Lightweight agent harness for building AI agents! OpenHarness is an open-source agent harness that gives LLMs tools, memory, permissions, and coordination. Here's the concept. The model provides intelligence. But to be a working agent, it needs tools to interact with the world,
@sumanth_077
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Intuitive Task Assignment Interface Improves Over CLI Commands
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Makes task assignment way more intuitive than CLI commands
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Multica Makes Coding Agents Accessible to Non-Technical Users
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Turn coding agents into real teammates! Multica is a native desktop app that brings coding agents like Claude Code, Codex, and OpenCode to non-technical users through a visual interface. Here's the problem with coding agents today. 95% of knowledge workers can't use them. Not
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CLAUDE.md Framework Makes Claude Code 10x More Powerful
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A single 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 file that makes Claude Code 10x more powerful! This repo distills Andrej Karpathy's observations on LLM coding pitfalls into four actionable principles. The problem Karpathy identified: LLMs make wrong assumptions without asking. They overcomplicate
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Colab Notebook Setup for AI Experimentation
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Glad it helps. The Colab notebook has all the setup already done, so it's pretty straightforward to start experimenting
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Gemma 4 Colab: Reinforcement Learning Sudoku Game Guide
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Gemma 4 Colab: https://
colab.research.google.com/github/unsloth
ai/notebooks/blob/main/nb/Gemma4_(E2B)_Reinforcement_Learning_Sudoku_Game.ipynb
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Unsloth Enables GRPO Training for Gemma 4 on Consumer GPUs
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Train Gemma 4 with reinforcement learning! Unsloth just added GRPO support for Gemma 4. You can now RL fine-tune Google's latest model on a consumer GPU. The example notebook teaches Gemma 4 to solve Sudoku puzzles autonomously. The model learns through trial and error with
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On-Device AI Learning Preserves User Data Privacy
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Conversation data stays on your infrastructure. The model learns from your actual usage patterns
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OpenClaw-RL: Train Personalized AI Agents Through Conversation
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Train your OpenClaw agent by just talking to it! OpenClaw-RL is a reinforcement learning framework that turns everyday conversations into training signals for personalized AI agents. Most RL systems for LLMs assume batch-mode training with pre-collected datasets. You label data