System Prompt Development for AI Assistant
System Prompt — foundation of AI assistant behavior: defines role, constraints, answer format, communication tone. Quality system prompt is the difference between predictable production solution and unstable prototype.
Effective System Prompt Structure
- ROLE AND IDENTITY: Who are you? What do you do?
- CONTEXT AND KNOWLEDGE: What do you know? What data is available?
- TASKS: What to do? Priority order?
- CONSTRAINTS: What NOT to do? Out of scope topics?
- FORMAT AND STYLE: How to answer? Length, structure, tone?
- EDGE CASES: What to do with ambiguity or conflict?
Examples for Different Use Cases
- Corporate HR Assistant: helps with vacations, benefits, policies. NOT: salaries, hiring decisions, legal interpretation.
- Technical Assistant: provides working code, explains why, mentions risks. NOT: vague answers, no trade-off analysis.
- Customer Support: detect language, help with features/issues. Escalate: angry customers (2 exchanges), >$100 refunds.
System Prompt Testing
Test cases: happy path, edge cases, out of scope, adversarial. Eval: does assistant decline inappropriate requests? Does it include expected topics?
Versioning and Management: Store prompt versions in database. Track active version. Support rollback.
Timeline
- Basic system prompt: 1–2 days
- Version with edge case handling: 3–5 days
- Production with monitoring: 1 week