Real ChatGPT answer · index seedIX3pPeX7rUgcompleteB2B software · AI and automation toolsinformational

What causes LLM accuracy to degrade over time in production and how do engineers handle model drift detection today?

ChatGPTgpt-62 queries11/1/2026
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Fan-out diagram

The searches the AI actually ran for this prompt.

SEED QUERY
What causes LLM accuracy to degrade over time in production and how do engineers handle model drift detection today?
2 real searches · 1 real-search pass
LLM production monitoring drift detection evaluation observability input drift concept drift RAG evaluation 2025 2026Google ↗
OBSERVEDReason
NIST AI risk management monitoring deployed AI systems drift monitoring data quality evaluationGoogle ↗
OBSERVEDReason

Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.

Query classes

Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.

ChatGPT real searches (2)
Short factOther / navigationalComparisonConsequenceReason100%DefinitionInstructionYes / no

Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.

Searches and sources

ChatGPT2 real searches · gpt-6
LLM production monitoring drift detection evaluation observability input drift concept drift RAG evaluation 2025 2026 Google ↗
NIST AI risk management monitoring deployed AI systems drift monitoring data quality evaluation Google ↗

Queries

2 queries · click a column to sort
Query / typeSearchIntentQuery classRouting formatClusterFreq ↓Weight
LLM production monitoring drift detection evaluation observability input drift concept drift RAG evaluation 2025 2026
OBSERVED
Google ↗
AI Mode ↗
—Reason——1x
of 1
NIST AI risk management monitoring deployed AI systems drift monitoring data quality evaluation
OBSERVED
Google ↗
AI Mode ↗
—Reason——1x
of 1