# QCon AI Boston 2026

Published articles for QCon AI Boston 2026.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills

DevFeed: [Presentation: Decision Models in Agentic Architectures: From Production to Agent Skills](<https://devfeed.tech/articles/presentation-decision-models-in-agentic-architectures-from-production-to-agent-skills-17397.md>)

Original publisher: [Read original article](<https://www.infoq.com/presentations/decision-models-agentic-ai/>)

Author: Alex Porcelli

Published: 2026-09-14T11:00:00Z

Content type: article

Language: en

Sources: [InfoQ](<https://devfeed.tech/sources/infoq.md>)

Topics: [Agent Skills](<https://devfeed.tech/topics/agent-skills.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [NeMo](<https://devfeed.tech/topics/nemo.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agent-skills](<https://devfeed.tech/tags/agent-skills.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai-architecture](<https://devfeed.tech/tags/agentic-ai-architecture.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [ai-ml-data-engineering](<https://devfeed.tech/tags/ai-ml-data-engineering.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [architecture-design](<https://devfeed.tech/tags/architecture-design.md>), [architectures](<https://devfeed.tech/tags/architectures.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [business](<https://devfeed.tech/tags/business.md>), [decision-models-agentic-ai](<https://devfeed.tech/tags/decision-models-agentic-ai.md>), [development](<https://devfeed.tech/tags/development.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [enterprise-architecture](<https://devfeed.tech/tags/enterprise-architecture.md>), [governance](<https://devfeed.tech/tags/governance.md>), [infoq](<https://devfeed.tech/tags/infoq.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [llms](<https://devfeed.tech/tags/llms.md>), [ml-data-engineering](<https://devfeed.tech/tags/ml-data-engineering.md>), [models](<https://devfeed.tech/tags/models.md>), [nemo](<https://devfeed.tech/tags/nemo.md>), [presentation](<https://devfeed.tech/tags/presentation.md>), [production](<https://devfeed.tech/tags/production.md>), [qcon-ai-boston-2026](<https://devfeed.tech/tags/qcon-ai-boston-2026.md>), [qcon-software-development-conference](<https://devfeed.tech/tags/qcon-software-development-conference.md>), [skills](<https://devfeed.tech/tags/skills.md>), [transcripts](<https://devfeed.tech/tags/transcripts.md>)

### AI overview

Alex Porcelli explains how DMN decision models can be integrated with LLMs, agent skills, and NeMo guardrails to create auditable and deterministic agentic architectures for high-stakes enterprise decisions.

### Source excerpt

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

## Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs

DevFeed: [Presentation: From Retrieval to Reasoning: Building Production-Ready Agentic AI Systems with Knowledge Graphs](<https://devfeed.tech/articles/presentation-from-retrieval-to-reasoning-building-production-ready-agentic-ai-systems-with-knowledge-graphs-8463.md>)

Original publisher: [Read original article](<https://www.infoq.com/presentations/knowledge-graphs-agentic-systems-patterns/>)

Author: Cassie Shum

Published: 2026-09-12T11:00:00Z

Content type: tutorial

Language: en

Sources: [InfoQ](<https://devfeed.tech/sources/infoq.md>)

Topics: [Graphs](<https://devfeed.tech/topics/graphs.md>), [Architecture & Design](<https://devfeed.tech/topics/architecture-design.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [agentic-ai-architecture](<https://devfeed.tech/tags/agentic-ai-architecture.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-architecture](<https://devfeed.tech/tags/ai-architecture.md>), [ai-ml-data-engineering](<https://devfeed.tech/tags/ai-ml-data-engineering.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [architecture-design](<https://devfeed.tech/tags/architecture-design.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [code](<https://devfeed.tech/tags/code.md>), [development](<https://devfeed.tech/tags/development.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [infoq](<https://devfeed.tech/tags/infoq.md>), [knowledge-graph](<https://devfeed.tech/tags/knowledge-graph.md>), [knowledge-graphs-agentic-systems-patterns](<https://devfeed.tech/tags/knowledge-graphs-agentic-systems-patterns.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [ml-data-engineering](<https://devfeed.tech/tags/ml-data-engineering.md>), [presentation](<https://devfeed.tech/tags/presentation.md>), [production](<https://devfeed.tech/tags/production.md>), [qcon-ai-boston-2026](<https://devfeed.tech/tags/qcon-ai-boston-2026.md>), [qcon-software-development-conference](<https://devfeed.tech/tags/qcon-software-development-conference.md>), [rag](<https://devfeed.tech/tags/rag.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [retrieval-augmented-generation](<https://devfeed.tech/tags/retrieval-augmented-generation.md>), [transcripts](<https://devfeed.tech/tags/transcripts.md>)

### AI overview

A presentation on using knowledge graphs as a foundation for production-ready agentic AI systems. It covers architectural patterns for context bundling, decision provenance, code as truth, and agent visibility, along with a graph-based engineering harness for feedback loops, token optimization, and reliability.

### Source excerpt

Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability. By Cassie Shum