Using Claude to assess the survey responses, we rated the extent of people’s self-reported productivity gains from AI on a 1–7 scale, where 1 is “less productive,” 2 is “no change,” and each subsequent level denotes a larger gain. Responses that scored 7 included testimonials like, “It used to take months to make the website I [made] in 4-5 days”; Claude gave a 5 to statements like, “What might have taken four hours was accomplished in half the time,” and a 2 to ones like, “Personally, I had AI help me fix code on a website. But it took multiple passes to get the result I was after.”3 Overall,
What 81,000 people told us about the economics of AIEconomic Research What 81,000 people told us about the economics of AI Apr 22, 2026 Read the PDF Key findings: Our recent survey of 81,000 Claude users shows that people who work in roles that are more exposed to AI have more concerns about AI-driven job displacement. …
Economic Research Labor market impacts of AI: A new measure and early evidence Mar 5, 2026 Read in PDF Key findings We introduce a new measure of AI displacement risk, observed exposure , that combines theoretical LLM capability and real-world usage data, weighting automated rather than augmentativ… …
Interpretability A “diff” tool for AI: Finding behavioral differences in new models Mar 13, 2026 Read the paper Every time a new AI model is released, its developers run a suite of evaluations to measure its performance and safety. …
… Compounding these concerns is the fact that models appear able to use the tools and environments available to them in unexpected ways, as we saw when Claude used our REPL-based search tool to decrypt answers, or when retailers’ persistent links became a way for agents to unintentionally maintain st… …
… Evaluated against leading AI models through our proprietary benchmarking solution, the biggest gains showed up where they matter most: reasoning depth, structured problem-framing, and complex technical work. …
… Of course, when reviewing AI-authored patches, we recommend that maintainers apply the same scrutiny they’d apply to any other patch created by an external author. Zooming out to the process of submitting bugs and patches: we know that maintainers are underwater. …
… Second, Claude's Constitution , which directly shapes how our models are trained, reinforces a similar instinct, favoring “raising concerns, seeking clarification, or declining to proceed” over acting on assumptions. Our research on agent use gives a sense of the impact of this training. …
… This process is very slow, taking around 50 years to disperse fully.” 4 With our bottom-up analysis of 1P API traffic we see Claude used to "Generate personalized B2B cold sales emails" 0.47% , "Analyze emails and draft replies for business correspondence" 0.28% , "Build and maintain invoice proces… …
… Paired with our Public Benefit Corporation status, the LTBT helps to align our corporate governance with our mission of developing and maintaining advanced AI for the long-term benefit of humanity. …
… When we initially put the brain in a container, it meant that many brains required as many containers. For each brain, no inference could happen until that container was provisioned; every session paid the full container setup cost up front. …
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