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Observability and human intuition in an AI world

In this two-for-one episode recorded at HumanX, Ryan is first joined by Christine Yen, CEO of Honeycomb, to discuss how AI compresses the software development lifecycle, making observability about capturing the right telemetry. Then, Spiros Xanthos, founder and CEO of Resolve AI, shares with us how AI coding increases code volume but decreases human intuition, making production operations harder than ever.

Connecting the dots for accurate AI

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.

What (un)exactly do you mean by semantic search?

Ryan welcomes Brian O’Grady,  Head of Field Research and Solutions Architecture at Qdrant, to discuss the differences between traditional text search engines powered by Lucene and modern vector databases, when vector search’s exact-match needs work for things like logs and security analytics and when semantic search works for user-facing discovery and non-exact results, and how Qdrant is growing into video embeddings and local-agent contexts.