How do modern product teams track generative AI productivity gains without relying on misleading metrics like lines of code or number of prompts sent?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do modern product teams track generative AI productivity gains without relying on misleading metrics like lines of code or number of prompts sent?
1 real search · 1 real-search pass
DORA software delivery performance metrics generative AI productivity measurement SPACE framework developer productivity researchGoogle ↗
OBSERVED
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.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
DORA software delivery performance metrics generative AI productivity measurement SPACE framework developer productivity research Google ↗
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