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Everything tagged “evaluation” across News, Learn, Research and Interviews.
Turn prompt tuning from trial-and-error into reproducible evaluation: building living datasets, prompt-as-code, automated optimizers, and continuous regression for production agents.
Production AI agents need observability that tracks token cost per session, failure cascades, and eval loops. Here are the metrics that keep them reliable and profitable.
For years, "production monitoring" meant a familiar dashboard: uptime, latency, error rate, saturation. If a service was up, fast, and error-free, it was health
How evaluation-driven data flywheels turn user feedback into smarter LLM products. Build trustworthy evals, calibrate LLM judges, and close the loop.
A practical guide to LLM observability covering prompt logging, real-time debugging, evaluation frameworks, and the major platforms for shipping reliable AI applications.