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.

The bottom of the translation market is being automated, but the translators who supervise the machine are earning more, not less. This course gives you a complete, professional workflow for using ChatGPT, Claude, and Gemini as a first-draft and research copilot while you stay the editor who guarantees quality. You will learn to prompt for drafts you can trust, hunt the specific errors LLMs hide, protect your clients' confidential data, and price AI-assisted work so it actually pays. By the end you will have a repeatable system that makes you faster without putting your reputation, or your rates, at risk.

What you'll learn

• Build a repeatable LLM-assisted workflow you can trust on paid jobs
• Prompt for a first draft that carries your glossary, tone, and constraints
• Hunt the errors LLMs hide: hallucinations, silent omissions, fluent mistranslations
• Protect client confidentiality and stay on the right side of NDAs and data law
• Post-edit to the right level, light vs full, without over-polishing for free
• Know exactly when NOT to use AI, and how to price the work when you do

Course content

1. 1. The linguist above the machine (13 min)
2. 2. Meet your three copilots, and why you never marry one (13 min)
3. 3. The confidentiality line you must never cross (15 min)
4. 4. Prompting for a first draft you can trust (16 min)
5. 5. Where the machine lies: hunting the hidden errors (16 min)
6. 6. Post-editing like a pro: light vs full (15 min)
7. 7. When NOT to use AI, and how to charge for it (12 min)

Related courses

• 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.
• 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.