# 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