Over the past two years, Generative AI has dominated headlines.
ChatGPT can write emails.
Claude can summarize documents.
LLMs can answer questions, generate code, and even perform research.
Over the past two years, Generative AI has dominated headlines.
ChatGPT can write emails.
Claude can summarize documents.
LLMs can answer questions, generate code, and even perform research.
Over the past two years, artificial intelligence has rapidly entered the world of data and analytics. Large language models can now write SQL, explain trends, generate dashboards, and summarize reports in seconds. Because of this, a common question is starting to appear in data teams and executive meetings:
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As large language models (LLMs) move from demos into production systems, one question comes up quickly:
Can we A/B test an LLM like we test product features?
For teams coming from product analytics or growth, the instinct is straightforward: