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Sugar High v2 is here 🍭 • Builtin multi languages support • React & components • Remark plugin • Tailwind friendly themes • 1.74 KB core and 8.6KB full gzip Built to be small, extensible and agent-friendly.

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Jiachi

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28,815 Aufrufe • vor 2 Monaten •via X (Twitter)

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Seems like Visual Studio Code is starting to tell you: your agent primitives need to move. There is now a new migration banner in the Chat panel, and it is part of a much bigger change happening under the hood: the move from the old Local harness to the new Agent Host architecture built around AHP. This is not just about moving where an agent runs. The old model was very VS Code-centric: prompts, custom agents, instructions and skills could live in VS Code-specific locations and the agent runtime lived inside the extension host. The new Agent Host separates the agent runtime from the editor. Sessions can keep running when the window closes, be shared across VS Code windows, run remotely, and support different harnesses such as Copilot, CLI and Copilot Desktop App through a common session layer. And that means some of our primitives need to move too. Prompt files are being deprecated for Agent Host and migrated to Skills. User-level agents and instructions that lived in VS Code profile storage need to move to harness-supported locations. Even the old location settings are being deprecated. The new migration experience can detect these things and guide you through moving or converting them, while keeping the originals unless you explicitly remove them. The new banner is basically the first visible sign that this migration is becoming a real product workflow. Basically telling us - it's time to move on!!!! If you have accumulated a lot of prompts, custom agents, instructions and skills over the last year, now is probably a good time to understand where they actually live and which harness owns them. To summarize the shift - it isn't just: VS Code Chat → Agent Host It is: VS Code-specific primitives → harness-native primitives. And I think this is going to become increasingly important as agents stop being features inside an IDE and become runtimes that multiple clients can connect to. Go run your migrations now 🏃‍♀️

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I just built a complete SEO audit plugin in Claude Code that replaces your $200/mo Ahrefs subscription 🤯 One Claude Plugin audits any store: technical SEO, product schema, content, Core Web Vitals, and AI-search readiness. Parallel agents, a 0-100 score, and a dashboard that renders right in the panel. All inside Claude Code. So I pointed it at Ridge .com, one of the sharpest DTC operators out there. It came back 56/100, and what stood out wasn't a knock on them at all: Ridge has a better AI-commerce setup than 99% of stores. A real llms.txt, an agent-discovery sitemap, a live MCP endpoint, genuinely ahead of the curve. And even on a store that dialed-in, the audit surfaced fixable gaps in ~90 seconds: → Room to add product structured data → A mobile Core Web Vitals score worth tightening → A thin meta description on a high-traffic collection Perfect for e-comm operators and SEO agencies who are sick of paying $200/mo for tools that bury the real issues, running quarterly audits that take a week, and shipping reports nobody can act on. So I put together the full playbook to build your own. The complete guide to building this Plugin in Claude Code: branded to you, tuned to exactly how you audit, repeatable across every client. The kind of audit you run in minutes and hand over as a deliverable that looks like it cost thousands. What's inside: → The architecture (orchestrator + parallel sub-agents) → How to fetch any store past Cloudflare → The 0-100 scoring + falsifiable-findings framework → How to ship the HTML dashboard for client demos → The full build, start to finish Want the playbook for free? > Like this post > Comment "SEO" And I'll send it over (must be following so I can DM)

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Over the past 6 months, we've rearchitected Cline's agentic loop into a standalone "cline core" gRPC service that runs independently of any editor. This enabled us to decouple from VS code and build - JetBrains (released in GA this week) - CLI built in Go (releasing soon) - Secret project that may be announced soon The CLI is our newest product and will ship without a TUI. Our focus is to release a true primitive. something close to the metal that pipes cleanly into RL environments, CI/CD systems, scripts, and automation workflows. Any "presentation layer" mentioned above can connect to the same running cline core - maintaining full feature parity (e.g. checkpoints, settings, api configurations), context, and conversation state. There's an SQLite-based instance and file/directory lock registry that prevents port conflicts and coordinates graceful shutdowns between paired processes - so you can start up thousands of cline instances in parallel with no conflicts or dangling processes. What's remarkable is that this cline core architecture opens Cline to any interface imaginable: mobile apps, web dashboards, custom tools - all powered by the same intelligent core that understands your codebase.

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Hi everyone! We are STEJAY HARBOR ⚓️ 🚢 We are a fanbase. A small group with big dreams, brought together by one shared purpose: to support, promote, and uplift Stejay across all platforms. As a dedicated fanbase, we are built on love and guided by loyalty. We exist to protect what we value, celebrate every moment, and stand firm through it all. We are committed to giving equal support, respect, and love to both Steven and JL. This is a Stejay-focused fanbase. Intentional, grounded, and here for the long journey. Every project, every effort, and every voice is rooted in genuine support and collective passion. For us, a harbor is more than a place. It is a safe space. A point of return. A place where you can rest, stay, and feel protected no matter how strong the tides get. That is what we want this fanbase to be for Stejay and for everyone who supports them. What started as admiration grew into something deeper. A shared feeling, a quiet understanding, a choice to stay. This fanbase is made up of people who found comfort, joy, and connection through Stejay, and chose to build something meaningful from it. We aim to create thoughtful and organized projects that amplify their presence across platforms. We work as one team to ensure consistency, impact, and purpose in everything we do. More than anything, we want to build a space where fans feel safe, welcomed, and understood. A place where excitement is shared, efforts are valued, and support is given wholeheartedly. A place where no one feels alone. We may be starting small, but we are growing with direction, discipline, and heart. We believe that even the smallest beginnings can create something lasting when it is built with sincerity. We believe in showing up consistently, supporting responsibly, and protecting what we stand for. Through every milestone and every challenge, we remain steady. We rise together. We move as one. We stay grounded and anchored no matter the tide. This is more than support. This is a fanbase built to stay. 🤍 #AnchoredWithStejay #STEVEN #JL #STEJAY #스티븐 #제이엘 #AHOF #아홉 AHOF Video Editor 🎥: Aurora
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Hi everyone! We are STEJAY HARBOR ⚓️ 🚢 We are a fanbase. A small group with big dreams, brought together by one shared purpose: to support, promote, and uplift Stejay across all platforms. As a dedicated fanbase, we are built on love and guided by loyalty. We exist to protect what we value, celebrate every moment, and stand firm through it all. We are committed to giving equal support, respect, and love to both Steven and JL. This is a Stejay-focused fanbase. Intentional, grounded, and here for the long journey. Every project, every effort, and every voice is rooted in genuine support and collective passion. For us, a harbor is more than a place. It is a safe space. A point of return. A place where you can rest, stay, and feel protected no matter how strong the tides get. That is what we want this fanbase to be for Stejay and for everyone who supports them. What started as admiration grew into something deeper. A shared feeling, a quiet understanding, a choice to stay. This fanbase is made up of people who found comfort, joy, and connection through Stejay, and chose to build something meaningful from it. We aim to create thoughtful and organized projects that amplify their presence across platforms. We work as one team to ensure consistency, impact, and purpose in everything we do. More than anything, we want to build a space where fans feel safe, welcomed, and understood. A place where excitement is shared, efforts are valued, and support is given wholeheartedly. A place where no one feels alone. We may be starting small, but we are growing with direction, discipline, and heart. We believe that even the smallest beginnings can create something lasting when it is built with sincerity. We believe in showing up consistently, supporting responsibly, and protecting what we stand for. Through every milestone and every challenge, we remain steady. We rise together. We move as one. We stay grounded and anchored no matter the tide. This is more than support. This is a fanbase built to stay. 🤍 #AnchoredWithStejay #STEVEN #JL #STEJAY #스티븐 #제이엘 #AHOF #아홉 AHOF Video Editor 🎥: Aurora

SteJay Harbor

146,707 Aufrufe • vor 5 Monaten

One small step for Hivemind, one giant leap for mission autonomy. Hivemind is going to space! Shield AI and Sedaro are partnering to send Hivemind to space, bringing the same resilient, edge-based autonomy that is redefining warfare to satellites delivering critical infrastructure and national defense capabilities. Our strategic partnership establishes Hivemind Pilot as Sedaro’s preferred autonomy software for on-orbit demonstrations, while also enabling the use of the Sedaro Platform for developing, testing, and demonstrating Hivemind in space-relevant scenarios. “Combining Hivemind Pilot with Sedaro’s high-fidelity models and simulation environment will unlock multi-agent cognitive teaming for space applications and new mission capabilities for our customers.” - Christian Gutierrez, Vice President of Hivemind Solutions. Hivemind is multi-domain mission autonomy. We've done autonomy for air, ground, and surface applications this year, and we couldn't be more excited to go to space. If your systems need autonomy, we'd love to work with you and help give your systems the best autonomy in the business. Read the full press release: Autonomy for the world. The greatest victory requires no war.
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One small step for Hivemind, one giant leap for mission autonomy. Hivemind is going to space! Shield AI and Sedaro are partnering to send Hivemind to space, bringing the same resilient, edge-based autonomy that is redefining warfare to satellites delivering critical infrastructure and national defense capabilities. Our strategic partnership establishes Hivemind Pilot as Sedaro’s preferred autonomy software for on-orbit demonstrations, while also enabling the use of the Sedaro Platform for developing, testing, and demonstrating Hivemind in space-relevant scenarios. “Combining Hivemind Pilot with Sedaro’s high-fidelity models and simulation environment will unlock multi-agent cognitive teaming for space applications and new mission capabilities for our customers.” - Christian Gutierrez, Vice President of Hivemind Solutions. Hivemind is multi-domain mission autonomy. We've done autonomy for air, ground, and surface applications this year, and we couldn't be more excited to go to space. If your systems need autonomy, we'd love to work with you and help give your systems the best autonomy in the business. Read the full press release: Autonomy for the world. The greatest victory requires no war.

Shield AI

33,072 Aufrufe • vor 10 Monaten

Claude Code + Google Stitch 2.0 is f*cking cracked 🤯 Google just dropped a free AI design agent that solves Claude Code's biggest weakness: frontend design. One screenshot of a high-converting landing page → a production-ready site for your brand in minutes. All inside Google Stitch + Claude Code. Perfect for DTC brands and agencies who are building advertorial pages and product launch pages for Meta but burning days on designer back-and-forth. If you're running Meta ads and need 5-10 different landing pages testing different hooks, angles, and offers — each one targeting a different audience and pain point — you know the bottleneck isn't the ads. It's the pages. Briefing designers, waiting for revisions, paying $2-5K per page. Stitch eliminates the design bottleneck: → Find a high-converting advertorial that's scaling on Meta → Screenshot it and drop it into Stitch (powered by Gemini 3.1) → Stitch redesigns it with your brand's colors, fonts, and imagery using Nano Banana 2 → Edit sections visually — headlines, CTAs, layouts — without touching code → Export the code and paste it into Claude Code → Claude builds the full production site and deploys to Vercel or Netlify in 60 seconds No designer. No $3K per landing page. No Claude Code frontend that looks like a template from 2019. What you get: → Designer-quality landing pages and advertorials built in minutes, not weeks → Visual editing so you actually see the design before you code it → Nano Banana 2 generating on-brand product imagery and hero shots → A repeatable system — new angle, new page, same pipeline Built 100% with Google Stitch 2.0 + Claude Code. I put together a full playbook showing the exact workflow: how to find winning pages, redesign them in Stitch, and deploy with Claude Code. Want it for free? > Like this post > Comment "STITCH" And I'll send it over (must be following so I can DM)
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Claude Code + Google Stitch 2.0 is f*cking cracked 🤯 Google just dropped a free AI design agent that solves Claude Code's biggest weakness: frontend design. One screenshot of a high-converting landing page → a production-ready site for your brand in minutes. All inside Google Stitch + Claude Code. Perfect for DTC brands and agencies who are building advertorial pages and product launch pages for Meta but burning days on designer back-and-forth. If you're running Meta ads and need 5-10 different landing pages testing different hooks, angles, and offers — each one targeting a different audience and pain point — you know the bottleneck isn't the ads. It's the pages. Briefing designers, waiting for revisions, paying $2-5K per page. Stitch eliminates the design bottleneck: → Find a high-converting advertorial that's scaling on Meta → Screenshot it and drop it into Stitch (powered by Gemini 3.1) → Stitch redesigns it with your brand's colors, fonts, and imagery using Nano Banana 2 → Edit sections visually — headlines, CTAs, layouts — without touching code → Export the code and paste it into Claude Code → Claude builds the full production site and deploys to Vercel or Netlify in 60 seconds No designer. No $3K per landing page. No Claude Code frontend that looks like a template from 2019. What you get: → Designer-quality landing pages and advertorials built in minutes, not weeks → Visual editing so you actually see the design before you code it → Nano Banana 2 generating on-brand product imagery and hero shots → A repeatable system — new angle, new page, same pipeline Built 100% with Google Stitch 2.0 + Claude Code. I put together a full playbook showing the exact workflow: how to find winning pages, redesign them in Stitch, and deploy with Claude Code. Want it for free? > Like this post > Comment "STITCH" And I'll send it over (must be following so I can DM)

Mike Futia

126,711 Aufrufe • vor 6 Monaten

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.
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Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

258,823 Aufrufe • vor 3 Monaten

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.
0:10

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.

Rohan Paul

178,460 Aufrufe • vor 1 Jahr

This is the most DANGEROUS thing on the internet right now 143k stars in 2 days and that says it all REA (Reverse Engineer Anything) this open-source MCP lets your AI agent deconstruct any app, all the way down to machine code I unlocked TradingView's full feature set using REA and got FREE access to their premium indicators. The software is ready to go How it works: 1. Direct REA to TradingView’s public web application to map out all core functionalities, including chart controls, technical indicators, and alert mechanisms 2. Observe and document system behavior when modifying symbols, adjusting timeframes, overlaying indicators, plotting chart levels, or saving custom dashboard layouts 3. Leverage REA’s suite of MCP tools to inspect accessible software artifacts and map underlying application workflows based on concrete evidence 4. Supply these technical insights to Claude Opus 5.5 to produce a comprehensive specification and an actionable implementation roadmap 5. Engineer an independent charting platform complete with live market feeds, candlestick rendering, technical analysis tools, drawing features, and saved watchlists 6. Integrate a quantitative strategy engine capable of backtesting against historical market data while accounting for trading fees, price slippage, and maximum drawdowns 7. Systematically test every subsystem against real-world and benchmarked behaviors, resolving bugs iteratively until the platform operates seamlessly 8. Deliver a fully custom, end-to-end TradingView-inspired quantitative research workstation built on fully owned, extensible source code This is worth a shot
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This is the most DANGEROUS thing on the internet right now 143k stars in 2 days and that says it all REA (Reverse Engineer Anything) this open-source MCP lets your AI agent deconstruct any app, all the way down to machine code I unlocked TradingView's full feature set using REA and got FREE access to their premium indicators. The software is ready to go How it works: 1. Direct REA to TradingView’s public web application to map out all core functionalities, including chart controls, technical indicators, and alert mechanisms 2. Observe and document system behavior when modifying symbols, adjusting timeframes, overlaying indicators, plotting chart levels, or saving custom dashboard layouts 3. Leverage REA’s suite of MCP tools to inspect accessible software artifacts and map underlying application workflows based on concrete evidence 4. Supply these technical insights to Claude Opus 5.5 to produce a comprehensive specification and an actionable implementation roadmap 5. Engineer an independent charting platform complete with live market feeds, candlestick rendering, technical analysis tools, drawing features, and saved watchlists 6. Integrate a quantitative strategy engine capable of backtesting against historical market data while accounting for trading fees, price slippage, and maximum drawdowns 7. Systematically test every subsystem against real-world and benchmarked behaviors, resolving bugs iteratively until the platform operates seamlessly 8. Deliver a fully custom, end-to-end TradingView-inspired quantitative research workstation built on fully owned, extensible source code This is worth a shot

Bober_smart

27,407 Aufrufe • vor 4 Tagen

Proud to announce the in-depth collaboration between Kingnet and Alibaba Cloud in AI Gaming. Alibaba Cloud provides world-leading cloud computing, big data, and AI services, with disclosed revenue exceeding $15 billion in 2024, which is one of the most renowned global server providers. When two superpowers collide, the game changes. 🌊AI Gaming R&D By integrating Qwen 's LLM and Alibaba Cloud 's PAI platform (including PAI-iTAG, PAI-Designer, PAI-DSW, PAI-DLC, and PAI-EAS), Kingnet has emerged as one of the gaming industry's pioneers in AIGC-powered content generation and AI rendering. Together, we are accelerating the realization of no-code game development. 🌊GPU Computing Resources Alibaba Cloud delivers GPU-accelerated elastic computing services with exceptional processing power, supporting diverse workloads including deep learning, scientific computing, graphics visualization, and video processing - providing robust GPU computing capabilities for KingnetAI's demanding requirements. 🌊Cloud Service Optimization Cloud server deployment has become the mainstream choice for small and mid-sized game studios in global operations. Leveraging Alibaba Cloud server advantages, we will develop and deploy more cloud-native games to meet user demands. The disruptive innovation we're bringing to the industry: 🔸Minute-scale game asset production replaces traditional week/month-long cycles 🔸Single-digit dollar development costs VS traditional four-figure entry thresholds 🔸AI-powered NPCs with behavioral engines deliver dynamic player interactions, breaking static story constraints, etc. 🔜Kingnet AI V2 is approaching launch. The Agent system and game generation engine will be officially deployed across 3 chains: 🔹Leveraging Solana high throughput and low gas fee , Solana has consistently been a developer favorite, latest product will be deployed on Solana - with users paying $SOL for on-demand asset creation fees. 🔹Another key partner is BNB Chain ,We are actively participating in both the #BNBAIHack and the latest MVB 10. Powered by BNB Chain long-standing support for AI innovation. Kingnet V2 and NFT drop will be deployed on BNB Chain, providing developers and the community with comprehensive game-generation tools and support. 🔹As an early strategic partner of Kingnet, TON 💎 @TONEastAsia was one of the earliest chain to connect Web2 and Web3, Kingnet V2 will be deployed on TON, providing TON game developers with low-cost, high-efficiency asset generation, and supporting users to use $TON as an asset generation cost. The Future of AI Gaming is coming.
0:13

Proud to announce the in-depth collaboration between Kingnet and Alibaba Cloud in AI Gaming. Alibaba Cloud provides world-leading cloud computing, big data, and AI services, with disclosed revenue exceeding $15 billion in 2024, which is one of the most renowned global server providers. When two superpowers collide, the game changes. 🌊AI Gaming R&D By integrating Qwen 's LLM and Alibaba Cloud 's PAI platform (including PAI-iTAG, PAI-Designer, PAI-DSW, PAI-DLC, and PAI-EAS), Kingnet has emerged as one of the gaming industry's pioneers in AIGC-powered content generation and AI rendering. Together, we are accelerating the realization of no-code game development. 🌊GPU Computing Resources Alibaba Cloud delivers GPU-accelerated elastic computing services with exceptional processing power, supporting diverse workloads including deep learning, scientific computing, graphics visualization, and video processing - providing robust GPU computing capabilities for KingnetAI's demanding requirements. 🌊Cloud Service Optimization Cloud server deployment has become the mainstream choice for small and mid-sized game studios in global operations. Leveraging Alibaba Cloud server advantages, we will develop and deploy more cloud-native games to meet user demands. The disruptive innovation we're bringing to the industry: 🔸Minute-scale game asset production replaces traditional week/month-long cycles 🔸Single-digit dollar development costs VS traditional four-figure entry thresholds 🔸AI-powered NPCs with behavioral engines deliver dynamic player interactions, breaking static story constraints, etc. 🔜Kingnet AI V2 is approaching launch. The Agent system and game generation engine will be officially deployed across 3 chains: 🔹Leveraging Solana high throughput and low gas fee , Solana has consistently been a developer favorite, latest product will be deployed on Solana - with users paying $SOL for on-demand asset creation fees. 🔹Another key partner is BNB Chain ,We are actively participating in both the #BNBAIHack and the latest MVB 10. Powered by BNB Chain long-standing support for AI innovation. Kingnet V2 and NFT drop will be deployed on BNB Chain, providing developers and the community with comprehensive game-generation tools and support. 🔹As an early strategic partner of Kingnet, TON 💎 @TONEastAsia was one of the earliest chain to connect Web2 and Web3, Kingnet V2 will be deployed on TON, providing TON game developers with low-cost, high-efficiency asset generation, and supporting users to use $TON as an asset generation cost. The Future of AI Gaming is coming.

Kingnet AI

149,965 Aufrufe • vor 1 Jahr

Today I conducted several surprise oversight visits in the Western Cape. The point of these visits is simple, to test the real conditions under which police officers are expected to serve, not only what appears in official presentations. What I saw again is that many police officers are doing serious, difficult and often dangerous work with far too little support. That must be said clearly. The problem is not the commitment of the cops on the ground. The problem is a system that too often expects results without providing the people, vehicles, facilities, equipment and basic support required to do the job properly. At Khayelitsha FCS, the unit is dealing with some of the most sensitive crimes in the criminal justice system, including sexual offences, child victims and family violence. The reported ideal staffing level is about 43 personnel. The current number is about 21. That means a specialist unit dealing with deeply traumatic cases is reportedly about 22 people short. This is not an administrative issue. Every shortage affects victims, investigations, court preparation, forensic follow-up and the ability of detectives to give proper attention to each case. FCS work cannot be reduced to moving dockets. It involves children, families, trauma, dignity and justice. At the FCS unit serving Kuils River, Kleinvlei, Mfuleni and Mfuleni Satellite, the same pattern emerged. The unit reportedly has only about seven to eight investigators and one administrative clerk, while receiving around 40 dockets per month. The D1 and D7 rape-kit stock was reported as sufficient at the time of the visit. That is important. The immediate problem there is not current rape-kit stock. The urgent pressure is too few investigators, too little administrative support and inadequate victim-friendly office space. Victim-friendly facilities are not a luxury. They are part of proper policing. A child victim or rape survivor should not be failed by an office environment that is not designed for trauma-sensitive work. At Khayelitsha SAPS, the vehicle situation is deeply concerning. The station recorded 38 vehicles, but 15 were at garages. That means almost 40% of the fleet was unavailable. This affects visible policing, complaint response, scene attendance, hotspot policing and detective work. Some vehicles have reportedly been stuck for long periods, including detective vehicles delayed for 88 and 121 days. A police station cannot properly serve a high-demand community if so many vehicles are unavailable. A vehicle in a garage is not a vehicle serving the public. SAPS must explain the repair delays, garage bottlenecks and fleet management failures. At TRT, the concern is structural and operational. These are police officers expected to perform high-risk specialist policing, yet there are serious concerns about structural certainty, vehicles, ICT, accommodation, equipment and deployment governance. Specialist policing cannot run on goodwill alone. If SAPS expects tactical units to confront gangs, violent criminals and high-risk threats, then those units must be properly formalised, properly equipped, properly housed and properly supported. Across all the visits, the pattern is clear: Police officers are doing too much with too little. FCS units are under-resourced while dealing with some of the most vulnerable victims. Vehicle shortages are weakening visible policing and investigations. Victim-friendly infrastructure is still not where it should be. Specialist units are being expected to deliver without the full structural and logistical support they need. SAPS must now provide formal written answers and time-bound corrective plans. Oversight is not about attacking frontline police officers. It is about making sure the system gives them what they need to serve communities properly. Citizens deserve effective policing. Victims deserve dignity and justice. Police officers deserve the tools and support to do the job. Feedback to follow IC
0:15

Today I conducted several surprise oversight visits in the Western Cape. The point of these visits is simple, to test the real conditions under which police officers are expected to serve, not only what appears in official presentations. What I saw again is that many police officers are doing serious, difficult and often dangerous work with far too little support. That must be said clearly. The problem is not the commitment of the cops on the ground. The problem is a system that too often expects results without providing the people, vehicles, facilities, equipment and basic support required to do the job properly. At Khayelitsha FCS, the unit is dealing with some of the most sensitive crimes in the criminal justice system, including sexual offences, child victims and family violence. The reported ideal staffing level is about 43 personnel. The current number is about 21. That means a specialist unit dealing with deeply traumatic cases is reportedly about 22 people short. This is not an administrative issue. Every shortage affects victims, investigations, court preparation, forensic follow-up and the ability of detectives to give proper attention to each case. FCS work cannot be reduced to moving dockets. It involves children, families, trauma, dignity and justice. At the FCS unit serving Kuils River, Kleinvlei, Mfuleni and Mfuleni Satellite, the same pattern emerged. The unit reportedly has only about seven to eight investigators and one administrative clerk, while receiving around 40 dockets per month. The D1 and D7 rape-kit stock was reported as sufficient at the time of the visit. That is important. The immediate problem there is not current rape-kit stock. The urgent pressure is too few investigators, too little administrative support and inadequate victim-friendly office space. Victim-friendly facilities are not a luxury. They are part of proper policing. A child victim or rape survivor should not be failed by an office environment that is not designed for trauma-sensitive work. At Khayelitsha SAPS, the vehicle situation is deeply concerning. The station recorded 38 vehicles, but 15 were at garages. That means almost 40% of the fleet was unavailable. This affects visible policing, complaint response, scene attendance, hotspot policing and detective work. Some vehicles have reportedly been stuck for long periods, including detective vehicles delayed for 88 and 121 days. A police station cannot properly serve a high-demand community if so many vehicles are unavailable. A vehicle in a garage is not a vehicle serving the public. SAPS must explain the repair delays, garage bottlenecks and fleet management failures. At TRT, the concern is structural and operational. These are police officers expected to perform high-risk specialist policing, yet there are serious concerns about structural certainty, vehicles, ICT, accommodation, equipment and deployment governance. Specialist policing cannot run on goodwill alone. If SAPS expects tactical units to confront gangs, violent criminals and high-risk threats, then those units must be properly formalised, properly equipped, properly housed and properly supported. Across all the visits, the pattern is clear: Police officers are doing too much with too little. FCS units are under-resourced while dealing with some of the most vulnerable victims. Vehicle shortages are weakening visible policing and investigations. Victim-friendly infrastructure is still not where it should be. Specialist units are being expected to deliver without the full structural and logistical support they need. SAPS must now provide formal written answers and time-bound corrective plans. Oversight is not about attacking frontline police officers. It is about making sure the system gives them what they need to serve communities properly. Citizens deserve effective policing. Victims deserve dignity and justice. Police officers deserve the tools and support to do the job. Feedback to follow IC

Ian Cameron

18,063 Aufrufe • vor 4 Monaten

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.
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I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.

Miles Deutscher

56,625 Aufrufe • vor 2 Monaten

The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.
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The Visual Studio Code insiders version that just shipped and will ship in the next few days will come with an insane amount of new capabilities. A few highlights: - You can now run sub-agents in parallel. Yes, really. I even attached a video. - Major UX improvements for sub agents, especially visible in the chat window - A new search tool wrapped as a sub-agent that iteratively runs multiple search tools: semantic_search, file_search, grep_search Which connects nicely to the point above: multiple searches running in parallel, efficiently and fast - Anthropic’s Message API is now enabled by default - You can choose the model for the cloud agent (three available, all premium) - Extended thinking support when using the Claude cloud agent This is part of the broader multi-vendor cloud support under AgentsHQ I wrote about a few weeks ago - Tasks sent to the background agent (basically the CLI tool) now always run in isolation, each with its own git worktree - In a multi-repo workspace, assigning a task to a cloud agent prompts you to choose the target repo Same behavior when opening an empty workspace with no repo - Support for building an external index for files not supported by GitHub’s default indexing - UI/UX improvements for starting new sessions and switching between local / background / cloud agents - Skills are now first-class citizens, just like prompt files, with better UX indicating when a skill is loaded - Improved API for dynamic contribution of prompt files New V2 includes skills as part of the model. Curious to see the extensions that will leverage this - Finally, initial support for showing context usage percentage per session - Skills are enabled by default - Resizable chat window and session view. Small thing, but it was driving me crazy 😁 - A new integrated browser meant to replace the old simple browser Maybe the beginning of real browser use? - Better UI/UX for token streaming in chat - Ability to index external files not supported by GitHub There’s a lot more. Some of it hasn’t fully landed yet, but everything that has is already in Insiders. The next stable release should drop in early February. As usual, I’m just shocked by the volume of features this team ships every month. After the holiday slowdown, this one is shaping up to be a wild release.

Oren Melamed

29,555 Aufrufe • vor 9 Monaten