Anthropic’s CFO Krishna Rao says more than 90% of the company’s internal code is generated by its agentic AI tool, Claude Code. He adds that the company uses dozens of specialized AI workflows to automate finance and enterprise operations, shrinking tasks that used to take hours—like revenue and compute utilization reporting—into roughly 30 minutes. Even then, AI typically produces 90–95% of outputs before human review, allowing employees to focus on judgment, strategy, and oversight while hiring accelerates.
Enterprises report production AI agent pipelines failing not due to model skill, but because the agent decides it’s “done” too early—sometimes before code is actually compiled. Anthropic’s new Claude Code /goals separates task execution from task evaluation, running a dedicated evaluator model after each step to prevent premature exits using measurable completion conditions like tests and exit codes.
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New figures show Anthropic has pulled ahead of OpenAI in enterprise AI spending, with 34.4% of surveyed companies paying for Anthropic products in April. The jump is attributed mainly to growing demand for Claude Code, Anthropic’s AI coding assistant. The result suggests a faster, tool-driven shift in how businesses are choosing their next AI vendor.
Anthropic says it reached a $30 billion annualized revenue run rate after revenue and usage jumped 80x in the first quarter on an annualized basis. The breakneck pace is straining compute, pushing the company to secure massive GPU capacity, including from SpaceX, while its agentic coding product Claude Code drives enterprise demand at unprecedented speed.
An Anthropic employee wowed wedding guests with an AI-made presentation built using Claude Code. Instead of traditional photos, the groom analyzed over 100,000 messages from 12 years with his girlfriend, mapping everything from “I love you” counts to patterns that emerged at specific times. The data-driven romance became the main event, replacing the usual slideshow format.
Anthropic says reports of “nerfed” Claude Code performance were caused by bugs that degraded the tool’s output. The company has released an update to address the issue and reset users’ rate limits, aiming to restore expected behavior and normalize usage after the malfunction. The fix comes amid growing scrutiny of model performance changes.
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