AI and Data Engineering Plugin¶
Skills for data engineering, AI/ML production systems, RAG, agents, and LLM cost optimization.
- data-engineering: ELT/ETL, dbt, orchestration, warehouse cost controls, data contracts, and feature stores.
- ai-ml-landscape: 2026 frontier model landscape, production ML patterns, classical ML, inference serving, and governance.
- rag-and-agents: RAG pipeline design (hybrid search, reranking, parent-child chunking), agent frameworks, MCP, and Azure AI Search.
- llm-cost-optimization: Token economics, model routing, prompt caching, APIM AI gateway, PTU/Batch pricing, cost governance, and provider-agnostic prompt/context compression (LLMLingua family, RECOMP, extractive compression, caveman prompting, token-lean formats, Chain-of-Draft).