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Concept

Cold Start Problem

The performance gap or reasoning failure that occurs when an AI Agent or RAG system lacks sufficient historical context, indexed documents, or few-shot examples to ground its initial operations. In RAG, this often refers to the 'empty index' phase or the trade-off between deployment speed and the time required to generate high-quality embeddings for large datasets.

Definition

The performance gap or reasoning failure that occurs when an AI Agent or RAG system lacks sufficient historical context, indexed documents, or few-shot examples to ground its initial operations. In RAG, this often refers to the 'empty index' phase or the trade-off between deployment speed and the time required to generate high-quality embeddings for large datasets.

Disambiguation

In AI, this refers to data and context scarcity, not the latency of spinning up serverless containers.

Visual Metaphor

"An intern arriving at a new job with an empty desk and no handover notes, forced to guess until they gain institutional knowledge."

Key Tools
LangChain (Memory modules)PineconeZep (Memory store)MemGPTRedis (Semantic Caching)
Related Connections

Conceptual Overview

The performance gap or reasoning failure that occurs when an AI Agent or RAG system lacks sufficient historical context, indexed documents, or few-shot examples to ground its initial operations. In RAG, this often refers to the 'empty index' phase or the trade-off between deployment speed and the time required to generate high-quality embeddings for large datasets.

Disambiguation

In AI, this refers to data and context scarcity, not the latency of spinning up serverless containers.

Visual Analog

An intern arriving at a new job with an empty desk and no handover notes, forced to guess until they gain institutional knowledge.

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