Prompt Engineering
The practice of designing and structuring prompts to obtain more accurate and useful outputs from AI models.
The practice of designing and structuring prompts to obtain more accurate and useful outputs from AI models.
What Is Prompt Engineering
Prompt engineering is the process of crafting instructions that guide AI models toward reliable, relevant, and context-aware outputs. It combines linguistic clarity, task design, and iterative refinement.
How Prompt Engineering Works
Effective prompts define objective, context, constraints, and expected output format. By reducing ambiguity, prompts help models prioritise the right information and produce more stable responses across repeated requests.
Types of Prompting Techniques
- Instruction prompting: explicit commands describing the task and rules.
- Few-shot prompting: examples demonstrating desired input-output behaviour.
- Role prompting: assigning perspective or expertise (for example, legal translator).
- Constraint prompting: limiting style, length, terminology, or structure.
- Chain-of-thought style scaffolding: encouraging stepwise reasoning in complex tasks.
Role in Large Language Models
Large language models are highly sensitive to instruction quality. Prompt engineering improves controllability, reduces hallucination risk, and supports consistent performance without modifying model weights.
Applications in Translation and Language Technologies
In translation workflows, prompt engineering helps enforce terminology, preserve tone, follow domain conventions, and keep document-level consistency. It is widely used in AI-assisted localisation, quality estimation, terminology extraction, and multilingual content generation.
Related Terms
Parallel Corpus
A collection of texts and their translations in two or more languages used to train machine translation systems.
Post-Editing (MTPE)
The process of reviewing and correcting machine translation output to achieve publishable quality.
Pretraining
The initial phase of training a machine learning model on large datasets before adapting it to specific tasks.
Project Management in Translation
Organising translation tasks, resources, deadlines, and quality processes.
Prompt
A structured instruction or input guiding an AI model’s behaviour.
Related Resources
Prompt
A structured instruction or input guiding an AI model’s behaviour.
Large Language Model (LLM)
A neural model trained on vast text corpora, capable of understanding and generating natural language.
Context Window
The amount of text an AI model can process at once during translation or generation.
Generative AI
AI systems that generate new text, images, audio, code, or other content from learned patterns.
Natural Language Processing (NLP)
A field of artificial intelligence focused on enabling computers to understand, analyse, and generate human language.
Token
A unit of text processed by a model, such as a word, subword, or punctuation mark.