Category:
Category:
Prompt Engineering
Category:
Core AI & LLM Concepts
Definition
The craft of designing prompts to optimize LLM outputs.
Explanation
Prompt engineering designs prompts that guide LLMs toward accurate, structured, contextual outputs. Techniques include role prompting, chain-of-thought, few-shot examples, output formatting, tool-call structure, and safety prompting. While models improve, prompting remains essential for reliable agent behavior and workflow stability.
Technical Architecture
Prompt Template → LLM → Output → (Optional) Validator
Core Component
Template library, few-shot examples, format constraints, role instructions
Use Cases
Assistants, agents, code generation, reasoning tasks, RAG formatting
Pitfalls
Brittle prompts across models; prompt injection risks; overspecification
LLM Keywords
Prompt Engineering, Structured Prompting, Chain Of Thought Prompting
Related Concepts
Related Frameworks
• Instruction Tuning
• CoT
• Guardrails
• Prompt Template Library