Developed comprehensive integration documentation for the Weco-Langfuse workflow within the langfuse-docs repository, focusing on streamlining large language model (LLM) application code optimization. The work centered on clarifying the integration process between Weco and Langfuse, reducing ambiguity for developers onboarding new tools. Leveraging expertise in Python, AI integration, and data science, the documentation provided clear, actionable guidance to facilitate smoother cross-tool adoption. The approach emphasized targeted, practical instructions to minimize integration guesswork and support efficient development practices. This contribution addressed a key need for robust onboarding resources, enhancing the overall usability and maintainability of LLM application infrastructure.