Prompt Engineering
Crafting inputs that elicit more accurate or useful outputs from AI models.
Detailed Definition
Prompt engineering is the practice of systematically designing the text (and, in multi-modal setups, images or audio) you feed into an AI model so that its responses are more accurate, reliable, or stylistically aligned. It encompasses techniques such as role-setting (‘You are an expert…’), few-shot examples, chain-of-thought instructions, and system-level prompts baked into products. Effective prompt engineering can dramatically improve performance without retraining the underlying model.
Developer ToolsMore in this Category
LangChain
An open-source framework for developing applications powered by large language models (LLMs).
Vibe coding
Building applications using AI tools by describing what you want in plain English (prompts) rather than writing code.
MCP (model context protocol)
An open standard that allows AI models to interact with external tools like calendars, CRMs, or codebases easily and securely.
Vibe coding
Building applications using AI tools by describing what you want in plain English (prompts) rather than writing code.
MCP (model context protocol)
An open standard that allows AI models to interact with external tools like calendars, CRMs, or codebases easily and securely.