DSPy MIPROv2 Optimizer

Goal

Jointly optimize instructions and few-shot demonstrations using Bayesian Optimization for maximum performance.

When to Use

• You have 200+ training examples
• You can afford longer optimization runs (40+ trials)
• You need state-of-the-art performance
• Both instructions and demos need tuning

Related Skills

• For limited data (10-50 examples): dspy-bootstrap-fewshot
• For agentic systems: dspy-gepa-reflective
• Measure improvements: dspy-evaluation-suite