TLDR Tech / Data
How Anthropic enables self-service data analytics with Claude
Anthropic argues that accurate self-service analytics with LLMs is mostly a context, governance, and verification problem, not a SQL generation problem: teams need canonical datasets, strong metadata, semantic-layer-first workflows, maintained skills, and curated sources of truth. Their biggest gains came from reducing ambiguity, preventing staleness, improving retrieval, and validating continuously through offline evals, ablations, provenance, and correction loops.
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