This presentation explores the complex and often contradictory nature of large language models (LLMs) in data science, acknowledging the simultaneous excitement and apprehension that we feel toward these technologies. We’ll provide a practical framework to help you understand the LLM ecosystem (from foundation models and hosting to SDKs and applications) that supports our current philosophy: augmenting, not replacing human intelligence. The talk demonstrates how Posit is addressing this space through two complementary approaches: building SDKs and tools that help you create your own LLM-powered solutions, and developing integrated LLM capabilities directly into data science workflows through tools like Positron assistant and databot. We’ll showcase practical, immediately useful applications while addressing current limitations, providing you with both the emotional preparation and technical foundation needed to effectively leverage LLMs in their data science practice today.