KaybaAI/Agentic-Context-Engine
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1<!doctype html>2<html>3 <head>4 <meta charset="utf-8" />5 <meta name="viewport" content="width=device-width" />6 <title>Agentic Context Engineering</title>7 <link rel="stylesheet" href="style.css" />8 </head>9 <body>10 <div class="card">11 <div class="banner">12 <img src="Screenshot 2025-10-22 at 17.04.10.png" alt="KAYBA" />13 </div>14 <br>15 <h1>We open-sourced Stanford's "Agentic Context Engineering" implementation - agents that learn from execution</h1>16 17 <p class="intro">We shipped an implementation of Stanford's "Agentic Context Engineering" paper: agents that improve by learning from their own execution.</p>18 19 <p class="section-title">How does it work? A three-agent system (Generator, Reflector, Curator) builds a "playbook" of strategies autonomously:</p>20 21 <ul class="features">22 <li>Execute task → Reflect on what worked/failed → Curate learned strategies into the playbook</li>23 <li>+10.6% performance improvement on complex agent tasks (according to the papers benchmarks)</li>24 <li>No training data needed</li>25 </ul>26 27 <p class="integration">My open-source implementation works with any LLM, has LangChain/LlamaIndex/CrewAI integrations, and can be plugged into existing agents in ~10 lines of code.</p>28 29 <div class="links">30 <p><strong>GitHub:</strong> <a href="https://github.com/kayba-ai/agentic-context-engine" target="_blank">https://github.com/kayba-ai/agentic-context-engine</a></p>31 <p><strong>Paper:</strong> <a href="https://arxiv.org/abs/2510.04618" target="_blank">https://arxiv.org/abs/2510.04618</a></p>32 </div>33 34 <p class="feedback">Would love feedback!</p>35 </div>36 </body>37</html>38