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Chris Potts introduces AI coding CPI

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Chris Potts introduces AI coding CPI
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// 1h agoRESEARCH PAPER

Chris Potts introduces AI coding CPI

Stanford researcher Christopher Potts and Moritz Sudhof created a "Consumer Price Index" for AI coding using developer interaction data from the SWE-chat dataset. Examining Anthropic's Opus 4.6 model, they found that engineering output per token dropped by up to 85% in two months, though code survival rates rose from 90% to 95%.

// ANALYSIS

While LLM unit costs are plummeting, tokenflation means developers are actually getting less raw code per token because modern reasoning models use more conversational context and internal thought tokens.

  • **The "Tokenflation" Reality:** Raw volume metrics like PRs, files touched, and lines of code produced per token have dropped by up to 85% in just over two months.
  • **Hedonic Adjustments Matter:** The 5% improvement in code survival rate (from 90% to 95%) is the silver lining, indicating that models are producing more robust, long-lasting code rather than sheer volume.
  • **Agentic Workflows are Expensive:** This index confirms that agentic execution and deep-thinking frameworks will shift developers from buying raw token volume to buying verified outcomes.
// TAGS
tokenflationcpiai-codingswe-chatanthropicopus-4-6llm-costsdeveloper-productivity

DISCOVERED

1h ago

2026-06-08

PUBLISHED

1h ago

2026-06-08

RELEVANCE

8/ 10

AUTHOR

jeremyphoward