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    Home»Science & Technology»US Science & Tech»Anthropic’s Cat Wu says that, in the future, AI will anticipate your needs before you know what they are
    US Science & Tech

    Anthropic’s Cat Wu says that, in the future, AI will anticipate your needs before you know what they are

    News DeskBy News DeskMay 13, 2026No Comments5 Mins Read
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    Anthropic's Cat Wu says that, in the future, AI will anticipate your needs before you know what they are
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    With the tech industry singularly focused on AI models, Anthropic is having an exceptionally good year.

    The company may soon pull ahead of its main competitor, as it looks to raise tens of billions of dollars in a funding round that would put its valuation at some $950 billion (OpenAI was valued at $854 billion in its March round), and business customers increasingly express a prefererence for Claude over ChatGPT. A recent report showed Anthropic recently outpaced OpenAI among business customers, quadrupling its market share since May 2025.

    Cat Wu, Anthropic’s head of product for Claude Code and Cowork, has been a key figure in that success. Since joining the company in August 2024, Wu has helped shepherd Claude through a critical phase, leveling it up from a purely informational chatbot to a coding tool and beyond. Wu, who oversees the development of new features, is frequently paired with Boris Cherny, a core member of Anthropic’s technical staff and the creator of Claude Code, leading the pair to be characterized as Anthropic’s “Batman and Robin.”

    Wu sat down with me at last’s week’s second annual Code with Claude conference in San Francisco, where she discussed how she thinks about product strategy, and how she hopes the experience of using Claude will change in the future. 

    This interview has been edited for length and clarity.

    When you’re looking at product strategy, how much of it is reactive to your peers or your competitors? Do you think about that at all?

    The main thing that we design for is staying on the exponential, so I think, across our team, we instill in everyone the lesson that AI will just continue to get better. For us, we just need to stay at this frontier. We don’t think about competitors. I think if you do think about competitors, you end up being, like, perpetually two weeks, or like, a month behind how fast you can execute. And so it’s normally not the best way to stay at the frontier.

    Anthropic released at least six models last year and has already released almost as many this year. Do you expect this pace of development to continue?

    Our hope is that it continues (laughing). I think the models are still improving at a very steady pace, and so we should be able to keep sharing those with our users. I think the deployments might look a bit different—like how we handled Glasswing, but as much as possible, we want this intelligence to benefit as many people as possible, and it has to be handled in a very safe way, which is why we handled Glasswing [in the way that we did].

    [Glasswing is an initiative that Anthropic launched in April that invited a small consortium of partner organizations — including companies like Amazon, Apple, CrowdStrike, and Microsoft — to gain access to its new cybersecurity model, Mythos. Unlike many of Anthropic’s other AI models, Mythos is not being given a general public release. The company has claimed that it fears the model — which is designed to scan codebases for software vulnerabilities — is too powerful, and could be weaponized by bad actors.]

    You said in a previous interview that the future of work is basically staff managing fleets of agents. It seems like that could eventually lead to a situation where the agents are better at the job, or know the job, better than the human.

    I think it is extremely hard to manage agents if you can’t do the job yourself. I think the managers still need to be experts in their domain. It’s a new skill set that a lot of people are going to have to learn, but managing agents is actually very similar to being a manager of people, in the sense that you have to understand, like, why did the agent make this mistake? Did it misinterpret my instruction? Was my request under-specified? You have to have the ability to debug it.

    It does seem like the long term goal is to cut down on team size, though. Because if you have agents doing a job, then you don’t need an intern, right?

    Ideally, I think the idea is that everyone can get a lot more done. I think that, for everyone’s job, there’s always this percentage of it that’s really tedious. For me, it’s responding to emails. I think everyone has this part of their life…So my hope is that it [the AI agents] actually does that, and then everyone has, like, all these cool things that they will want to build [in their spare time].

    What are you guys most excited about in the next six months?

    I think the next big thing is proactivity. Last year we were in this world of synchronous development. Right now, people are shifting to routines, so like automating, for example, responses to customer support tickets. And I think the next step is that Claude understands what you work on, and just sets up some of these automations for you.

    When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

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