No. Prompt improvements can help, but we also focus on structured outputs, validation, grounding where needed, cost/latency control, and measurable evaluation.

Yes. We reduce hallucinations by grounding responses where needed, using constraints and validations, and defining safe fallback behavior.

Fine-tuning makes sense when you have enough high-quality examples, stable objectives, and clear evidence it will outperform optimization and retrieval approaches.

Yes. We can optimize live systems with phased changes and measurable regression checks to avoid disrupting users.