Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills
Must ReadInfoQ · 2026-09-14 11:00 UTC AI
AI Summary
Alex Porcelli discusses the gap in enterprise AI regarding non-deterministic output and accountability. He proposes integrating DMN decision models with LLMs, agent skills, and NeMo guardrails to build auditable, deterministic agentic architectures. This allows business leaders to own decision logic while engineers maintain governance.
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Why should I care?
Because it shows how to combine LLMs with deterministic decision models, aligning with your interest in AI Agents and LLMs.
Content
Alex Porcelli discusses the critical gap in enterprise AI: non-deterministic output and lack of accountability in high-stakes decisions. He shares how integrating DMN decision models with LLMs, agent skills, and NeMo guardrails creates auditable, deterministic agentic architectures - allowing business leaders to own decision logic while engineers maintain robust architectural governance. By Alex Porcelli