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Your OpenCode will no longer hallucinate. It now automatically detects when it needs docs, repos, or research papers, then indexes and fetches them via Nia. All retrieved context remains stateful. Introducing the Nozomio Labs opencode plugin. bunx nia-opencode@latest install

Arlan

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116,303 views • 6 months ago •via X (Twitter)

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Here is a demo of the most comprehensive research agent for your code docs, powered by Nozomio Labs. It turns your indexed repos and docs into a dynamic tree that the agent can access on the fly, using SOTA tools to reduce code hallucinations. Now using the latest Anthropic model, Claude Opus 4.5.

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Arlan

28,405 views • 7 months ago

we just killed product onboardings. i did more than 200 collison installations over the summer, going around houses and onboarding people to my product. Paul Graham ended up tweeting about it, and a lot of people recognize me just because of that. today, i decided to automate it. introducing collison installation agent by Nozomio Labs. 1) tell our agent what product you want to be onboarded to 2) we index their docs and packages 3) the agent installs it on your machine bun install nia-onboarding-agent

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Arlan

37,216 views • 5 months ago

QVAC SDK 0.15.0 is live. This release adds multiple prompts batching, brings a native AMD GPU backend to the stack, moves more vision encoders onto mobile GPUs, and adds a second local coding-agent integration. Main highlights: - Prompt batching for the LLM addon. Batch multiple prompts into one job and process them concurrently, with each answer returned the moment its generation finishes. - Native AMD GPU backend. A first-class HIP/ROCm backend in @qvac/vla-ggml, auto-selected over Vulkan with clean fallback when ROCm is absent. - A second local coding agent. OpenClaw joins OpenCode for local, cloud-free agent workflows. AGENTS - OpenCode plugin update (@qvac/opencode-plugin). Aligned with the current SDK, CLI, and AI SDK provider packages. A fresh install runs OpenCode against managed local QVAC models out of the box, from the default qvac/qwen3.5-9b, with no manual qvac serve setup. - OpenClaw plugin (@qvac/openclaw-plugin). A second coding-agent integration alongside OpenCode. A fresh setup installs the plugin, creates a local qvac provider through onboarding, and runs a QVAC model through OpenClaw🦞's local service path. LANGUAGE MODELS - Prompt batching (LLM addon). Batch multiple prompts in one job and run them concurrently, each answer returns the moment its generation finishes, no waiting on the others. - Reasoning-context trimming on hybrid + recurrent models (@qvac/llm-llamacpp). remove_thinking_from_context now works beyond pure-attention models. Same JS API, no throw. VOICE AND SPEECH - Transcription (transcription-parakeet 0.9.0). More robust CPU fallback on GPU failure and a faster Vulkan backend on Pixel 9. - Text-to-speech features (tts-ggml 0.4.0). Adds LavaSR for noise removal and adjustable output frequency up to 48 kHz, plus Japanese via Chatterbox. - Text-to-speech fixes (tts-ggml 0.4.1). CPU fallback on GPU failure, a q8_0 KV crash fix on Metal with Chatterbox. VISION - Qwen3.5 vision encoder on GPU (Android). Image encoder moves onto the phone GPU, with a smarter tile-grid preprocessor and default image-token caps, for flagship Android: Vulkan on Mali (Pixel 9 Pro) and OpenCL on Adreno 830 (Galaxy S25). - Gemma-4 vision encoder on GPU (Android). Vision encoder runs on the phone GPU instead of CPU, same flagship Android targets. PLATFORM AND PERFORMANCE - AMD GPU backend (@qvac/vla-ggml). Native HIP/ROCm backend, auto-selected over Vulkan with clean fallback when ROCm is absent (Linux x64 only). Comes with ~23% faster than Vulkan, ~14% faster than PyTorch-ROCm, parity preserved. Unified code style. A cleaner, more consistent, easier-to-contribute codebase. Let's build. npm install @qvac/sdk

QVAC SDK 0.15.0 is live. This release adds multiple prompts batching, brings a native AMD GPU backend to the stack, moves more vision encoders onto mobile GPUs, and adds a second local coding-agent integration. Main highlights: - Prompt batching for the LLM addon. Batch multiple prompts into one job and process them concurrently, with each answer returned the moment its generation finishes. - Native AMD GPU backend. A first-class HIP/ROCm backend in @qvac/vla-ggml, auto-selected over Vulkan with clean fallback when ROCm is absent. - A second local coding agent. OpenClaw joins OpenCode for local, cloud-free agent workflows. AGENTS - OpenCode plugin update (@qvac/opencode-plugin). Aligned with the current SDK, CLI, and AI SDK provider packages. A fresh install runs OpenCode against managed local QVAC models out of the box, from the default qvac/qwen3.5-9b, with no manual qvac serve setup. - OpenClaw plugin (@qvac/openclaw-plugin). A second coding-agent integration alongside OpenCode. A fresh setup installs the plugin, creates a local qvac provider through onboarding, and runs a QVAC model through OpenClaw🦞's local service path. LANGUAGE MODELS - Prompt batching (LLM addon). Batch multiple prompts in one job and run them concurrently, each answer returns the moment its generation finishes, no waiting on the others. - Reasoning-context trimming on hybrid + recurrent models (@qvac/llm-llamacpp). remove_thinking_from_context now works beyond pure-attention models. Same JS API, no throw. VOICE AND SPEECH - Transcription (transcription-parakeet 0.9.0). More robust CPU fallback on GPU failure and a faster Vulkan backend on Pixel 9. - Text-to-speech features (tts-ggml 0.4.0). Adds LavaSR for noise removal and adjustable output frequency up to 48 kHz, plus Japanese via Chatterbox. - Text-to-speech fixes (tts-ggml 0.4.1). CPU fallback on GPU failure, a q8_0 KV crash fix on Metal with Chatterbox. VISION - Qwen3.5 vision encoder on GPU (Android). Image encoder moves onto the phone GPU, with a smarter tile-grid preprocessor and default image-token caps, for flagship Android: Vulkan on Mali (Pixel 9 Pro) and OpenCL on Adreno 830 (Galaxy S25). - Gemma-4 vision encoder on GPU (Android). Vision encoder runs on the phone GPU instead of CPU, same flagship Android targets. PLATFORM AND PERFORMANCE - AMD GPU backend (@qvac/vla-ggml). Native HIP/ROCm backend, auto-selected over Vulkan with clean fallback when ROCm is absent (Linux x64 only). Comes with ~23% faster than Vulkan, ~14% faster than PyTorch-ROCm, parity preserved. Unified code style. A cleaner, more consistent, easier-to-contribute codebase. Let's build. npm install @qvac/sdk

QVAC

17,700,244 views • 9 days ago

Coding agents shouldn't run on a laptop. That's why I've been building Cave. It's a self-hosted platform for running OpenCode agents in isolated sandboxes on your own server. You give it a GitHub repo, it creates an isolated sandbox, clones the code, sets everything up, and gives you a coding agent. Check in from your phone, run multiple agents side by side. It's not open source yet (it will be), but I'm opening a private beta so you can install it on your own server already. I've been dogfooding it since day one. If you're running a software factory: multiple agents working in parallel across repos, Cave gives you one place to monitor and manage all of it. Now, I'm looking for people who want to give it a spin. DM me, happy to set you up 😊 🚀

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André König

36,095 views • 3 months ago

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Lawrence Chen

49,471 views • 3 months ago

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naïve

14,708 views • 2 months ago

I tested MiniMax M3 so you do not have to. It is free in OpenCode right now and it claims to beat GPT 5.5 on SWE-bench. So I put it on real production code. It broke my push-to-talk. It glitched a game through the floor. It took two tries to render a video and still looked rough. The benchmark said one thing. The real work said another. The one thing it has going for it is price. I ran all of BridgeBench for $4.09. If budget is your only constraint, it is the cheapest Chinese model out there. But cheap is not free when it breaks your codebase. No BridgeMind stamp of approval. Full breakdown in the video.

I tested MiniMax M3 so you do not have to. It is free in OpenCode right now and it claims to beat GPT 5.5 on SWE-bench. So I put it on real production code. It broke my push-to-talk. It glitched a game through the floor. It took two tries to render a video and still looked rough. The benchmark said one thing. The real work said another. The one thing it has going for it is price. I ran all of BridgeBench for $4.09. If budget is your only constraint, it is the cheapest Chinese model out there. But cheap is not free when it breaks your codebase. No BridgeMind stamp of approval. Full breakdown in the video.

BridgeMind

46,304 views • 1 month ago

Your Plan SUCKS! 👀 Inspired by the legend Andrej Karpathy himself, I created a new skill: LLM Council. Create better plans, by committee. Supports: > Codex CLI > Gemini CLI > Claude Code > OpenCode Call the skill with your feature that you'd like to build. It will ask you some clarifying question, and then launch up to four parallel planning agents to create a detailed plan. Once the plans are in, all plans are anonymized and the "The Judge" will critique and choose the best plan *OR* the best parts from all of them. Finally, it will output a final-plan, which you can review and refine. I even created a nice UI for you to review and refine your plans. This Skill has been tested on Linux only, but should work on other platforms. Please report any bugs! Links in the comments.

Your Plan SUCKS! 👀 Inspired by the legend Andrej Karpathy himself, I created a new skill: LLM Council. Create better plans, by committee. Supports: > Codex CLI > Gemini CLI > Claude Code > OpenCode Call the skill with your feature that you'd like to build. It will ask you some clarifying question, and then launch up to four parallel planning agents to create a detailed plan. Once the plans are in, all plans are anonymized and the "The Judge" will critique and choose the best plan OR the best parts from all of them. Finally, it will output a final-plan, which you can review and refine. I even created a nice UI for you to review and refine your plans. This Skill has been tested on Linux only, but should work on other platforms. Please report any bugs! Links in the comments.

am.will

69,010 views • 6 months ago

Everyone keeps asking me how to build a second brain or an LLM wiki. Here is the easiest setup I have found. I took my Wiki Builder skill, installed it into HyperAgent (Hyperagent) as a reusable skill, and asked it to build a research wiki on LLM verification from the latest 2026 papers. Recorded a quick demo. Built with Hyperagent. It planned first, asked a few sharp questions, then did the research: 29 papers curated into 21 files, a research map, a glossary, and clean subfields. Now it is a knowledge base that my other research agents build on. HyperAgent has all the capabilities to allow your agents and skills to compound. That’s a powerful use of AI agents.

Everyone keeps asking me how to build a second brain or an LLM wiki. Here is the easiest setup I have found. I took my Wiki Builder skill, installed it into HyperAgent (Hyperagent) as a reusable skill, and asked it to build a research wiki on LLM verification from the latest 2026 papers. Recorded a quick demo. Built with Hyperagent. It planned first, asked a few sharp questions, then did the research: 29 papers curated into 21 files, a research map, a glossary, and clean subfields. Now it is a knowledge base that my other research agents build on. HyperAgent has all the capabilities to allow your agents and skills to compound. That’s a powerful use of AI agents.

elvis

225,183 views • 8 days ago

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

forloop

226,054 views • 4 months ago

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?

Faheem Ullah

12,175 views • 1 year ago

I built the clipboard I always wanted for working with AI agents. It’s called Bluey and It’s 100% local-first. It lives under your mouse cursor. You can draw on your screen, speak to it, or type what you mean, and Bluey turns all of that into rich context for Claude Code or Codex. I’ve been using it to design websites and debug UI because I can finally say things like “move this here” or “make this section feel cleaner” while pointing at the actual screen. No more writing long explanations. No more manually describing screenshots. No more agents getting lost because they don’t know what “this” or "that" means. You can just point to it, speak or type and it will curate the best possible context for your agents Bluey captures the screenshot, annotation, transcript, app/window context, and the details your agent needs, then sends it directly into your coding session. I am giving it out for free for a while! Im building it with my buddy Omkar Satpute and we would love to hear what you think about it on Discord what context do you wish your agent could understand better?

I built the clipboard I always wanted for working with AI agents. It’s called Bluey and It’s 100% local-first. It lives under your mouse cursor. You can draw on your screen, speak to it, or type what you mean, and Bluey turns all of that into rich context for Claude Code or Codex. I’ve been using it to design websites and debug UI because I can finally say things like “move this here” or “make this section feel cleaner” while pointing at the actual screen. No more writing long explanations. No more manually describing screenshots. No more agents getting lost because they don’t know what “this” or "that" means. You can just point to it, speak or type and it will curate the best possible context for your agents Bluey captures the screenshot, annotation, transcript, app/window context, and the details your agent needs, then sends it directly into your coding session. I am giving it out for free for a while! Im building it with my buddy Omkar Satpute and we would love to hear what you think about it on Discord what context do you wish your agent could understand better?

Milind S

13,342 views • 1 month ago

Today we’re introducing Superhuman Docs, the evolution of Coda (Superhuman Docs) into the best place for teams and AI to work together. I co-founded Coda to reimagine the modern document and enable anyone to make a doc as powerful as an app. Superhuman Docs builds on that mission, and is reimagined for how teams work with AI now. With Superhuman Docs, AI is no longer a solo experience. Docs AI works with you the way a teammate would, with full context of everything your team has built: your data, your briefs, your roadmaps, your connected tools. You can ask it to summarize a sprint, draft a decision record from your meeting notes, or pull a competitor analysis into a new page, and that work stays right where your teammates can pick it up. I’m incredibly proud of the team for bringing Docs to life! There’s so much more we’re launching, including a way to create custom interfaces on top of your data just by describing it. We’re also introducing Superhuman Databases for teams to manage up to 1 million rows, launching Docs MCP to open it up to the AI tools you already use, and debuting a brand new Mac app. We’ve been building toward this moment for a long time, and Docs starts rolling out today. If you’re an existing Coda user, everything you rely on in your docs will remain the same, and if you’re new, now is a great time to jump in.

Shishir

22,007 views • 13 days ago

Reckless Ben explains why he's no longer able to talk about Bricks & Minifigs after being sent court papers "Episode 3 is finally finished..but I can't post it or I will go to jail..I will also immediately lose my lawsuit..and the GoFundMe that we made for Bryan..will go straight to this mystery company" "They sent court papers to my email..judge approved..now that I'm officially served, I cannot even mention this company or I will be in jail..normally I would be like screw the big guy..if I do that then all my friends get screwed with this lawsuit and we lose all the GoFundMe money..so I am no longer allowed to mention this mystery company..my personal opinion is that this is unfair" (Via RecklessBen on YT)

Reckless Ben explains why he's no longer able to talk about Bricks & Minifigs after being sent court papers "Episode 3 is finally finished..but I can't post it or I will go to jail..I will also immediately lose my lawsuit..and the GoFundMe that we made for Bryan..will go straight to this mystery company" "They sent court papers to my email..judge approved..now that I'm officially served, I cannot even mention this company or I will be in jail..normally I would be like screw the big guy..if I do that then all my friends get screwed with this lawsuit and we lose all the GoFundMe money..so I am no longer allowed to mention this mystery company..my personal opinion is that this is unfair" (Via RecklessBen on YT)

yeet

1,157,225 views • 1 month ago

OK THIS SONG!!!! Bro!!! I am cryingggg 😭😭😭 Bro he will!! Even if others will try to control your appearance and tell you to lose weight or tell you how your hair should be, he loves you the same. Then and now, old or young, It's just you😭😭 "I've seen the world, done it all, had my cake now Diamonds, brilliant, and Bel Air now HOT SUMMER NIGHTS, MID-JULY WHEN YOU AND I WERE FOREVER WILD The crazy days, city lights The way you'd play with me like a child WILL YOU STILL LOVE ME WHEN I'M NO LONGER YOUNG AND BEAUTIFUL? Will you still love me when I got nothing but my aching soul? I KNOW YOU WILL, I KNOW YOU WILL, I KNOW THAT YOU WILL Will you still love me when I'm no longer beautiful?"

OK THIS SONG!!!! Bro!!! I am cryingggg 😭😭😭 Bro he will!! Even if others will try to control your appearance and tell you to lose weight or tell you how your hair should be, he loves you the same. Then and now, old or young, It's just you😭😭 "I've seen the world, done it all, had my cake now Diamonds, brilliant, and Bel Air now HOT SUMMER NIGHTS, MID-JULY WHEN YOU AND I WERE FOREVER WILD The crazy days, city lights The way you'd play with me like a child WILL YOU STILL LOVE ME WHEN I'M NO LONGER YOUNG AND BEAUTIFUL? Will you still love me when I got nothing but my aching soul? I KNOW YOU WILL, I KNOW YOU WILL, I KNOW THAT YOU WILL Will you still love me when I'm no longer beautiful?"

GnuTan

24,330 views • 2 months ago

Claude just got a massive upgrade today and I am proud to be part of it. From today on, Claude can generate videos, podcasts or host apps just like Lovable and Replit. We just launched SkillBoss a skill plugin for Claude that enables Claude to: ✅ Generate videos, images, audio, postcast ✅Build apps with logins, DBs, & payments built-in ✅ Send bulk marketing campaigns ✅ Host custom domains SkillBoss credit will cover all of the above with access to VEO, ElevenLabs, Sora API and 50 more. All you need is to go to download and drag to Claude. Then ask Claude to "make a cat video" or "build an app that charges $5"! SkillBoss also works with Codex, Codex, OpenCode and even OpenClaw(yeah I know!) To celebrate the launch, if you comment "skillboss", you will get 15 credit for free.

Claude just got a massive upgrade today and I am proud to be part of it. From today on, Claude can generate videos, podcasts or host apps just like Lovable and Replit. We just launched SkillBoss a skill plugin for Claude that enables Claude to: ✅ Generate videos, images, audio, postcast ✅Build apps with logins, DBs, & payments built-in ✅ Send bulk marketing campaigns ✅ Host custom domains SkillBoss credit will cover all of the above with access to VEO, ElevenLabs, Sora API and 50 more. All you need is to go to download and drag to Claude. Then ask Claude to "make a cat video" or "build an app that charges $5"! SkillBoss also works with Codex, Codex, OpenCode and even OpenClaw(yeah I know!) To celebrate the launch, if you comment "skillboss", you will get 15 credit for free.

Xiaoyin Qu

291,396 views • 5 months ago

Demo alert: What if your company wiki was automatically written and updated by LLMs? Jim Fisher built a demo of this for Granola using all the meetings we've shared internally. Observations so far: it's incredibly up to date (no more stale docs!) and it requires zero effort. Not having a human author feels... different. When it's missing context on something (ie when something happens but we don't talk about it in a meeting) I want to add it manually to the wiki, but then that'll disappear the next time the page gets regenerated... Generally, makes me bullish on workflows where humans feed tons of unstructured data (easiest of which to create is conversations) to an AI, and then AI organizes + structures it on the fly.

Demo alert: What if your company wiki was automatically written and updated by LLMs? Jim Fisher built a demo of this for Granola using all the meetings we've shared internally. Observations so far: it's incredibly up to date (no more stale docs!) and it requires zero effort. Not having a human author feels... different. When it's missing context on something (ie when something happens but we don't talk about it in a meeting) I want to add it manually to the wiki, but then that'll disappear the next time the page gets regenerated... Generally, makes me bullish on workflows where humans feed tons of unstructured data (easiest of which to create is conversations) to an AI, and then AI organizes + structures it on the fly.

Chris Pedregal

15,213 views • 1 year ago

Announcing the latest release from Qodo: Modern engineering runs across hundreds of repos, dozens of teams, and AI that writes code faster than anyone can review it. Today, Qodo releases features built for these teams. - Cross Repo Review: Qodo now maps dependencies across your repos and catches breaking changes before they merge. A change to a shared SDK, API contract, or database schema no longer ships before anyone knows it broke something downstream. - Rules Miner: Qodo analyzes your PR review history, recurring comments, accepted vs. rejected suggestions, and reviewer patterns, and turns them into enforceable rules. The standards that lived in senior engineers' heads are now in the system. - Skill Review Standards: Skills are now a managed entity in Qodo, with visibility, governance controls, and per-skill analytics. The instructions encoding how your team builds software are visible to the people responsible for enforcing them. All of these features are now available in BETA. Sign up for a 14-day free trial.

Announcing the latest release from Qodo: Modern engineering runs across hundreds of repos, dozens of teams, and AI that writes code faster than anyone can review it. Today, Qodo releases features built for these teams. - Cross Repo Review: Qodo now maps dependencies across your repos and catches breaking changes before they merge. A change to a shared SDK, API contract, or database schema no longer ships before anyone knows it broke something downstream. - Rules Miner: Qodo analyzes your PR review history, recurring comments, accepted vs. rejected suggestions, and reviewer patterns, and turns them into enforceable rules. The standards that lived in senior engineers' heads are now in the system. - Skill Review Standards: Skills are now a managed entity in Qodo, with visibility, governance controls, and per-skill analytics. The instructions encoding how your team builds software are visible to the people responsible for enforcing them. All of these features are now available in BETA. Sign up for a 14-day free trial.

Qodo

631,742 views • 29 days ago

QVAC SDK 0.14.0 is live. This release makes the on-device stack faster on mobile, ships the developer-agent path, and takes local text-to-speech to 31 languages. Main highlights: - OpenCode and OpenClaw. The first official OpenCode plugin, plus a maintained OpenClaw compatibility path, both built on managed mode and qvac serve. Point a coding agent at a local model with far less setup and far fewer surprises. - Brain-computer interface transcription, on the SDK. Take recorded neural signal data and decode it into text, fully on-device, no cloud. Stream it in chunks through a simple API. In 0.14 it runs GPU-accelerated on iOS. - Text to Speech in 31 languages with our Supertonic3 upgrade. VOICE AND SPEECH - Supertonic3 multilingual TTS, 5 languages to 31. - Chatterbox and Supertonic now run on the Android GPU, with lower memory use (especially on iOS), quantized s3gen Chatterbox support, and a fix for Chatterbox occasionally emitting random speech. - Whisper transcription now runs on the iOS GPU. Parakeet runs on the Android GPU, with steadier real-time streaming. VISION AND OCR - VLM multi-tile batching: high-resolution Pan and Scan images are encoded in one pass instead of tile by tile, for faster vision throughput. - OCR on ggml (EasyOCR and DocTR) reaches full speed parity with the onnx path, across Metal, OpenCL, and Vulkan. PLATFORM AND RELIABILITY - Dynamic compute backends on Linux: one build picks the right backend at runtime, and opens the door to ROCm and CUDA support without per-backend builds. - Thinking tokens are kept out of the model context, so reasoning no longer fills the KV cache. SDK 0.14.0 is now leaner and faster to start. Let’s build.

QVAC SDK 0.14.0 is live. This release makes the on-device stack faster on mobile, ships the developer-agent path, and takes local text-to-speech to 31 languages. Main highlights: - OpenCode and OpenClaw. The first official OpenCode plugin, plus a maintained OpenClaw compatibility path, both built on managed mode and qvac serve. Point a coding agent at a local model with far less setup and far fewer surprises. - Brain-computer interface transcription, on the SDK. Take recorded neural signal data and decode it into text, fully on-device, no cloud. Stream it in chunks through a simple API. In 0.14 it runs GPU-accelerated on iOS. - Text to Speech in 31 languages with our Supertonic3 upgrade. VOICE AND SPEECH - Supertonic3 multilingual TTS, 5 languages to 31. - Chatterbox and Supertonic now run on the Android GPU, with lower memory use (especially on iOS), quantized s3gen Chatterbox support, and a fix for Chatterbox occasionally emitting random speech. - Whisper transcription now runs on the iOS GPU. Parakeet runs on the Android GPU, with steadier real-time streaming. VISION AND OCR - VLM multi-tile batching: high-resolution Pan and Scan images are encoded in one pass instead of tile by tile, for faster vision throughput. - OCR on ggml (EasyOCR and DocTR) reaches full speed parity with the onnx path, across Metal, OpenCL, and Vulkan. PLATFORM AND RELIABILITY - Dynamic compute backends on Linux: one build picks the right backend at runtime, and opens the door to ROCm and CUDA support without per-backend builds. - Thinking tokens are kept out of the model context, so reasoning no longer fills the KV cache. SDK 0.14.0 is now leaner and faster to start. Let’s build.

QVAC

23,973,950 views • 23 days ago