Prompt Engineering for Translators
Turn vague AI output into on-brief translations: glossaries, style rules, and reusable templates that make ChatGPT, Claude and Gemini obey.
Prompt engineering is no longer optional for language professionals. It is the difference between a draft you rewrite from scratch and one you lightly polish. Learn the four levers that control any model, the anatomy of a professional translation prompt, few-shot examples that teach your exact style, and how to inject terminology so output stays consistent across a long job. You will finish with a reusable template library that makes every future job faster.
What you'll learn
- Structure a prompt that reliably carries glossary, tone, and constraints
- Use few-shot examples to teach the model your exact style
- Control register, formality, and forms of address on demand
- Inject terminology and references so output stays consistent
- Build a reusable template library for your common job types
- Diagnose and fix a prompt that keeps producing the wrong output
Course content
- 1. Why the model disobeys, and the four levers that fix it (14 min)
- 2. The anatomy of a professional translation prompt (15 min)
- 3. Few-shot: teaching the model by example (15 min)
- 4. Controlling register, tone, and forms of address (16 min)
- 5. Feeding terminology and references for consistency (15 min)
- 6. Debugging a prompt and building your template library (15 min)
Related courses
- AI for Translators: Your First LLM Workflow — Drive ChatGPT, Claude & Gemini as a translation copilot: a repeatable, confidentiality-safe workflow that keeps you the editor in charge.
- Machine Translation Post-Editing (MTPE), Done Right — Post-edit to the right standard, light vs full per ISO 18587, spot the errors machines make, and price MTPE so it actually pays.
- AI Quality Evaluation & Supervision — Supervise the machine, don't just translate: grade AI output with MQM, use quality estimation, and design review workflows that scale.