OpenAI Academy Builder Bootcamp: Production & Optimization

This OpenAI Academy Builder Bootcamp session, led by OpenAI technical success engineer Sean Lubbers, is about taking an AI system that works and making it measurable, efficient, and production-ready. It covers how to benchmark model performance, compare baselines, and use evaluation results to make practical decisions about model selection and the tradeoffs between quality, latency, and cost.

The session then walks through fine-tuning and distillation patterns: preparing a dataset, generating teacher outputs, training a smaller model, and measuring whether the optimised model holds its quality. It is aimed at builders who want to move beyond proof-of-concept toward systems they can run cost-effectively at scale. As the closing module in the builder bootcamp series, it complements the earlier Codex, Evals, and RAG sessions. The livestream is free; register through OpenAI Academy.