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Akash ML is now processing about 50 billion tokens a month on Openrouter 👉 openrouter.ai/provider/akash… $AKT

100,000 Stars, #1 Trending Repo this Month This is just the beginning. Stay tuned.

🚨 AWS DevOps Agent is finally here! On March 31, 2026, AWS DevOps Agent became generally available. This is actually a big deal. It can: → Generate CI/CD pipelines → Debug failed deployments → Suggest infrastructure changes → Analyze logs and incidents → Help with Terraform & CloudFormation → Recommend cost optimizations → Explain AWS architecture issues Basically, it’s like having a junior DevOps engineer inside AWS. DevOps is slowly becoming AI-assisted operations. Source: aws.amazon.com/devops-agent/

this guy figured out how to vibe code entirely by voice (hands free) he has a walkie talkie app on his phone that does voice to text and automatically types into whichever Claude Code terminal session he wants. he just talks into his phone and the code starts writing itself on screen AND it dispatches tasks to different sessions. reviews the output. all from his phone. this is what PEAK vibe coding looks like

The fastest growing GitHub repos this week: 1. microsoft/VibeVoice (+11.1K stars) Open-source frontier voice AI. Clone voices, transcribe 60min audio in one pass. 2. bytedance/deer-flow (+9.0K stars) ByteDance's open-source SuperAgent. Researches, codes, creates on its own. 3. NousResearch/hermes-agent (+8.8K stars) The agent that grows with you. Self-evolving memory. 4. mvanhorn/last30days-skill (+8.6K stars) AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket. 5. hacksider/Deep-Live-Cam (+7.3K stars) Real-time face swap with a single image. 6. TauricResearch/TradingAgents (+3.9K stars) Multi-agent LLM trading framework. Because one agent wasn't scary enough. 7. hesreallyhim/awesome-claude-code (+3.2K stars) Curated skills, hooks, and plugins for Claude Code. 8. google-research/timesfm (+2.8K stars) Google's time-series foundation model. Zero-shot forecasting. 9. datalab-to/chandra (+2.4K stars) OCR model for complex tables, forms, and handwriting. 10. SakanaAI/AI-Scientist-v2 (+2.0K stars) Automated scientific discovery via agentic tree search. The theme this week: voice AI and self-evolving agents dominated. Bookmark this. Next week's list will look completely different.

OpenClaw + Gemma 4 rodando local num MacBook Air M4 16GB Free. Open-source. Local. Sem API, sem assinatura, sem mandar seus dados pra ninguem 426 likes em horas. A comunidade ta entendendo que o stack local ja e viavel pra uso real Gemma 4 e o primeiro modelo open-source do Google que compete de verdade com os closed. Agora junta com OpenClaw e voce tem um agente completo rodando no seu laptop O melhor: com PolarQuant comprime ainda mais e cabe em maquinas menores

Open-source Memory for Agents - OpenClaw, Hermes, Claude Code and more @karpathy just validated the exact memory architecture we open-sourced today. Detailed in our new arXiv paper. The idea here is that structured Markdown vaults are the gold standard for agent memory. However, the "compilation" of these vaults is usually too tedious for manual maintenance. It turns out you can just automate the whole curation layer. ByteRover solves this by automating the curation layer: Connecting nodes, links and context graphs while maintaining a human-readable Obsidian format. Token Efficiency: Save you tons of tokens (50-70% on average) because the tiered retrieval only pulls exactly the context the agent needs, instead of dumping massive files into the prompt. Proven Scalability: Benchmarked on Locomo & LongMemEval for production-grade latency and accuracy. Collaboration: Native support to sync and manage knowledge with your teammates and other agents. No vector DBs, zero infra. Just a native "second brain" for your agents that actually works out of the box.

@Cloudtheboi @AlexFinn Yes please

@AlexFinn i built a mobile version of openclaw completly rebuilt for mobile. interested in testing?

If you used a Claude subscription with OpenClaw, read this: Unfortunately all other AI models out there absolutely suck with OpenClaw compared to Opus It's just a fact and anyone denying this is delusional So here is my new recommended OpenClaw setup: Pay for the Opus API and use it as your orchestrator Then use other models as the execution layer If you do this correctly, yes your costs will go up, but not by as much as you think I use my ChatGPT subscription as the coding execution. GPT 5.4 is excellent at coding. When The Opus orchestrator gives a coding task to the ChatGPT subagent, it always performs really well If you are on the Pro plan, you should have enough usage to have ChatGPT be the execution layer for every task. But if youre on the $20 a month plan, youre going to need other subscriptions to handle other tasks GLM 5.1 and Qwen are excellent. I'd get a cheap sub through them and have them handle all other tasks given to them from the orchestrator The best setup tho if you have the hardware is Opus API for orchestrator, ChatGPT for coding, then local Gemma 4 and local Qwen handling everything else. Right now have Gemma running on my DGX Spark and Qwen 3.5 on my Mac Studio. They handle all other execution from my Opus API orchestrator Unfortunately all options above will cost more than the $200 a month subscription. It just is what it is. But if you optimize correctly it wont cost much more, and you'll still get frontier performance. OpenClaw is the most powerful piece of software ever released. $200 a month ($2,400 a year) was a steal for a digital employee. Honestly anything under $50,000 a year is a no brainer if you run a serious business. The situation isn't great but you also need to face reality: Claude Opus 4.6 is the best model for OpenClaw. If you use any other model, your productivity will suffer Business is a battlefield and I refuse to fall behind, so despite me not being happy with the Anthropic decision the setup above is what I'm going with Virtue signaling might get me brownie points on the internet, but it won't increase my productivity

@bensig How would you compare with memorilabs or mem0?

My friend Milla Jovovich and I spent months creating an AI memory system with Claude. It just posted a perfect score on the standard benchmark - beating every product in the space, free or paid. It's called MemPalace, and it works nothing like anything else out there. Instead of sending your data to a background agent in the cloud, it mines your conversations locally and organizes them into a palace - a structured architecture with wings, halls, and rooms that mirrors how human memory actually works. Here is what that gets you: → Your AI knows who you are before you type a single word - family, projects, preferences, loaded in ~120 tokens → Palace architecture organizes memories by domain and type - not a flat list of facts, a navigable structure → Semantic search across months of conversations finds the answer in position 1 or 2 → AAAK compression fits your entire life context into 120 tokens - 30x lossless compression any LLM reads natively → Contradiction detection catches wrong names, wrong pronouns, wrong ages before you ever see them The benchmarks: 100% recall on LongMemEval — first perfect score ever recorded. 500/500 questions. Every question type at 100%. 92.9% on ConvoMem — more than 2x Mem0's score. 100% on LoCoMo — every multi-hop reasoning category, including temporal inference which stumps most systems. No API key. No cloud. No subscription. One dependency. Runs on your machine. Your memories never leave. MIT License. 100% Open Source. github.com/milla-jovovich…

After the Claude Code source code leak, a former PM extracted its multi-agent orchestration system into an open source model agnostic framework. He studied the architecture, focused on the multi-agent orchestration layer (the coordinator that breaks goals into tasks, team system, message bus, task scheduler with dependency resolution), and reimplemented these patterns from scratch as a standalone open source framework without infringing on Anthropic's code. The result is what @JackChen_x calls an "open-multi-agent." Unlike claude-agent-sdk, which spawns a CLI process per agent, this runs entirely in-process and can be deployed anywhere (serverless, Docker, CI/CD) Check it out: github.com/JackChen-me/op…

How to install Google’s local Claude killer in under 90 seconds

Do you even understand what this means? An open source model just released that is: • Outperforms models 20x its size • Can run on a base model Mac Mini • Is AMERICAN 🇺🇸 If you have a base model Mac Mini you can have unlimited super intelligence on your desk. For free. Sonnet 4.5 was released 5 months ago In 5 months that level of intelligence went from frontier to free on your desk And not only that, can run on any basically any computer out there If you have even a remotely modern computer, do the following immediately: 1. Download LM Studio 2. Go to your OpenClaw and ask which of these new Gemma 4 models is best for your hardware 3. Have it walk you through downloading and loading it 4. Build apps with it knowing you are using your own personal, private super intelligence on your desk The people denying this is the future are so beyond lost.

Anthropic tried to kill 8,100 GitHub repos. Then this happened > They filed a DMCA. GitHub nuked the entire network within hours. Developers got notices for forks of Anthropic's OWN public repo - one guy's fork had zero leaked code. > Boris Cherny, head of Claude Code, had to go on X personally: "This was not intentional. Should be better now." > Meanwhile Sigrid Jin - who used 25 billion Claude Code tokens last year - woke up at 4AM and rewrote the entire thing in Python before sunrise. DMCA can't touch a clean-room rewrite. > It hit 50K stars in 2 hours. Fastest repo in GitHub history. > Today claw-code officially launched as an independent project with a formal press release. And the Rust port merged today - what started as a panic rewrite now ships release 0.1.0. > 140K stars. 102K forks. More than Anthropic's own repo. > 512,000 lines are in the wild forever. What started as Anthropic's biggest embarrassment just became their most dangerous competitor. You cannot make this up.

Want to build your own background agents platform like Ramp Inspect or Stripe Minions? Now you can: background-agents.com/landscape

This AI agent just hit 10,000 GitHub stars in under a month. And it gets smarter every time you use it. It's called Hermes. Built by Nous Research. $65M in funding. MIT licensed. Completely free. Here's what makes it different from every other AI agent: → It has permanent memory. Your projects, clients, preferences — all saved forever. → When it solves a hard problem, it writes itself a skill document. Next time, it already knows how. → The skills improve the more you use them. Week 1 it knows nothing. Month 6 it knows your entire business. → There's an open marketplace called agentskills.io where people share skills. Microsoft and GitHub already adopted the format. → It works across Telegram, Discord, Slack, WhatsApp, Signal, and email. Context carries across all of them. → Send a voice note on your walk. It transcribes it and does the work before you get home. → Runs on a $5/month server. Or free locally. → One command to migrate from OpenClaw. Brings your settings, memory, and API keys. ChatGPT Pro costs $200/month. It still forgets your name when you close the tab. Hermes costs less than a cup of coffee. And it never forgets anything.

Announcing companies.sh - the open standard for Agent Companies Import and run entire companies with a single command Just run `npx companies.sh add <repo/company>` More 👇

🚨 OpenAI charges $0.006/minute. Google charges $0.024. AWS charges $0.024. Someone just open sourced a tool that does it for $0. And it's faster than all of them. It's called Insanely Fast Whisper. And that's not hype. That's the benchmark. 150 minutes of audio. 98 seconds to transcribe. On your own machine. No API key. No cloud. No per-minute billing. Here's what the numbers look like: → Whisper Large v3 + Flash Attention 2: 150 min of audio in 98 seconds → Distil Whisper + Flash Attention 2: 150 min in 78 seconds → Standard Whisper without optimization: 31 minutes for the same job → That's a 19x speedup. Same model. Same accuracy. Just faster. Here's what it does: → One command to transcribe any audio file or URL → Speaker diarization — knows WHO said WHAT → Transcription AND translation to other languages → Runs on NVIDIA GPUs and Mac (Apple Silicon) → Flash Attention 2 for maximum speed → Clean JSON output with timestamps → Works with every Whisper model variant Here's the wildest part: Otter.ai charges $100/year. Rev charges $1.50/minute. Descript charges $24/month. Enterprise transcription contracts cost thousands. Podcasters, journalists, researchers, lawyers, content creators — anyone still paying for transcription is lighting money on fire. 8.8K GitHub stars. 633 forks. MIT License. 100% Open Source. (Link in the comments)

Today we're announcing the Vibecode CLI Your OpenClaw (or any agent) can build and deploy up to 20 apps in parallel in a single prompt. Your agent will communicate with Vibecode to build your app(s). Frontend, Backend, Database, Deployments, APIs. Works with OpenClaw, Claude Code, Perplexity Computer, Manus, and any agent with access to a terminal. Just add this to your prompt: "Please use vibecode . dev CLI to build these apps"

Fastest growing GitHub projects this week 🤯 1. agency-agents (+23.2K) AI agency in one repo 2. superpowers (+19.2K) framework for AI agents 3. MiroFish (+17.6K) swarm intelligence engine 4. OpenViking (+10.2K) context DB for agents 5. browser (+9.9K) headless browser for AI 6. impeccable (+6.4K) design system for AI UI 7. page-agent (+6.2K) control websites with AI 8. context-hub (+5.2K) Andrew Ng’s agent layer 9. deepagents (+4.9K) multi-agent framework 10. BitNet (+4.8K) 1-bit LLMs by Microsoft AI agents took over GitHub 😭 x.com/DAIEvolutionHu…