Against Theory-Motivated Experimentation
Summary
The article promotes a new practical guide on using large language models with Python for analysts, covering API usage across major providers, RAG applications, tool calling, and model orchestration through MCP and agents. It contrasts this hands-on tutorial with competing texts and provides extensive content including a detailed table of contents and sample code, aiming to equip readers to build real LLM-driven workflows.