ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
Defining code changes as state transitions with reproducibility guarantees and gate-enforced approval workflows
AI code generation is probabilistic, so the same prompt may produce different outputs across runs. In enterprise systems, this requires reproducibility, auditability, and explicit approval controls for every change. This paper introduces DB-Approved Development, a framework that models code changes as database-backed state transitions with reproducibility guarantees and gate-enforced approval workflows for AI-generated code.
A mathematical optimization of how often AI code generators should be required to explain their output, minimizing total cost of explanation overhead plus undetected errors
Requiring AI to explain every generated line can be expensive, while requiring no explanation increases risk exposure. The practical operating point lies between these extremes. This paper derives an optimal explanation interval that minimizes the combined cost of explanation overhead and undetected misgeneration risk.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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