A practical guide to LLM evaluations — what to measure, building eval sets, LLM-as-judge done right, RAG-specific metrics, and integrating evals into CI so you stop shipping silent regressions.
The prompt patterns I keep reaching for in production LLM apps — system prompt structure, role separation, structured output, few-shot, chain-of-thought, prompt caching, and the anti-patterns to skip.
How to actually use the Anthropic Claude API in production. Messages format, tool use, prompt caching for 90% cost cuts, structured outputs, streaming, and the gotchas worth knowing.
A from-scratch tutorial on building AI agents with LangGraph. Tools, persistent state, conditional routing, human-in-the-loop, and the production patterns most demos skip.
A complete, end-to-end RAG backend built on PostgreSQL + pgvector and FastAPI. Real chunking, real embeddings, hybrid (vector + BM25) retrieval, prompt assembly, citations, and production gotchas.