
from christophacham
A comprehensive workflow bundle for designing, building, and operating LLM applications, RAG systems, AI agents, and ML pipelines.
This bundle provides a structured, phase-based workflow for end-to-end AI and machine learning projects. It covers design, LLM integration, RAG implementation, multi-agent architectures, ML pipeline development, observability, and security. The skill groups related sub-skills into actionable phases and includes prompts and checklists to guide implementation.
Use this workflow when you are planning or building production LLM applications, implementing retrieval-augmented systems, creating autonomous or multi-agent solutions, setting up ML pipelines, or adding AI features to existing products. It's also useful for teams establishing observability and security practices for AI systems.
This skill is implementation-agnostic and can support agents and tools used for AI development such as Claude Code, Gemini CLI, LangChain-based workflows, and general-purpose developer agents (Copilot/Code assistants).
This skill has not been reviewed by our automated audit pipeline yet.
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