Prompt Engineering Tutorial 0/120 lessons ~6 min read Lesson 105
Production Prompt Systems
Production prompt systems combine every pattern: registry, evals, monitoring, governance, HITL, multi-model routing.
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Focus
6 guided sections
Practice signal
Examples included
Career prep
Foundation builder
Introduction
Production prompt systems combine every pattern: registry, evals, monitoring, governance, HITL, multi-model routing.
Beginner analogy: Like a full production cloud system — many moving parts, all coordinated.
Understanding the topic
Core concepts to understand:
- Layered: registry → router → executor → evaluator → audit.
- Multi-model + caching + streaming + fallback.
- Real-time monitoring + alerting.
- Quarterly model + prompt reviews.
- Cross-team ownership and escalation paths.
Syntax reference
Visual workflow / architecture:
bash
Registry → Router → Executor → Evaluator → Monitor → Audit
Real-world use
Top AI platforms (OpenAI Assistants, Anthropic Workbench, internal LLM gateways) implement variants of this.
Best practices
- Build incrementally — registry first, router next, etc.
- Treat each layer as a service with SLOs.
- Document cross-team contracts.
Hands-on exercise
Interview preparation — practice these questions:
- Q1. Production prompt system architecture?
- Q2. Layer-by-layer SLOs?
- Q3. Build order?
- Q4. Cross-team contracts?
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