agentic-eval

Yes, you can automate test-driven code refinement by using iterative self-critique loops that automatically run tests, identify failures, and refine the generated code until it passes, ensuring functional correctness without manual intervention.

The best way to implement self-critique loops is by applying structured evaluation patterns that parse critique results reliably, enabling agents to assess and improve their own work through rubric-based or outcome-based strategies.

Yes, structured output formats are required for reliable parsing of critique and evaluation results in agentic evaluation systems, ensuring the iterative refinement process can accurately interpret and act upon self-critique feedback.

You should use iterative refinement for quality assurance when generating code for specific specifications that require functional correctness, applying test-driven loops to evaluate, critique, and improve outputs until quality standards are met.

Limitations of LLM-as-judge assessment strategies include the dependency on structured output for reliable parsing, potential evaluation loops that fail to converge without clear rubrics, and the need for objective outcome-based tests to ensure functional correctness.