Build a Prompt Learning Loop
summary
A hands‑on loop that generates outputs, runs OpenAI + Elements judge evaluations, collects rule‑level failures and English explanations, and injects those into an optimizer that rewrites the system prompt. A JSON web‑page notebook and a prompt hub prototype run the loop. Benchmarks show 15% improvement on coding tasks, 4.1 approaching 4.5 at two‑thirds the cost, and fewer iterations than evolutionary baselines; the agent Alex and the optimizer produce repeatable gains. rule‑by‑rule evals
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chapters (9)
- 0:00Introduction
- 1:59Agents fail in production
- 4:50Prompt learning basics
- 9:01Case study: effectiveness
- 13:38Prompt learning vs GA
- 23:05Setting up the prompt learning workshop
- 36:55JSON webpage prompt
- 43:13Running optimization loop
- 51:31Q&A
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