System Prompt
Hidden instructions provided to an LLM that define its behavior, personality, constraints, and capabilities for a conversation. System prompts set the rules of engagement before the user interacts.
Why It Matters
System prompts are how companies customize AI behavior for their products — defining tone, safety guardrails, domain focus, and response formatting.
Example
A customer support bot's system prompt: 'You are a helpful support agent for Acme Corp. Only answer questions about our products. Always be polite. Never discuss competitors.'
Think of it like...
Like stage directions for an actor — the audience does not see them, but they shape everything about how the performance unfolds.
Related Terms
Prompt Engineering
The practice of designing and optimizing input prompts to get the best possible output from AI models. It involves crafting instructions, providing examples, and structuring queries to guide the model toward desired responses.
Guardrails
Safety mechanisms and constraints built into AI systems to prevent harmful, inappropriate, or off-topic outputs. Guardrails can operate at the prompt, model, or output level.
Instruction Tuning
A fine-tuning approach where a model is trained on a dataset of instruction-response pairs, teaching it to follow human instructions accurately. This transforms a text-completion model into a helpful assistant.
Role Prompting
A technique where the model is instructed to adopt a specific persona, expertise, or perspective in its responses. The assigned role shapes tone, depth, terminology, and reasoning approach.
Prompt Injection
A security vulnerability where malicious input is crafted to override or manipulate an LLM's system prompt or instructions, causing it to behave in unintended ways.