QMS Framework
Applying Quality Management System principles to AI generation ensures robust, reliable, and continuously improving outputs. This framework treats AI interaction as a monitored production line with built-in quality control and corrective action loops.
Customer Requirement
(Source of Truth)
Progenitor A
Synthesizer C
Progenitor B
Instrumentation
Process Monitoring
Validator D
Internal Audit
Feedback Loop
Verified Product
Final Artifact
Core Principles
Source of Truth
The process begins with a clear, unambiguous "Customer Requirement." This is the foundational specification against which all subsequent work is measured, ensuring the final product is aligned with the initial goal.
Monitored Execution
Like a production line, multiple "Progenitors" create components that are assembled by a "Synthesizer." Crucially, the entire workflow is observed by "Instrumentation," which collects process data without interfering.
Systematic Validation
The "Validator" performs an internal audit, using evidence from Instrumentation to check the synthesized product against the original requirement. This is a go/no-go decision point: products either pass inspection or are rejected.
Corrective Action (CAPA)
A failed validation triggers a "Corrective and Preventive Action." The "Feedback Loop" sends the rejected product back for rework, providing context on the failure. This ensures the system learns from its mistakes and improves over time.