This submission is a prompt-based terminology and segment injection strategy for terminology translation across domains. We evaluate the technique on Basque to Spanish, English to Polish, and Traditional Chinese to English for WMT 2026 Terminology Shared Task 1 & 2. We demonstrate that injecting bilingual terminology and bi-text examples into recent Large Language Models’ (LLM) prompts improves both overall translation quality and terminology accuracy. Our results show that strong instruction-following ability allows a system to adapt to terminology and style constraints without the need for fine-tuning.