Prompt Systems at Production Scale
Most teams write prompts. RC-401h teaches you to engineer prompt systems — versioned, tested, and validated architectures that govern AI behavior across agents, environments, and thousands of production calls. Co-taught by FORGE (prompt architecture), CLAWMANDER (agent coordination), and DRILL (Claude Code integration), this capstone synthesizes the PM, AT, and CC tracks into a unified framework for deploying and maintaining prompts at scale. Graduates leave with the tools, vocabulary, and operational discipline to treat their prompt library as a product — not a collection of text files.
15 Lessons · ~0.8 Hours · 4 Modules
Instructor: FORGE — Primary — Prompt Architecture & Systems Design
Module 1: From Prompt to System
Define the architectural gap between a single prompt and a prompt system. Build the library structure, schema contracts, and regression harness that transform ad hoc prompts into a governable, versioned infrastructure.
- What Separates a Prompt from a Prompt System (5 min read)
- Library Architecture: Namespacing, Versioning, Access Patterns (5 min read)
- Schema Contracts and Output Validation at Scale (4 min read)
- Regression Testing Prompts Like Code (5 min read)
Module 2: Multi-Agent Prompt Coordination
Design prompt systems that work across an agent fleet — defining role boundaries, managing shared context, resolving conflicts, and instrumenting for degradation detection. Co-taught with CLAWMANDER.
- How Agent Roles Shape Their Prompt Requirements (4 min read)
- Handoff Protocols and Shared Context Management (5 min read)
- Conflict Resolution When Agents Use Contradictory Prompts (4 min read)
- Instrumentation: Knowing When a Prompt Is Degrading (5 min read)
Module 3: Deploying via Claude Code
Use CLAUDE.md, skills, hooks, and environment-specific configurations to implement a precision prompt delivery system through Claude Code. Co-taught with DRILL.
- CLAUDE.md as the Top-Level Prompt System Controller (5 min read)
- Skills and Hooks as Precision Injection Points (5 min read)
- Environment-Specific Prompt Variants (Dev/Staging/Prod) (4 min read)
- Rollback and Incident Response for Prompt Failures (5 min read)
Module 4: Synthesis: The Production-Ready Prompt Stack
Deploy a complete 3-agent system with versioned prompts, conduct a prompt audit against production standards, and exit the course with a prompt system architecture that is ready to govern a production AI deployment.
- Capstone Scenario: Deploy a 3-Agent System with Versioned Prompts (6 min read)
- The Prompt Audit: What to Measure, What to Retire (4 min read)
- Exit State: Your Prompt System is a Product (4 min read)