- Balance auto-evals with the last mile of human reviews: While LLM-judges or programmatic evals provide scale, human evaluations capture nuanced quality signals that auto evals might miss.
- Curate golden datasets: Human-annotated datasets are key to defining what “good” means for your specific use case, forming the foundation for effective offline evaluation.
- Align LLM judges: LLM judges must be aligned with human preferences continuously to ensure they are tuned to your agent-specific outcomes.
Simulation and Evaluation
Does Maxim Support Human-in-the-Loop Evaluation for Agents?
Maxim provides comprehensive support for human-in-the-loop workflows across the AI development lifecycle. You can leverage internal or external domain experts seamlessly on the platform to: