AI Glossary
Prompt Engineering
The discipline of designing precise instructions for AI models that maximize the quality and relevance of responses.
Prompt engineering is the most important skill for working with language models. The difference between a good prompt and a mediocre one can be a useful result vs a useless one.
Fundamental techniques
- Few-shot prompting: providing examples of the expected output
- Chain-of-thought: asking the model to reason step by step
- Role prompting: assigning a specific role to the model
- Structured output: requesting specific JSON, table, or list format
Common mistakes
- Prompts that are too vague or generic
- Not including enough context
- Not specifying output format
- Not iterating and refining the prompt
Application in business
In an SMB, prompt engineering applies to: email templates, support responses, data analysis, report generation, and any process where a language model participates.
Related services
Related terms
AI Agent
An AI system that can plan, execute actions, and use tools autonomously to complete complex tasks.
LLM (Large Language Model)
An artificial intelligence model trained on large volumes of text that can understand and generate natural language with high quality.
Fine-tuning
Process of retraining an AI model with your company's specific data so it specializes in your domain or tone.
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