Partner: An AI That Does Research While You Sleep Based on the article, Partner is an autonomous AI research companion that works independently in the background, conducting tasks like reading papers, analyzing codebases, and generating ideas without user commands. It runs a configurable research cycle every 30 minutes, where each cycle automatically spawns new events to continue the research process. The user simply checks in by asking "what have you been doing?" to receive a report of the AI's discoveries. LLM generates text. Agent executes tasks. Partner does research — on its own. The Problem As a researcher, I have more ideas than time. Papers to read, experiments to run, code to review, and connections to find between projects. No matter how fast I work, the backlog grows. What if I had a research companion that worked independently — reading papers, exploring my codebase, building a knowledge base, and proposing new ideas — while I focused on the hard problems? The Three Layers of AI We've seen two layers of AI tools: Introducing Partner 🤝 Partner is an autonomous research entity . It sits on top of existing agent frameworks like how agents sit on top of LLMs and conducts research independently. The core interaction is beautifully simple: "Hey Partner, what have you been doing?" And it tells you everything it discovered while you were away. How It Works Partner runs in the background, executing a research cycle every 30 minutes configurable . Each cycle: - Picks a task from its queue self-generated or user-injected - Executes it via the agent backend web search, code analysis, etc. - Records findings in its knowledge base - Generates new tasks based on what it learned - Repeats — forever Events: The Heart of Partner An Event is one complete research cycle — like how Agents have Skills, Partner has Events. Each Event follows a structured flow: 📖 Literature → Search and read papers 🔬 Project Scan → Analyze your codebase 💡 Idea Generate → Propose improvements 🧭 Exploration → Try new directions 📝 Knowledge → Record findings 🌱 Spawn → Create new Events Events grow on their own — one Event's findings automatically spawn new Events. The research never stops. Real Results I ran Partner overnight on my bioinformatics research projects. By morning: - 29 research cycles completed autonomously - 34 tasks finished - 48 knowledge entries accumulated - 94 tasks queued for future exploration Key discoveries Partner made on its own: Multi-Agent Support Partner works on top of existing agent frameworks — it doesn't reinvent the wheel. Run partner setup to auto-detect installed agents. Cross-Platform Partner runs on Linux, macOS, Windows, and WSL . On WSL, it can automatically access your Windows files through the WSL Bridge. Getting Started git clone https://github.com/zty522/partner.git cd partner pip install -e . partner setup Then open your agent Hermes, OpenClaw, etc. and say: "Hey Partner, what have you been doing?" What's Next - WeChat/QQ integration — ask Partner via voice message - Community Events — share and install Event templates - Multi-Partner collaboration — multiple Partners working together - More agent backends — Claude Code, Cursor, and more Partner: because research shouldn't wait for you. GitHub: 🤝 Partner "Hey Partner, what have you been doing?" An AI research companion that works independently in the background You don't give it commands. You just check in. The Idea LLM: You ask → It answers → Done Agent: You command → It executes → Waits Partner: It works on its own → You ask "what have you been doing?" → It reports Partner is proactive . It reads papers, explores your projects, builds a knowledge base, and proposes new ideas — all without you telling it to. When you're ready, you just ask: "Hey Partner, what have you been doing?" And it tells you everything it discovered while you were away. Quick Start git clone https://github.com/zty522/partner.git cd partner pip install -e . partner setup The setup wizard detects your installed agents Hermes, Codex, Claude Code , configures a workspace, and registers Partner as a skill. Then just talk naturally: You: …