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Research Review

A review series covering new papers and articles in AI and agent systems. Each review verifies claims against the original tables and figures, assesses reliability including conflicts of interest, and closes with practical takeaways — answering "can we trust this, and what should we change?" rather than just summarizing. Published daily, automatically.

· NBER Working Paper

How Real Are AI Coding Productivity Gains? A Review of NBER w35275

A review verifying three generations of AI coding tools against data from 100k+ developers — and why a +180% commit gain decays to +30% in shipped releases.

  • Marginal and cumulative effects reconcile exactly across all six production layers
  • Only Claude Code (+29.2%) translated into releases — the pipeline, not the tool, is the bottleneck
  • Full reliability assessment: conflicts of interest, contradicting RCT evidence, coverage limits
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