Presentation: Opening the Black Box: Critical Explainability for AI Agent Tool Selection with Kiji Inspector

Hannes Hapke shares how Dataiku’s open-source Kiji Inspector applies Sparse Autoencoders (SAEs) directly to decision tokens to expose why agents pick specific tools. Moving past superficial chain-of-thought narratives, he discusses causal ablation, layer activation extraction via patched vLLM engines, and production monitoring workflows for software architects and senior engineering leaders.

By Hannes Hapke
内容来源:InfoQ