Agentic coding and persistent returns to expertise: How Claude Code is used in practice
AI Summary
Anthropic economic research analyzing ~400,000 privacy-preserving Claude Code sessions from October 2025 to April 2026, finding a stable division of labor (people decide what to build, Claude decides how), rising task value and success rates over time, and that domain expertise — not coding skill — is the strongest predictor of a session succeeding.
Original excerpt
Published June 16, 2026. Building on prior work, Anthropic introduces a framework for studying interactive agentic coding based on a privacy-preserving analysis of ~400,000 Claude Code sessions from between October 2025 and April 2026, evaluating the composition of tasks, human-AI collaboration, and success rates.
Key findings: In a typical session, people make most of the planning decisions (what to do) and Claude makes most of the execution decisions (how to do it). The greater domain expertise a person brings to a session, the more work Claude does per instruction. On coding tasks, every major occupation succeeds — accomplishes what the person set out to do, with verifiable evidence like…
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Anthropic economic research analyzing ~400,000 privacy-preserving Claude Code sessions from October 2025 to April 2026, finding a stable division of labor (people decide what to build, Claude decides how), rising task value and success rates over time, and that domain expertise — not coding skill —…
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This piece is part of the Claude Code vault on Burn 451, covering agentic coding with claude. The original author is attributed at the source link.
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