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Paging Charity! How can engineering leaders avoid becoming Bond villains? Code isn’t the only thing causing your production failures Your AI shipped a backend that boots. That is the whole problem. The 2026 Developer Survey is now open (for human developers only)! Oh the places you’ll go with spatial data Dispatches from O'Reilly: From capabilities to responsibilities You don’t understand DNS like you think you do The new bottleneck - Stack Overflow AI agents are a confused deputy with the keys to your kingdom If context is king, architecture is the castle Selenium vs Cypress vs Playwright: Choosing Your Test Automation Framework AI agents expose the security checks you never actually wrote Designing CherryScript: Optimizing Data-Driven Workflows via Custom Python-Based Interpreters Paging Charity? How do I get my leaders to stop running teams Into the ground? Developers are emotionally attached to their tools When the cost of code approaches zero, what does engineering leadership look like? Announcing Stack Overflow for Agents Creating checkpoints by gaslighting a Postgres database What can 500 years of journalism teach developers about AI trustworthiness? Making the OWASP top ten in the vibe code era What it takes to be a player in the international AI game Best of the Heap: First post of the past The find out stage of AI is just supply chain and password protection In an AI world, the most valuable developers will be both artisans and builders Agents on a leash: Agentic AI remains mostly single-agent and monitored at work Do you have what it takes to run AI in production? Dispatches from O'Reilly: The accidental orchestrator Breaking your AI storage bottlenecks Coding agents are giving everyone decision fatigue Pack your agentic stack in Slack
Connecting the dots for accurate AI
Phoebe Sajor · 2026-05-12 · via Stack Overflow Blog

At HumanX, Ryan is joined by Philip Rathle, CTO at Neo4j to discuss what knowledge context means for AI agents, how limitations like stale training data make the model-only approach to agents a bad fit for enterprise environments, and how Graph RAG raises the bar for accuracy and reduces context rot by combining vectors with a knowledge graph so agents are more targeted and connected.

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Neo4j is a native graph database management system designed to handle complex, highly-connected data by focusing on relationships rather than tables. You can try it out for free on Aura and learn more at their Graph Academy.

Connect with Philip on LinkedIn.

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