Giving your AI a Job Interview

You can’t rely on vibes to understand these patterns, and you can’t rely on general benchmarks to reveal them. You need to systematically test your AI on the actual work it will do and the actual judgments it will make. Create realistic scenarios that reflect your use cases. Run them multiple times to see the patterns and take the time for experts to assess the results. Compare models head-to-head on tasks that matter to you. It’s the difference between knowing “this model scored 85% on MMLU” and knowing “this model is more accurate at our financial analysis tasks but more conservative in its risk assessments.” And you are going to need to be able to do this multiple times a year, as new models come out and need evaluation.