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Deep Dive

Explainability

In RAG and agentic systems, explainability is the capability to provide a transparent audit trail linking a generated output to its retrieved source chunks and the specific reasoning steps taken by the model. It involves surfacing metadata, citation markers, and Chain-of-Thought (CoT) traces to prove that a response is grounded in factual context rather than being a hallucination.

Definition

In RAG and agentic systems, explainability is the capability to provide a transparent audit trail linking a generated output to its retrieved source chunks and the specific reasoning steps taken by the model. It involves surfacing metadata, citation markers, and Chain-of-Thought (CoT) traces to prove that a response is grounded in factual context rather than being a hallucination.

Disambiguation

Refers to tracing retrieval provenance and logic paths, not the internal mathematical weights of the neural network.

Visual Metaphor

"A Legal Brief with Footnotes: Every assertion made by the lawyer points directly to a specific page and line number in the discovery evidence folder."

Key Tools
LangSmithArize PhoenixTruLensWeights & Biases Prompt WatchLlamaIndex (Metadata Extractors)
Related Connections

Conceptual Overview

In RAG and agentic systems, explainability is the capability to provide a transparent audit trail linking a generated output to its retrieved source chunks and the specific reasoning steps taken by the model. It involves surfacing metadata, citation markers, and Chain-of-Thought (CoT) traces to prove that a response is grounded in factual context rather than being a hallucination.

Disambiguation

Refers to tracing retrieval provenance and logic paths, not the internal mathematical weights of the neural network.

Visual Analog

A Legal Brief with Footnotes: Every assertion made by the lawyer points directly to a specific page and line number in the discovery evidence folder.

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