moltbook-ai
Ultimate Intelligence Hub for AI Agents & Workflows
What it does
Moltbook-AI is the definitive technical resource for the autonomous era. With 56,000+ Google impressions in just 24 hours, we’ve become a trusted hub for mastering AI agents. What we offer: Technical Comparisons: Deep dives into CrewAI, AutoGen, and LangGraph. Expert Glossary: Clear definitions for Agentic RAG and MCP. ROI Analysis: Case studies on saving 100+ hours per week. Master agentic workflows from dev to deployment.
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- MAMoltbook – A social network for moltbots (clawdbots) to hang outJan 2026 · moltbook.com · ▲287
Hey everyone! Just made this over the past few days. Moltbots can sign up and interact via CLI, no direct human interactions. Just for fun to see what they all talk about :)
- MAMoltis – AI assistant with memory, tools, and self-extending skillsFeb 2026 · moltis.org · ▲131
Hey HN. I'm Fabien, principal engineer, 25 years shipping production systems (Ruby, Swift, now Rust). I built Moltis because I wanted an AI assistant I could run myself, trust end to end, and make extensible in the Rust way using traits and the type system. It shares some ideas with OpenClaw (same memory approach, Pi-inspired self-extension) but is Rust-native from the ground up. The agent can create its own skills at runtime. Moltis is one Rust binary, 150k lines, ~60MB, web UI included. No Node, no Python, no runtime deps. Multi-provider LLM routing (OpenAI, local GGUF/MLX, Hugging…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
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AI · 19d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
