EDUCATION & TRAINING
Stop Evaluating LLMs with “Vibe Checks”
Towards Data Science
About This Tutorial
Evaluating Large Language Models (LLMs) with subjective "vibe checks" can lead to enterprise AI project failures to scale. Traditional software engineering rigor is often abandoned, and teams rely on human evaluation instead of measurable metrics. This approach neglects critical operational realities, such as latency, cost, and reliability, which are essential for production-ready AI systems. To move AI systems from fragile s to robust production assets, teams must build decision-grade evaluation scorecards that consider accuracy, latency, cost, and reliability.