Grounded Inference by Marty O'Neill: Deterministic Encapsulation

Grounded Inference, a paper credited to Marty O'Neill on arXiv, was submitted on 18 Jun 2026 as arXiv:2606.19753 and argues for a foundational framework to integrate generative models into traditional systems. The manuscript, 12 pages with 3 figures, defines four primitives of AI blended architecture and describes two overarching anti-patterns to help engineers achieve deterministic encapsulation of probabilistic models.

What does the paper propose?

The paper proposes four specific primitives for AI blended architecture intended to enable deterministic encapsulation of probabilistic generative models, and it names two overarching anti-patterns as warnings to engineers. The abstract says the framework is designed both to "enable successful integration of AI into traditional systems" and to provide a basis for generative model providers to build next-generation interfaces. The submission lists the work under the subjects Artificial Intelligence (cs.AI) and Software Engineering (cs.SE).

Beyond that summary, the arXiv record shows the manuscript is available as a PDF and TeX source and notes an arXiv-issued DOI via DataCite pending registration. The paper is presented as 12 pages containing 3 figures, which suggests a short, focused position and design document rather than a long experimental study.

How does this fit prior work or existing needs?

The manuscript frames its contribution against the current risks and costs of adopting generative models: it says many early adopters "have realized these perils at great expense," and asserts the field still lacks foundational frameworks to de-risk AI integration into traditional systems. In that context the paper positions its primitives and anti-patterns as a practical engineering foundation rather than a purely theoretical result.

The arXiv entry offers two author name variants: the paper's author line shows "Marty O'Neill," while the submission history lists the sender as "Martin O'Neill." The record also supplies the formal citation string arXiv:2606.19753 [cs.AI], which readers can use to locate the PDF or TeX source provided on the arXiv page.

Why it matters

Concrete engineering patterns matter when probabilistic models meet deterministic systems. By codifying four primitives and calling out two anti-patterns, the paper attempts to reduce integration risk and give engineers specific design targets. That could change how enterprises structure interfaces to generative models and how vendors expose deterministic wrappers for probabilistic behavior.

What to watch

Look for public copies of the PDF and TeX source linked on the arXiv page and for an official DOI once the DataCite registration completes. Also watch for follow-up work or implementations that adopt the paper's four primitives or that explicitly test the two anti-patterns in production stacks.

Details and source notes: the arXiv record shows the submission date as 18 Jun 2026, the arXiv identifier arXiv:2606.19753, and the file length as 12 pages with 3 figures. The paper is listed in cs.AI and cs.SE on arXiv.