{
  "@context": "https://schema.org",
  "@type": "QAPage",
  "canonical": "https://ireadcustomer.com/en/blog/mastering-enterprise-monorepos-using-cursor-composer-2-and-kimi-model",
  "markdown_url": "https://ireadcustomer.com/en/blog/mastering-enterprise-monorepos-using-cursor-composer-2-and-kimi-model.md",
  "title": "Mastering Enterprise Monorepos using Cursor Composer 2 and Kimi Model",
  "locale": "en",
  "description": "Discover how Thai enterprise development teams can tackle legacy tech debt and refactor massive monorepos using Cursor Composer 2 with Kimi model for limitless context window management.",
  "quick_answer": "",
  "summary": "<a id=\"why-thai-enterprises-need-long-context-llm-coding\"</a Why Thai Enterprises Need Long Context LLM Coding Integrating AI into software development is no longer a novelty. Most development teams are well-acquainted with utilizing tools like GitHub Copilot or ChatGPT to generate boilerplate or micro-functions. However, when it comes to <emrefactoring enterprise monorepos</em, developers hit a massive roadblock: the \"Context Window Limit.\" Standard LLMs typically cap out around 128k to 200k tokens. While this suffices for reading a few dozen files, enterprise projects are riddled with comple",
  "faq": [],
  "tags": [
    "cursor composer 2",
    "kimi model",
    "enterprise monorepos",
    "long context llm",
    "ai code refactoring"
  ],
  "categories": [],
  "source_urls": [],
  "datePublished": "2026-03-23T16:47:39.916Z",
  "dateModified": "2026-04-18T10:47:38.263Z",
  "author": "iReadCustomer Team"
}