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%.
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.
DISCOVERED
1h ago
2026-06-08
PUBLISHED
1h ago
2026-06-08
RELEVANCE
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jeremyphoward