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AI is radically changing the future of the workplace from redefining jobs to fueling the rise of so-called work slop. Live on stage at the Masters of Scale Summit in San Francisco, Box CEO Aaron Levie, LinkedIns Chief Economic Opportunity Officer Aneesh Raman, and Metas Head of Business AI Clara Shih share their insider perspectives on AI optimism, uncertainty, and navigating this unprecedented era. This is an abridged transcript of an interview from Rapid Response, hosted by the former editor-in-chief of Fast Company Bob Safian and recorded live at the 2025 Masters of Scale Summit in San Francisco. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with todays top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. iFrame Embed: Aneesh, there’s a real debate about the impact of AI on work and some say it will be positive, some say it will be negative. You’ve said it will be spectacular. Why? Raman: I’m at LinkedIn, we are if nothing else, a platform of people. We go where the species goes. So for two years I have thought about human intelligence as my core focus For humans, work has kind of sucked since the industrial age. We have turned ourselves into efficiency machines, whether you’re at the assembly line or sending emails, it’s more, better, faster. More, better, faster… That isn’t who humans are. AI is going to out-efficiency us, robots going to out efficiency us. That’s okay. We became the apex species, not because we were the most efficient, but because we were the most imaginative, the most innovative AI is going to force us finally to broaden our view of human intelligence. I’m pessimistic about our state of being ready for that because it’s entire new systems of education, employment, entrepreneurship, but we’re going to have to fix that and that’s great, I think. Clara, we’ve heard this term that’s become very popular, work slop, that AI-generated work is creating more work. It’s like volume over quality Is work slop just a phase for AI? Is it like a bug that we’re going to fix or is this a feature and something that we’re always going to have to be vigilant about when we’re in a world where so much can be created so easily? Shih: I think there’s always been work slop. I’ve been responsible for some work slop, especially earlier in my career. I think certainly AI makes it easier to create lots of work slop, and so just like any new technology. I can imagine the very first spreadsheets when they were invented, people weren’t sure how to use it. The features probably didn’t include checking the formulas, and so there were probably some really bad, incorrect spreadsheets. The same thing is happening now. Raman: Like any tool, use it. Do not misuse it. Do not overuse it. There’s already lots of research. MIT has great research with brain scans that if you overuse AI, you’ll deplete your ability to grow critical thinking skills. AI helps individuals get started, but if everyone’s using it across a team, sameness creeps in. So it’s all about how you use it. Aaron, you founded Box. You know how important and distinctive a culture can be in an organization. Each company is different. All of our cultures, each one is different. When we add AI agents to our work, do we need to orient them like we do new employees? If we all use off-the-shelf AI, are we going to end up with off-the-shelf culture? Levie: Certainly. And by the way, I’m actually fine with lots of work slop because all I see is lots of files that are going to get generated That’s good for you. Levie: I think everybody here is familiar with context engineering. It’s sort of a simple analogy, which is if you have an employee off the street, super-intelligent person, doesn’t know kind of what job they’re in, they just appeared and you’re like, “Okay, today you’re a lawyer and the next day you’re a marketer and the next day you’re a coder.” That’s kind of what an AI model is. And so you have to give it the context necessary to be able to perform its tasks. And so maybe actually ironically, if anything, you’ll have to get more context than the person would. It’s actually very easy for an employee to pick up the general cultural sort of norms and work practices because they can just look over at one other person and say, “Oh, I see the way that you just collaborated over there.” And so we’re more of a collaborative culture versus we just make really quick decisions and then move forward. An AI agent again doesn’t know, “Did I just join SpaceX or did I join Patagonia?” I’m assuming those are two different ends of the cultural spectrum. So you’re going to have to tell the agent effectively like, “Who are you right now? And here are the norms in our organization, and here is the context about the business process that you’re involved in.” Clara, I talked to one CEO last week who said like he’s being pressured to adopt AI in areas that he’s not sure it’s actually beneficial for the business, but he feels like, “Oh, I’m getting this push from all different parts of the organization, investors, and the board.” How do leaders strike the balance between, “I got to be in this,” versus, “It’s not really showing any measurable impact now yet”? Shih: I see this all the time from various leaders that I meet with. I think it’s first being hands-on and really getting in there and understanding the capabilities because I think with that judgment, with that firsthand experience, only then can leaders really know, “Okay, I want to apply it here but not here.” Another really great success formula is splitting up the team, having people focus on immediate use cases. What can I unlock today that will show me ROI this quarter, next quarter, versus what are the bigger bets where just I see the secular trend and we have to skate to where the puck is going Levie: One pitfall that a lot of existing organizations will fall into, like us included when I walk around and try and talk about what kind of processes we can bring automation to, I think there is this idea that we have this sort of end-state utopian view of AI can do anything and can automate anything. The reality is that if you drop AI into today’s business process, it’s going to actually do very little and you have to actually re-engineer your workflow and you have to re-engineer your process. I think a lot of times, unfortunately, you’ll see people try and drop in AI into a process where then even with thebest automation, you’re going to get a 10% gain or whatnot of that workflow. It’s not world-changing. Levie: It’s not world-changing, but it’s because you didn’t think about re-engineering the workflow for AI. And we thought AI would work how we do. It turns out it might be the case that we have to work how AI does and we have to be actually in service of the agent to make it most productive as opposed to this unfortunate reality where we probably thought it would make us productive. It’s a little terrifying. Your job is to make the AI more productive? Levie: Totally. Well, so there was some offsite 15 years ago where one of our engineering managers told me about the inverted pyramid. His job is to enable all the people below him technically in a hierarchy, but to be as productive as possible. And it was sort of this inversion of like he works for them to make them as effective as possible. And the reality is that that’s kind of what we’re going to be doing with AI agents for quite some time because we’re going to be working to make them effective And if you look at the five and 10 and 20-person startups that are AI-native fully, they don’t have a single business process, that’s basically what they’re doing. They’re working to support agents to be super effective, and that’s just a totally different way to work. Raman: Make them more productive to make you more impactful. Shih: Yeah, help you help me. Raman: I think we have to be affirmatively pro-human. It’s hard to state how radical it is.
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E-Commerce
The U.S. Department of Energy has struck a $1 billion deal with Advanced Micro Systems (AMD) to build two supercomputers that have unprecedented power to supercharge scientific advances ranging from nuclear power to developing cancer treatments. The partnership, first reported by Reuters on Monday, will ensure the U.S. government has the necessary computing power to accommodate enormous amounts of dataand could deliver about three times the AI capacity of current supercomputers. The artificial intelligence-powered supercomputers could be deployed for advancing nuclear power and replicating fusionthe process that fuels the sun and creates massive amounts of energy. Were going to get just massively faster progress using the computation from these AI systems that I believe will have practical pathways to harness fusion energy in the next two or three years, Energy Secretary Chris Wright told Reuters. Shares of AMD rose nearly 1% in midday trading on Monday. The semiconductor makers stock has more than doubled in value this year, and the company recently forged a partnership to supply its chips to OpenAI to build out AI infrastructure. Neither the Department of Energy nor AMD responded immediately to a request for comment from Fast Company. SUPERCOMPUTER TIMELINES The forthcoming supercomputers could be used to further advancements in technologies for defense and national security, including helping the U.S. government to manage its arsenal of nuclear weapons, along with accelerating drug discovery for the treatment of cancers, Wright told Reuters. My hope is, in the next five or eight years, we will turn most cancers, many of which today are ultimate death sentences, into manageable conditions. The first of two supercomputers, Lux, could be up and running within the next six months and will be based on AMDs MI355X artificial intelligence chips and the companys central processing units (CPUs) and networking chips. The supercomputer system is co-developed by AMD, Hewlett Packard Enterprise, Oracle Cloud Infrastructure, and Oak Ridge National Laboratory (ORNL). The timeline for Lux will mark the fastest deployment of this size of supercomputer that AMDs CEO, Lisa Su, has ever seen, she told Reuters. “This is the speed and agility that we wanted to [do] this for the U.S. AI efforts.” A second, even more advanced supercomputer, called Discovery, will have a longer timeline for completion and is expected to be ready for operations sometime in 2029.
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E-Commerce
Rare earth stocks find themselves underground on Monday as Treasury Secretary Scott Bessent said he expects that China and the U.S. will work out a trade deal in the near future. Meanwhile, stock markets largely soared on news of the trade optimism, with the Dow Jones Industrial Average up roughly 0.5%, the S&P 500 up 1%, and the Nasdaq up 1.6% as of midday Monday. Bessent, appearing on CBS Face the Nation Sunday news program, said that he anticipates that China will resume soybean purchases from the U.S., and that there could be an announcement on Thursday when President Trump and Chinese President Xi Jinping meet in South Korea. I’m not going to get ahead of the two leaders who will be meeting in Korea on Thursday, but I can tell you we had a very good two days, he said. “So I would expect that the threat of the 100% [tariff] has gone away, as has the threat of the immediate imposition of the Chinese initiating a worldwide export control regime. Part of those export controls concerns rare earth minerals, which are used in the manufacturing of a wide variety of products, such as vehicles and consumer electronics. And Bessents comments led to some earthquakes in the market on Monday, as rare-earth stocks fell significantly. Shares of MP Materials, for instance, were down more than 9% since the market opened, as of midday Monday. USA Rare Earth Inc., likewise, was down roughly 10%. Notably, MP Materials share price is up more than 312% year-to-date and USA Rare Earth shares are up roughly 85%. So investors are still making out well, despite todays downturn. The issue at the molten core of the rare earth trade is the fact that China controls the vast majority of rare earth mineral production and refining. By some measures, the Chinese control as much as 70% of rare-earth mining, 80% of refining and processing capacity, and more than 90% of the worlds supply. That means those minerals are scarce, which drives up pricesand share prices of companies operating in the space outside of Chinese control. While we dont know yet what kind of trade deal or agreement will surface later this weekor if one will at allBessents signaling that things are heading in a positive direction is whats having an effect on rare-earth stocks today.
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