Pre-Response Discernment Architecture — a prior decision architecture for justified progression in AI systems.
PRDA is a pre-response AI governance architecture. It determines whether an AI system should proceed at all, and under what conditions, before response generation, tool use, memory access, or action execution.
As AI systems move beyond text output into tools, memory, and operational behavior, governance can no longer begin only after an output is produced. PRDA introduces a prior decision layer centered on admissibility, scope, authority, conditions, and escalation.
PRDA begins from a prior governance question: whether a system should be allowed to proceed at all, under what conditions, within what scope, and with what level of authority before response generation, tool use, memory access, or action execution.
It is designed for AI systems that increasingly move beyond simple output generation into tools, memory, and operational decisions.
PRDA does not begin from output review, runtime monitoring, or post-hoc auditability. It begins earlier: at the point of admissibility and justified progression.
PRDA is not a content moderation layer, a post-hoc audit tool, or a substitute for human oversight. It is a prior governance architecture for determining whether and how a system should be permitted to proceed.
Public archived paper and versioned reference record.
https://doi.org/10.5281/zenodo.19371813Minimal public-facing reference demo for practical exploration.
github.com/DimitraStAthanasopoulouhub/prda-open-reference-demoFor written communication, research contact, or relevant governance discussion:
research@dimitraathanasopoulou.com