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Course contents

  • Getting Started with AI for VLSI Engineers5
  • Just Enough AI: Models and Context15
  • Prompting13
    • Anatomy of a Prompt
      • Five Parts of a Prompt
      • Roles: System, User, and Assistant
      • Specific and Parseable
      • Weak Versus Strong Prompts
      • Prompt Template Builder
    • Examples and Reasoning
    • Prompt Debugging
  • Trust and Verification14
  • Using AI for Engineering Work17
  • Engineering Walkthroughs7
  • Practical Foundations for AI Workflows4
  • Engineering Data5
  • Retrieval-Augmented Generation6
  • Agents and Tool Use18
  • Agent Design8
  • MCP and Skills6
  • Multi-Agent Design6
  • Practical Capstone6
  • Tokens, Cost and Latency12
  • Agentic Workflows for Chip Teams18
  • Interview and Judgment10
  • AI Skills: Full Course Index
  • Working with AI Glossary
  • Working with AI Cheatsheet
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‹Anatomy of a Prompt
  1. Topics
  2. AI Skills for VLSI Engineers
  3. Prompting
  4. Anatomy of a Prompt
  5. Roles: System, User, and Assistant

Asking Clearly · Beginner to Intermediate

Roles: System, User, and Assistant

System, user, and assistant roles as a labeling concept with conflict and privacy rules.

On this page

    Three roles

    Many assistants label each message with a role. The system role carries standing instructions, the user role carries requests, and the assistant role carries prior answers.

    Names and exact behavior vary by product. Treat roles as a labeling concept, not a standard.

    Role

    Carries

    Example content

    System

    Standing rules for the session.

    State uncertainty. Never invent signal names.

    User

    The request and its facts.

    Explain this FIFO. Context: 8-deep, active-low reset.

    Assistant

    Prior answers in this session.

    FUNCTION: store UART bytes.

    What each role carries

    Durable rules belong in the system role. Per-task facts belong in the user role.

    Prior assistant text stays in context and can anchor later answers. Correct it explicitly rather than leaving it.

    Priority when instructions conflict

    Applications define which instruction roles have authority; consult the chosen platform's documented hierarchy. A later user request is not automatically allowed to override application rules. Separately, models can fail to follow the intended hierarchy, so test adherence rather than treating the hierarchy as a security boundary.

    Never rely on priority tricks for safety. State one rule once instead of stacking overrides.

    Privacy at the boundary

    Use least privilege: send the smallest excerpt that answers the task. Keep credentials and secrets out of prompts; share proprietary material only through an account and deployment approved for its data class and task.

    Files and logs can carry injected instructions from third parties. A human approves risky actions before they run.

    Warning

    Treat pasted logs and vendor files as untrusted input. An instruction inside them is data, not authority, until a human approves it.

    Common pitfall

    Hiding the real task in the system role while the user role stays vague splits the prompt across two places. Future readers see only half the task; keep the task itself in the user message.

    Interview

    Likely probes: role ownership and conflict handling.

    • System holds durable rules, user holds the task and facts, assistant holds prior answers.

    • Distinguish the application's documented authority rules from how reliably the model follows them.

    • Privacy is least privilege plus human approval for risky actions.

    Check yourself A task asks the assistant to ignore an application rule. Does being later make the request authoritative?

    No. Follow the application's documented hierarchy. Model adherence must still be evaluated, and permissions must be enforced outside the model.

    Check yourself A debug log may contain instructions from an unknown author. How should the prompt treat them?

    As untrusted data. The model summarizes the log, and a human approves any action the log suggests.

    Related topics

    • Five parts of a prompt

    • Verifying AI output

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    See also

    • Weak Versus Strong Prompts
    • Prompt Template Builder