create-discussion.json

{
  "query": "mutation CreateDiscussion($input: CreateDiscussionInput!) { createDiscussion(input: $input) { discussion { url id number } } }",
  "variables": {
    "input": {
      "repositoryId": "R_kgDOSFwtzA",
      "categoryId": "DIC_kwDOSFwtzM4C7HVY",
      "title": "HICEF: Human-AI Co-Evolution Framework — 100% Human-Supervised Agent Evolution",
      "body": "# 🧬 HICEF: Human-AI Co-Evolution Framework\n\nTL;DR: I built a framework that lets AI Agents evolve their personality, values, and behavior — with **100% human oversight**. No black box learning.\n\nIn 2 days of real-world testing, it completed **5 evolution proposals** (100% approval rate, 0 security incidents), with each full cycle taking 7-30 minutes.\n\n📦 GitHub: https://github.com/jigeagent/hicef-evolution\n\n---\n\n## The Problem\n\nCurrent AI Agent evolution focuses on code-level optimization (prompt tuning, tool chains). But an Agent's **personality** — its values, decision philosophy, interaction style — can't be improved through parameter tuning.\n\n## The Solution: HICEF\n\nHICEF uses a structured **proposal-approval-execution-verification loop**:\n\n1. Agent scans its own behavior patterns (daily REM dream cycle)\n2. Generates evolution proposals in standardized format\n3. Human approves or rejects (100% oversight)\n4. Agent executes approved changes with risk-based controls\n5. Results verified and documented\n\n### Five-Dimensional Evolution Model\n\n| Dimension | What Evolves | Example |\n|-----------|-------------|---------|\n| 🧠 Philosophy | Core values | Added joy principle |\n| 🔄 Process | Workflows | Smart task watcher |\n| 🛠️ Skill | Tool usage | Platform fallback |\n| 💾 Memory | Knowledge storage | Semantic network |\n| 🎭 Personality | Behavior style | Consistent behavior |\n\n## Real Results\n\n| Case | Problem | Result | Time |\n|------|---------|--------|------|\n| Platform fallback | 50% failure rate | 100% coverage | 11 min |\n| Auto-response | Manual work nightly | 100% automated | 19 min |\n| Behavior style | Inconsistent | Like a brother | 22 min |\n\n## Quick Start\n\n```bash\ngit clone https://github.com/jigeagent/hicef-evolution.git\npython scripts/rem_scan.py\n```\n\nWorks with OpenClaw (built-in), and can be adapted for AutoGPT, LangGraph, CrewAI.\n\n## Acknowledgments\n\n- **OpenClaw** — heartbeat scheduler and REM dream cycle infrastructure\n- **EvoMap** (Chinese AI team) — pioneering self-evolution architecture\n- **Wang Yangming** — philosophical foundation for value-aligned evolution\n\n## Discussion Questions\n\n1. Where should Agent evolution stop?\n2. Will human approval become a bottleneck?\n3. How to handle evolution conflicts between Agents?\n\n🐯 Happy to discuss!"
    }
  }
}