Claude Code's product lead talks usage limits, transparency, and the "lean harness"
SAN FRANCISCO—Amid an ever-expanding array of surfaces, growing demand for tokens and compute, and a rapidly evolving user base, Anthropic doesn't have a long-term road map for Claude Code. However, it's betting that such a plan would be rendered moot by improvements in model capabilities and new signals from developers on how best to use it. That's the takeaway from a 30-minute conversation Ars had with Cat Wu, Anthropic's head of product for Claude Code. Last week, in a three-level car rental parking garage meticulously converted into an event space in downtown San Francisco, Anthropic put on its second annual Code with Claude developer conference. As previously reported, the single-day event included a keynote introducing new features for Managed Agents and announcing a compute deal with SpaceX . That compute deal was accompanied by a doubling of usage limits for Claude Code users on the company's Pro and Max plans—a response to a lot of user frustration about a compute crunch, especially in recent weeks. Read full article Comments
SAN FRANCISCO—Amid an ever-expanding array of surfaces, growing demand for tokens and compute, and a rapidly evolving user base, Anthropic doesn't have a long-term road map for Claude Code. However, it's betting that such a plan would be rendered moot by improvements in model capabilities and new signals from developers on how best to use it. That's the takeaway from a 30-minute conversation Ars had with Cat Wu, Anthropic's head of product for Claude Code.
“We have no grand plan,” says Anthropic’s Cat Wu—but that’s by design.
Anthropic’s products—especially Claude Code, its tool for agentic software development—have seen runaway popularity. “We tried to plan very well for a world of 10x growth per year,” Anthropic CEO Dario Amodei said on stage at the conference. “And yet we saw 80x, and so that is the reason we have had difficulties with compute.”
User growth was accompanied by a shift in how people used the company’s models, away from simple chat interfaces to complex, multi-agent workflows that are many times more demanding.
