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🚀 New on ModelScope: MiniMax M2.1 is open-source! ✅ SOTA in 8+ languages (Rust, Go, Java, C++, TS, Kotlin, Obj-C, JS) ✅ Full-stack Web & mobile dev: Android/iOS, 3D visuals, vibe coding that actually ships ✅ Smarter, faster, 30% fewer tokens — with lightning mode (M2.1-lightning) for high-TPS workflows...

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ModelScope

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16,939 просмотров • 8 месяцев назад •via X (Twitter)

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Still relying on AI tools that can’t turn your ideas into real, working apps? Most can write code snippets but fall apart when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I simply asked it: “Build a responsive calculator app with a clean UI in light/dark mode.” Within minutes, it built the entire app with a beautiful UI, logic, light/dark mode, animations, and full responsiveness. Literally no setup. No debugging headache. Just vibe coding. Here’s why Replit stands out 👇 ✅ Build in Plain English: Just describe what you want and Replit turns it into a production-ready app. ✅ All-in-One Platform: Code, AI help, hosting, auth, and database, everything you need, already built in. ✅ Vibe Code Anywhere: Build on the go with the Replit mobile app for iOS & Android. ✅ Connected Ecosystem: Integrate with tools you already use like Notion, Slack, Google Drive, Dropbox, and more. ✅ Design to Live App: Import directly from Figma and bring your ideas to life in minutes. No micromanaging. No chaos. Just you, your idea, and Replit doing the heavy lifting. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my referral link. → #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore
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Still relying on AI tools that can’t turn your ideas into real, working apps? Most can write code snippets but fall apart when it’s time to actually build something complete. That’s where Replit ⠕ changes everything. I simply asked it: “Build a responsive calculator app with a clean UI in light/dark mode.” Within minutes, it built the entire app with a beautiful UI, logic, light/dark mode, animations, and full responsiveness. Literally no setup. No debugging headache. Just vibe coding. Here’s why Replit stands out 👇 ✅ Build in Plain English: Just describe what you want and Replit turns it into a production-ready app. ✅ All-in-One Platform: Code, AI help, hosting, auth, and database, everything you need, already built in. ✅ Vibe Code Anywhere: Build on the go with the Replit mobile app for iOS & Android. ✅ Connected Ecosystem: Integrate with tools you already use like Notion, Slack, Google Drive, Dropbox, and more. ✅ Design to Live App: Import directly from Figma and bring your ideas to life in minutes. No micromanaging. No chaos. Just you, your idea, and Replit doing the heavy lifting. 👉 Try it now: 🎁 Get $10 credit when you purchase Replit Core via my referral link. → #Replit #VibeCoding #AIApps #NoCode #BuildWithReplit #AItools #ReplitCore

Manish Kumar Shah

52,314 просмотров • 10 месяцев назад

While your team is just getting started vibe coding prototypes, the team at Stripe is vibe coding a full vibe coding platform. Owen Williams ⚡ is a design manager at Stripe who built Protodash - an internal AI prototyping tool that lets designers and PMs spin up real, clickable prototypes in minutes. In this ep he walks through: - why generic AI tools produce "blurple slop" that doesn't match your design system - how he built a full prototyping studio on top of dev boxes with cursor + cc - why more PMs than designers now use Protodash - the design review mode that lets teams ship feedback direct in the app Plus, we talk about getting to the ultimate dream: demos, not memos. ty to our sponsors! 🧠 CESAR - Intelligent automation built for AI 💻 Cursor - The best way to code with AI Full episode on yt:
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While your team is just getting started vibe coding prototypes, the team at Stripe is vibe coding a full vibe coding platform. Owen Williams ⚡ is a design manager at Stripe who built Protodash - an internal AI prototyping tool that lets designers and PMs spin up real, clickable prototypes in minutes. In this ep he walks through: - why generic AI tools produce "blurple slop" that doesn't match your design system - how he built a full prototyping studio on top of dev boxes with cursor + cc - why more PMs than designers now use Protodash - the design review mode that lets teams ship feedback direct in the app Plus, we talk about getting to the ultimate dream: demos, not memos. ty to our sponsors! 🧠 CESAR - Intelligent automation built for AI 💻 Cursor - The best way to code with AI Full episode on yt:

claire vo 🖤

92,220 просмотров • 4 месяцев назад

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☕ Launch Your Own Café App – No Code Needed! Cafés, coffee roasters, and baristas—it’s time to serve customers online with your own custom app! With our dApp Builder, you can create a cross-platform café app in minutes—no coding required. ✅ Sell Coffee, Beverages, Snacks & More – Directly to Customers ✅ Cross-Platform by Default – Android, iOS, Web, Windows, Mac, Linux ✅ Decentralized & Secure – Built on #ION for direct, fee-free transactions No more high commission fees—own your ordering system, offer subscriptions, and let customers grab their coffee anytime. ☕ The future of coffee ordering is here. Ready to build?

Ice Open Network

57,629 просмотров • 1 год назад

Today, we’re introducing new tools and model updates to help you build, deploy, and scale Voice AI applications.🎙️ 🆕 Speech Understanding: Turn transcripts into actionable data with speaker identification, custom formatting & translation 🆕 LLM Gateway: One API for your voice-to-intelligence pipeline, with GPT, Claude, Gemini & more 🆕 Voice AI Guardrails: End-to-end protection for safe, compliant content Model Upgrades: ✅ 99 languages with auto code-switching ✅ 64% fewer speaker counting errors ✅ 57% better accuracy on critical terms with 1,000-word context Real results: 🔥 Calabrio: 80% boost in customer satisfaction, 22% revenue increase 🔥 Siro: "10/10 customers say 'wow, that insight was crisp'" Build & scale Voice AI in minutes! Try it in our Playground or check the docs. 🚀
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Today, we’re introducing new tools and model updates to help you build, deploy, and scale Voice AI applications.🎙️ 🆕 Speech Understanding: Turn transcripts into actionable data with speaker identification, custom formatting & translation 🆕 LLM Gateway: One API for your voice-to-intelligence pipeline, with GPT, Claude, Gemini & more 🆕 Voice AI Guardrails: End-to-end protection for safe, compliant content Model Upgrades: ✅ 99 languages with auto code-switching ✅ 64% fewer speaker counting errors ✅ 57% better accuracy on critical terms with 1,000-word context Real results: 🔥 Calabrio: 80% boost in customer satisfaction, 22% revenue increase 🔥 Siro: "10/10 customers say 'wow, that insight was crisp'" Build & scale Voice AI in minutes! Try it in our Playground or check the docs. 🚀

AssemblyAI

18,157 просмотров • 10 месяцев назад

Introducing Shipper: the first autonomous AI business maker. Successful startups spend $65k/mo in salaries… before their first paying customers comes in - We built Shipper to change that forever this. Shipper can: ✅ Research how other startups made it big ✅ Build any kind of app: mobile, web, website, extension, bot etc ✅ Code, design, monetize, launch ✅ Do email marketing for you ✅ Self-maintain and build out new features ...and so much more Every project has its own AI co-founder, scheduled prompts, autonomous building mode and native connectors. No API tokens. No confusion on Cursor. No credits wasted on errors. Shipper replaces teams of 30+ employees and acts just like VC-backed startups... For the price of $25/month. To celebrate the launch, we're giving away free credits randomly. Repost and comment "SHIPPER" to join - we'll let Siri pick the winners.
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Introducing Shipper: the first autonomous AI business maker. Successful startups spend $65k/mo in salaries… before their first paying customers comes in - We built Shipper to change that forever this. Shipper can: ✅ Research how other startups made it big ✅ Build any kind of app: mobile, web, website, extension, bot etc ✅ Code, design, monetize, launch ✅ Do email marketing for you ✅ Self-maintain and build out new features ...and so much more Every project has its own AI co-founder, scheduled prompts, autonomous building mode and native connectors. No API tokens. No confusion on Cursor. No credits wasted on errors. Shipper replaces teams of 30+ employees and acts just like VC-backed startups... For the price of $25/month. To celebrate the launch, we're giving away free credits randomly. Repost and comment "SHIPPER" to join - we'll let Siri pick the winners.

David Ch

28,131 просмотров • 5 месяцев назад

Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.
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Alibaba just released a coding model that hits 82 percent on SWE-Bench Verified. That is the highest score ever published for an open-source model. The weights are free. The license is Apache 2.0. You can run it today. The model is Qwen 4 Coder 32B. Here is what 82 percent on SWE-Bench Verified actually means. SWE-Bench Verified tests whether an AI can autonomously resolve real bugs pulled from real production GitHub repositories. Not synthetic exercises. Real open-source projects that real teams depend on. A model gets a bug report, reads the code, writes a fix, and either passes the test suite or it does not. At 82 percent, Qwen 4 Coder 32B resolves 82 out of every 100 real production bugs it is given. Without a human guiding it. On code it has never seen before. For comparison: Qwen 4 Coder 32B: 82 percent SWE-Bench Verified. Open source. Apache 2.0. Claude Fable 5: 80.3 percent SWE-Bench Pro. $10 input / $50 output per million tokens. Currently suspended. GPT-5.6 Sol: Competitive on Terminal-Bench. $5 input / $30 output per million tokens. An open-weight model that you can download and run for free just beat both of them on the benchmark designed to measure real software engineering capability. Here is the architecture. Qwen 4 Coder 32B is a 32 billion parameter dense model. Not a Mixture-of-Experts. Every parameter is active on every request. This matters for inference: a dense 32B model runs on 22 gigabytes of VRAM, which fits on a single high-end consumer GPU or a MacBook Pro with 64GB of unified memory. The smaller variant, Qwen 4 Coder 4B, runs at approximately 135 tokens per second on an M5 Max and fits inside 8 gigabytes of RAM. For a model with usable coding capability, that is a new bar for what fits in a single laptop. The training methodology continued Alibaba's approach of reinforcement learning on verifiable coding tasks. The model gets rewarded when its code passes tests. It gets penalized when it fails. Over millions of training steps, the model learns to write code that actually runs rather than code that looks plausible. License: Apache 2.0. Full commercial use. No attribution requirement. No revenue threshold. No monthly active user ceiling. Weights: Hugging Face, available today. Runs on: vLLM, Ollama, SGLang, and any standard GGUF-compatible inference engine. Qwen 4 32B also runs at approximately 135 tokens per second on an M5 Max chip, setting a new bar for what a sub-8GB model can do on Apple Silicon. The open-source coding model just beat the best closed-source model in the world on the benchmark designed to test whether AI can actually do software engineering. The weights are free. The subscription is optional. Source: Autom8Labs AI Insight July 2026, State of Open Source LLMs June 2026, Kunal Ganglani blog June 2026.

Harman

41,278 просмотров • 2 месяцев назад

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.
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🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

AI Frontliner

60,126 просмотров • 6 месяцев назад

Make your CLI 10x more powerful with custom subagents! Mistral Vibe is an open-source coding agent that runs in your terminal. Most terminal agents give you one assistant that does everything. With Vibe, you can build custom subagents for targeted tasks like deploy scripts, PR reviews, and test generation, then invoke them on demand. Here's how it works: Each subagent runs independently and handles its job without cluttering your main workflow. You might have one for PR reviews, another for testing, and another for deployment. The agent also has full access to your codebase. It scans your project structure and Git status automatically, so it understands context across multiple files, not just the one you're editing. Key capabilities: • Web search and fetching - query and fetch content from the web mid-session for documentation, or API references. • Multi-choice clarifications - when your instruction is ambiguous, Vibe prompts with options instead of guessing. You pick the right path before it acts. • Full skills support - slash commands for preconfigured workflows, custom subagents for specialized tasks, and extensibility through the Agent Skills standard. Vibe works in your terminal or connects to VS Code, JetBrains, and Zed through the Agent Client Protocol. Mistral Vibe is available through Le Chat Pro and Team plans. It's 100% open source Link to Mistral Vibe in the comments!
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Make your CLI 10x more powerful with custom subagents! Mistral Vibe is an open-source coding agent that runs in your terminal. Most terminal agents give you one assistant that does everything. With Vibe, you can build custom subagents for targeted tasks like deploy scripts, PR reviews, and test generation, then invoke them on demand. Here's how it works: Each subagent runs independently and handles its job without cluttering your main workflow. You might have one for PR reviews, another for testing, and another for deployment. The agent also has full access to your codebase. It scans your project structure and Git status automatically, so it understands context across multiple files, not just the one you're editing. Key capabilities: • Web search and fetching - query and fetch content from the web mid-session for documentation, or API references. • Multi-choice clarifications - when your instruction is ambiguous, Vibe prompts with options instead of guessing. You pick the right path before it acts. • Full skills support - slash commands for preconfigured workflows, custom subagents for specialized tasks, and extensibility through the Agent Skills standard. Vibe works in your terminal or connects to VS Code, JetBrains, and Zed through the Agent Client Protocol. Mistral Vibe is available through Le Chat Pro and Team plans. It's 100% open source Link to Mistral Vibe in the comments!

Sumanth

10,483 просмотров • 5 месяцев назад

🔥 Pi Network Has Officially Entered Beast Mode – Global Payment Giants Now Support It! While others doubted, we built. While the world watched, Pi Network quietly integrated with the biggest financial platforms on Earth. And now… we’re ready. 💪🌎 💥 The Walls Are Down. Pi Is Borderless. The Open Mainnet is live, the infrastructure is in place, and now the final pieces are falling into place — Pi Network is supported by a massive alliance of global payment powerhouses, including: 🛡️ Exchange Titans & Fiat Gateways: •✅ Binance P2P •✅ Binance Connect •✅ Transak •✅ Sardine •✅ Topper •✅ UTORG •✅ Paybis •✅ Onmeta •✅ Onramp Money •✅ •✅ TransFi •✅ DFX •✅ Alchemy Pay •✅ Banxa •✅ BTC Direct •✅ Coinify •✅ MoonPay •✅ Fonbnk •✅ GateConnect •✅ Unlimit •✅ Guardarian •✅ Koywe •✅ LocalRamp •✅ Yellow Card 💳 World-Class Fintechs Now Support Pi: •✅ Stripe •✅ Skrill Crypto •✅ Revolut 🌐 This Is Bigger Than Just Crypto Stripe and Skrill aren’t just crypto services — they’re global payment kings. And now they’re helping Pi bridge traditional finance with the new digital economy. Revolut is a top fintech unicorn, and it’s already supporting Pi. Binance is the biggest crypto exchange in the world — and it’s ready. Let that sink in. 🔥 🚀 Why This Changes Everything •🌍 Anyone can access Pi, anywhere in the world •🏦 Buy and sell Pi directly with bank cards, local fiat, Apple Pay, and more •💼 Businesses can now prepare to integrate Pi into payments •🧠 Investors now see the foundation for real-world use and massive growth This is what true mass adoption looks like — infrastructure before hype. Utility before listing. Power before price. 🔮 The World’s Not Ready, But We Are. While other coins chased listings, Pi Network built alliances. While others pumped and dumped, Pi built its own economy. And now? The rocket is fully fueled. We’re not waiting for the future — we’re building it. “You don’t have to be first. You just have to be the one who finishes the race prepared. And Pi Network is ready to dominate.” 📢 Pioneers, Stand Tall Your patience, your faith, your mining, your contribution — it’s all paying off. With 40+ global financial platforms now supporting Pi, we’ve gone from an idea… to an unstoppable force. 🎯 Pi Network is not just another crypto project. 🚀 Pi is the people’s currency — and now the world is opening its gates to it. 📣 Share this. Shout it. Post it. Let every Pioneer know — Pi is ready. Let every skeptic watch — we told you so. Let every investor understand — the game has changed. Pi is no longer coming. Pi is here. 🔥 And the world is about to feel it. Pi Network Nicolas Kokkalis Chengdiao Fan ✅✅✅✅🚀🚀🚀🚀🚀🚀🚀🚀
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🔥 Pi Network Has Officially Entered Beast Mode – Global Payment Giants Now Support It! While others doubted, we built. While the world watched, Pi Network quietly integrated with the biggest financial platforms on Earth. And now… we’re ready. 💪🌎 💥 The Walls Are Down. Pi Is Borderless. The Open Mainnet is live, the infrastructure is in place, and now the final pieces are falling into place — Pi Network is supported by a massive alliance of global payment powerhouses, including: 🛡️ Exchange Titans & Fiat Gateways: •✅ Binance P2P •✅ Binance Connect •✅ Transak •✅ Sardine •✅ Topper •✅ UTORG •✅ Paybis •✅ Onmeta •✅ Onramp Money •✅ •✅ TransFi •✅ DFX •✅ Alchemy Pay •✅ Banxa •✅ BTC Direct •✅ Coinify •✅ MoonPay •✅ Fonbnk •✅ GateConnect •✅ Unlimit •✅ Guardarian •✅ Koywe •✅ LocalRamp •✅ Yellow Card 💳 World-Class Fintechs Now Support Pi: •✅ Stripe •✅ Skrill Crypto •✅ Revolut 🌐 This Is Bigger Than Just Crypto Stripe and Skrill aren’t just crypto services — they’re global payment kings. And now they’re helping Pi bridge traditional finance with the new digital economy. Revolut is a top fintech unicorn, and it’s already supporting Pi. Binance is the biggest crypto exchange in the world — and it’s ready. Let that sink in. 🔥 🚀 Why This Changes Everything •🌍 Anyone can access Pi, anywhere in the world •🏦 Buy and sell Pi directly with bank cards, local fiat, Apple Pay, and more •💼 Businesses can now prepare to integrate Pi into payments •🧠 Investors now see the foundation for real-world use and massive growth This is what true mass adoption looks like — infrastructure before hype. Utility before listing. Power before price. 🔮 The World’s Not Ready, But We Are. While other coins chased listings, Pi Network built alliances. While others pumped and dumped, Pi built its own economy. And now? The rocket is fully fueled. We’re not waiting for the future — we’re building it. “You don’t have to be first. You just have to be the one who finishes the race prepared. And Pi Network is ready to dominate.” 📢 Pioneers, Stand Tall Your patience, your faith, your mining, your contribution — it’s all paying off. With 40+ global financial platforms now supporting Pi, we’ve gone from an idea… to an unstoppable force. 🎯 Pi Network is not just another crypto project. 🚀 Pi is the people’s currency — and now the world is opening its gates to it. 📣 Share this. Shout it. Post it. Let every Pioneer know — Pi is ready. Let every skeptic watch — we told you so. Let every investor understand — the game has changed. Pi is no longer coming. Pi is here. 🔥 And the world is about to feel it. Pi Network Nicolas Kokkalis Chengdiao Fan ✅✅✅✅🚀🚀🚀🚀🚀🚀🚀🚀

Mr Spock 𝛑

42,315 просмотров • 1 год назад

🚀New Amazon Q Developer agent for software development is available to customers: This agent is based on a new agent architecture that has exciting results coming from the SWE-bench scores (on the full and verified benchmarks) representing AI models’ ability to resolve real-world coding problems. Interesting aspect of Q Agent is that with these newest updates, Q drove nearly 50% more successful coding tasks completed. What makes Q Dev Agent remarkable? The agent architecture is not just about using the best LLMs (which we do), but also giving the agent the ability to constantly explore multiple paths to find the best way to resolve a particular problem (and back tracking when it has reached dead end like a developer would do). Needless to say, we are just getting started on the developer agent and we are constantly pushing to advance our AI capabilities while maintaining quality, security, privacy, and reliability to keep Amazon Q Developer an innovative and trusted option available to our customers using agents for software development. We highlighted the results of our first SWE-bench submission of Amazon Q Developer back in June blog post; with these updates, our new agent resolves 51% more coding tasks than its previous iteration on the SWE-bench verified dataset, and 43% more on the full dataset. That’s the difference a few months make, and I can’t wait to share what our teams will deliver at re:Invent this December. Here's a quick demo showcasing our new Agent in action:
1:28

🚀New Amazon Q Developer agent for software development is available to customers: This agent is based on a new agent architecture that has exciting results coming from the SWE-bench scores (on the full and verified benchmarks) representing AI models’ ability to resolve real-world coding problems. Interesting aspect of Q Agent is that with these newest updates, Q drove nearly 50% more successful coding tasks completed. What makes Q Dev Agent remarkable? The agent architecture is not just about using the best LLMs (which we do), but also giving the agent the ability to constantly explore multiple paths to find the best way to resolve a particular problem (and back tracking when it has reached dead end like a developer would do). Needless to say, we are just getting started on the developer agent and we are constantly pushing to advance our AI capabilities while maintaining quality, security, privacy, and reliability to keep Amazon Q Developer an innovative and trusted option available to our customers using agents for software development. We highlighted the results of our first SWE-bench submission of Amazon Q Developer back in June blog post; with these updates, our new agent resolves 51% more coding tasks than its previous iteration on the SWE-bench verified dataset, and 43% more on the full dataset. That’s the difference a few months make, and I can’t wait to share what our teams will deliver at re:Invent this December. Here's a quick demo showcasing our new Agent in action:

Swami Sivasubramanian

28,946 просмотров • 2 лет назад

🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.
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🚨 ALIBABA JUST OPEN-SOURCED THE MOST POWERFUL MODEL IN THE WORLD - Qwen3.5 plus And it changes the AI race forever. This is not another “bigger model” release. This is a complete architectural reset. 397B parameters → only 17B active at inference, Qwen3.5 plus delivers performance on par with GPT-5.2 and Gemini-3-Pro. A new Hybrid Sparse MoE + Linear Attention architecture + Multi-Token Prediction = near-instant long-context responses and massive speed gains. Built as a true native multimodal model, it doesn’t just chat it builds. With a single prompt: “Use the React framework to create a visually impressive Mapbox demo featuring locations in Beijing and Shanghai” it generates a live interactive 3D map UI, structured components, real layouts, and production-ready frontend logic. This is real agentic, multimodal coding not a static code block. MMLU-Pro: 87.8 GPQA: 88.4 IFBench: 76.5 ⚡ up to 8× faster inference And it’s fully open-sourced under Apache-2.0. No locked APIs. No restricted tiers. 201 languages supported bringing frontier AI to developers, startups, and researchers worldwide. The race is no longer about the biggest model. It’s about the most usable intelligence. Open source just entered the top tier.

RAVI KUMAR SAHU

380,123 просмотров • 6 месяцев назад

The wait is over 365 days ago, we launched our closed Alpha Since then, we have: ✅ Developed a custom ReAct agent with improved prompting, skill handling, and Nillion data storage ✅ Revealed some of our partnerships (big ones have yet to be announced 👀) ✅ Migrated to a new Uniswap Base (V3) pool for better price stability ✅ Allowed users to create their own Characters ✅ Added new Skills (so many more to go live) ✅ Overhauled the agent UI/UX ✅ Integrated with Telegram We are not building one single agent that does XYZ. We are building: ➡️ An Agent Framework ➡️ Secure Credential Storage ➡️ Enterprise-grade Access Control ➡️ Request tracking, and a lot of other stuff.. that allows thousands of people to create AI agents under minutes. The greatest leverage is not in using tools It’s in creating the tools that create tools The closed Alpha was our proof of concept What comes next is our proof of vision Full platform launch on February 25th 🌐
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The wait is over 365 days ago, we launched our closed Alpha Since then, we have: ✅ Developed a custom ReAct agent with improved prompting, skill handling, and Nillion data storage ✅ Revealed some of our partnerships (big ones have yet to be announced 👀) ✅ Migrated to a new Uniswap Base (V3) pool for better price stability ✅ Allowed users to create their own Characters ✅ Added new Skills (so many more to go live) ✅ Overhauled the agent UI/UX ✅ Integrated with Telegram We are not building one single agent that does XYZ. We are building: ➡️ An Agent Framework ➡️ Secure Credential Storage ➡️ Enterprise-grade Access Control ➡️ Request tracking, and a lot of other stuff.. that allows thousands of people to create AI agents under minutes. The greatest leverage is not in using tools It’s in creating the tools that create tools The closed Alpha was our proof of concept What comes next is our proof of vision Full platform launch on February 25th 🌐

Skillful AI

25,999 просмотров • 1 год назад

SonarQube has been catching my bugs and security issues for years. The only friction was having to leave Cursor or Windsurf to view the results. Their new MCP Server fixes that by bringing verification directly into the coding environment 🔥 This is actually perfect timing 🧵 ↓ Because we write more code than ever thanks to AI, yet productivity still doesn’t keep up. Google’s 2025 DORA Report shows the tension: → AI usage +90% → Bugs +9% → Review time +91% → PR size +154% (report here: The problem isn’t generating code. It’s verifying it quickly and reliably. And this is what SonarQube's new MCP Server brings instantly: - Live scanning → trigger SonarQube checks inside Cursor, Windsurf, Claude Code… basically any MCP-compatible IDE - Immediate surfacing → security, reliability, and maintainability issues in seconds - Smooth UI handoff → jump to the dashboard only when you need the full picture - AI-native workflow → Sonar’s long-standing rule engine integrated into your daily loop Why it’s great: • Removes constant tab-switching • Faster write → check → fix cycles • Lets the IDE handle speed while SonarQube handles structure • Feels like code quality finally meets AI-native development Setup is super simple: → Enable SonarQube's MCP Server in Cursor → Add your SonarQube instance → Open your repo → Run the scan directly inside the IDE I then pointed it to a JS component I’m building in Streamlit (psst, it’s called Streamlit ChartJS ;)) → Immediate results: security flags, reliability concerns, maintainability smells, and dependency risks ✅ Then I prompted: "Show me the full breakdown." → Cursor opens the SonarQube UI with rule details, severities, fix guidance, and project-wide quality signals! Exactly on point.
0:37

SonarQube has been catching my bugs and security issues for years. The only friction was having to leave Cursor or Windsurf to view the results. Their new MCP Server fixes that by bringing verification directly into the coding environment 🔥 This is actually perfect timing 🧵 ↓ Because we write more code than ever thanks to AI, yet productivity still doesn’t keep up. Google’s 2025 DORA Report shows the tension: → AI usage +90% → Bugs +9% → Review time +91% → PR size +154% (report here: The problem isn’t generating code. It’s verifying it quickly and reliably. And this is what SonarQube's new MCP Server brings instantly: - Live scanning → trigger SonarQube checks inside Cursor, Windsurf, Claude Code… basically any MCP-compatible IDE - Immediate surfacing → security, reliability, and maintainability issues in seconds - Smooth UI handoff → jump to the dashboard only when you need the full picture - AI-native workflow → Sonar’s long-standing rule engine integrated into your daily loop Why it’s great: • Removes constant tab-switching • Faster write → check → fix cycles • Lets the IDE handle speed while SonarQube handles structure • Feels like code quality finally meets AI-native development Setup is super simple: → Enable SonarQube's MCP Server in Cursor → Add your SonarQube instance → Open your repo → Run the scan directly inside the IDE I then pointed it to a JS component I’m building in Streamlit (psst, it’s called Streamlit ChartJS ;)) → Immediate results: security flags, reliability concerns, maintainability smells, and dependency risks ✅ Then I prompted: "Show me the full breakdown." → Cursor opens the SonarQube UI with rule details, severities, fix guidance, and project-wide quality signals! Exactly on point.

Charly Wargnier

22,702 просмотров • 9 месяцев назад