System prompt

The instruction layer a model treats as highest priority: its role, rules and boundaries for the whole conversation.

Last updated: November 9, 2026 · Markdown version

How to apply it in prompts

Use this concept to reduce ambiguity and improve consistency. If you need strict formatting, combine it with a JSON guide and a per-model template.

Related terms:Role prompting Constraints

Strict JSON Models Packs

What it means

Definition: in many chat products and APIs, instructions are layered by priority (system, then developer, then user). The system layer sets who the model is and what it must or must not do.
Why it matters: rules placed there survive the whole conversation, so a user message is less likely to override them than the same rule written mid-chat.
How to apply it: in the API, put role, rules and output format in the system field. In a chat window you usually cannot edit the real system prompt, but you can emulate it with a clear 'Role + Rules' block at the top of your first message.
Common mistake: stuffing the task, the data and one-off examples into the system prompt. Keep it for what is stable; send what changes with each request as the user message.

Copy-paste example

Role: You are a concise editor for a product blog.
Rules:
- Be direct; no filler.
- Keep the author's voice and meaning.
- If something is missing or ambiguous, ask before rewriting.
Output: the rewritten text, then a list of what you changed.

Task: rewrite this text for clarity:
"""[paste]"""

Opens the analyzer with the prompt prefilled.

Open in Promptea

FAQ

Do I need to write the word 'system' in my prompt?

No. In a chat window just put the role and the rules first and mark them clearly. In an API, use the system field the provider gives you.

What is the difference between a system prompt and a user prompt?

The system prompt holds stable behavior (role, rules, format) and ranks above the rest; the user prompt holds the request of the moment. Putting stable rules in the system layer keeps them from being diluted by a long conversation.