Golden datasets were the gold standard for testing AI prompts until fast-changing production data made static tests rigid, costly, and stale. QA Wolf takes a different approach: random sampling against live data to keep prompt evaluations accurate and relevant as tasks shift daily.
Nishant Shukla, QA Wolf’s Senior Director of AI, and Justin Torre, CEO & Co-founder of Helicone, join host Caleb Masters to break down how real-time sampling closes the gap between lab results and real-world performance.
In this webinar, you’ll learn about:
- Why golden datasets fall short for evolving LLM and agent workflows.
- How random sampling keeps prompt evaluations true to production data through a Helicone demo.
- The benefits of reducing overfitting to speed up improvements.
Watch the video or read to recap. See how QA Wolf uses live sampling to keep tests accurate.