build autonomous browsing AI Agents in minutes. It uses vision AI to interact with any interface, just like humans do. Works with Claude 4 Sonnet and Qwen 2.5 VL. 100% Opensource.
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Build autonomous browsing AI Agents in minutes. It uses vision AI to interact with any interface, just like humans do. Works with Claude 4 Sonnet and Qwen 2.5 VL. 100% Opensource.

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Sonnet 5 is here. It's worse than Opus 4.8 on nearly every benchmark... Does that mean it's useless? Absolutely not. Use it with Claude Code Dynamic Workflows! 1. /model set to Sonnet 5 2. /effort set to Ultracode 3. Any complex task will kick off a dynamic workflow This will only become more powerful when Fable is back. You'll use Fable 5 as the superintelligent advisor and Sonnet 5 as the fast and efficient implementer.
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Sonnet 5 is here. It's worse than Opus 4.8 on nearly every benchmark... Does that mean it's useless? Absolutely not. Use it with Claude Code Dynamic Workflows! 1. /model set to Sonnet 5 2. /effort set to Ultracode 3. Any complex task will kick off a dynamic workflow This will only become more powerful when Fable is back. You'll use Fable 5 as the superintelligent advisor and Sonnet 5 as the fast and efficient implementer.

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Introducing Dexter 2.0 Open source. Built for financial research. Like Claude Code, but for stocks. What Dexter does: • plans tasks • runs on its own • validates its work • researches stocks It uses OSS tools like , with a fresh stack of typescript, react, ink, and bun. Fast to build. Easy to use. No coding required. My favorite project of the year.
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Introducing Dexter 2.0 Open source. Built for financial research. Like Claude Code, but for stocks. What Dexter does: • plans tasks • runs on its own • validates its work • researches stocks It uses OSS tools like , with a fresh stack of typescript, react, ink, and bun. Fast to build. Easy to use. No coding required. My favorite project of the year.

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210,156 просмотров • 8 месяцев назад

Everyone is dunking on Sonnet 5 for losing to Opus 4.8 on benchmarks. They're all making the same mistake, judging a teammate by a solo test. Sonnet 5 was never built to win alone. Set the model to Sonnet 5, effort to Ultracode, and any complex task auto-kicks a dynamic workflow where it plans, spawns agents, executes and checks its own work, fast and cheap. When Fable 5 comes back, the setup gets stupid good. Fable 5 decides what to build, Sonnet 5 actually builds it. You stop paying flagship prices to do grunt work.
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Everyone is dunking on Sonnet 5 for losing to Opus 4.8 on benchmarks. They're all making the same mistake, judging a teammate by a solo test. Sonnet 5 was never built to win alone. Set the model to Sonnet 5, effort to Ultracode, and any complex task auto-kicks a dynamic workflow where it plans, spawns agents, executes and checks its own work, fast and cheap. When Fable 5 comes back, the setup gets stupid good. Fable 5 decides what to build, Sonnet 5 actually builds it. You stop paying flagship prices to do grunt work.

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98,313 просмотров • 2 месяцев назад

Claude Fable 5 and GPT-5.6 are cooked already… Sonnet 5 vs Opus 4.8 on another agentic video pipeline. Both generated a storyboard with GPT Images 2.0, then fed it into Seedance 2.0, all through Higgsfield MCP on Claude. Same quality, but each directed Seedance 2.0 completely differently.
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Claude Fable 5 and GPT-5.6 are cooked already… Sonnet 5 vs Opus 4.8 on another agentic video pipeline. Both generated a storyboard with GPT Images 2.0, then fed it into Seedance 2.0, all through Higgsfield MCP on Claude. Same quality, but each directed Seedance 2.0 completely differently.

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i built an app in 2 HOURS with claude 3.7 SONNET idea? take a photo of menu and get macros losing weight while eating out hit a like and i will release it
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i built an app in 2 HOURS with claude 3.7 SONNET idea? take a photo of menu and get macros losing weight while eating out hit a like and i will release it

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Announcing native availability of Anthropic Claude 3.7 Sonnet in Databricks across AWS, Azure and GCP! Customers can now securely access Claude’s advanced reasoning, planning and agentic capabilities directly within Databricks, no setup required. This launch marks the beginning of a strategic partnership between Anthropic and Databricks. We’re excited to see what our customers build and how they leverage domain-specific AI agents!

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I built a tool that runs autoresearch 24/7 in the cloud. It can scale to thousands+ of parallel experiments. Uses Modal (for GPUs) and Cloudflare Workers. Wraps coding tools Codex/Claude. Here's a quick demo ▶

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Most people are still asking: Opus or Sonnet? That may already be the wrong question. Claude is starting to look less like an AI model and more like an AI operating layer. The models are only one part of it. Around them, Anthropic is building the pieces required to move AI from a chat window into real software: → Reasoning models → MCP and tool connectivity → Agent frameworks and SDKs → APIs and managed agents → Memory and context systems → Security and permissions → Evaluation pipelines → Governance and observability → Production deployment infrastructure And that changes what it means to be good at AI engineering. Prompting is becoming table stakes. The harder skill is understanding how an agent gets context, remembers what matters, accesses tools safely, evaluates its own output, survives failures, and operates reliably inside a production system. That is a very different skillset from simply knowing which model tops a benchmark. In 2026, the advantage may not belong to the person who knows the best model. It may belong to the person who understands how the entire AI stack fits together. Claude’s evolution is a good preview of where AI engineering itself is heading.

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Claude Code's effort parameter is something you need to keep in mind before starting any task It's not just about picking the right model anymore (Haiku, Sonnet, Opus). Now you also need to think about which effort level to use before each task. One tip I always go back to: when Opus can't solve a problem, just adding ultrathink makes things click, it's almost magic. We wrote a post at Hedgineer benchmarking each effort level by cost and time Read it here:

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