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Together AI’s CEO flips the RTO script: employees “home from work”

Post-COVID AI startups run on high-trust, in-person cultures where founders say they never enforced return-to-office.

ByAbdullah Al-OtaibiBusiness Desk, The Executives Brief
·4 min read
Together AI’s CEO flips the RTO script: employees “home from work”
Executive summary

Together AI CEO Vipul Ved Prakash says his cloud compute startup has never enforced return-to-work policies, and employees often prefer coming in. For AI founders and boards, the implication is clear: talent incentives, innovation speed, and customer proximity can make remote norms harder to sustain.

When asked about return-to-office, Together AI CEO Vipul Ved Prakash’s answer was basically a mic drop. “What is an RTO?” he told Business Insider, explaining that his team generally “like[s] to come in” and that “We’ve never enforced it.” In other words, instead of the post-pandemic battle founders started waging against remote work, at least some AI startups are running the opposite play: high-trust cultures that treat the office as the default.

That “home from work” rhythm is more than a quirky slogan. Nicholas Bloom, an economics professor at Stanford University, told Business Insider the age demographics and personal stake many startup employees have can create a mode that is “almost entirely in-person” and “100% work focused.” Bloom framed it with a startling incentive math: for “a single 23-year-old with equity worth $20 million,” it can make sense to work “100 hours a week,” in the office. “They don’t work from home, they home from work,” he said. The stakes for executives are obvious: if your company’s product cycle and talent leverage depend on in-person cohesion, the usual remote playbook might not just fail, it might quietly undermine speed and buy-in.

Zoom out and the pattern starts to make sense. Business Insider reports that founders and workplace experts describe post-pandemic AI startups operating in a high-trust environment with tight-knit cultures that demand in-person work. The reason is partly human. In many traditional corporations, return-to-office mandates are attempts to impose structure at scale. In these AI startups, the argument is that culture already supplies the structure: small teams, dense collaboration, and a sense of shared momentum.

Arvind Jain, founder and CEO of Glean, an enterprise AI for productivity company, said he “was not eager” to bring his team back because “finding an office is a hassle,” even while acknowledging that everyone wanted to return to the original mode of working when the company first started in 2019, right before the pandemic lockdowns. Jain described the early pandemic period as a knowledge gap: “We just simply didn’t know how to work from home because everybody was in this one small room.” Before remote, the team could sit next to each other and brainstorm what to build, and Jain said that became “very, very hard” once they were dispersed.

Over time, Jain said he learned to enjoy remote work and got to spend time with family. But the team’s incentives did not line up with permanent distance. He described the emotional and social glue as the difference: “there’s this startup spirit, and it’s only 10, 15 people, and we want to be with each other.” As Glean grew, it moved into a larger office space and designated Thursday as its work-from-home day, a compromise that still keeps the core culture anchored in being together.

Spiros Xanthos, founder and CEO of Resolve AI, which builds multi-agent AI systems, echoed the “no enforcement needed” theme with a tighter operational example. He said the company has a “very strong culture” of in-person work and has never had to ask anyone to be in the office. Resolve AI has a “fairly big office now,” and Xanthos said the company holds meals on-site, including breakfast, lunch, and dinner. He also described an offsite dynamic designed to knit teams together across geographies: since founding in early 2024, he brings colleagues based in New York to the Bay Area for offsite retreats so people “could get to know each other better.”

The non-obvious part is why this matters specifically for AI. Xanthos argued that solving “very, very hard problems” at the frontier requires constant experimentation, and that experimentation depends on “very high trust” and psychological safety, so people can innovate “bottom up” without waiting for instructions. Richard Florida, an urban studies theorist and professor at the University of Toronto, added a broader industry mechanism: innovators have to be close to end users because end users are part of the innovation system. In Florida’s framing, it’s not just that the technology is interesting; it’s what teams learn through interaction with customers and clients that makes the work more location-dependent.

So the next time a leader hears the phrase “RTO,” these founders would likely treat it like the wrong question. The Business Insider report ends with that exact implication: don’t ask how their RTO is going, they’re probably too busy figuring out how to squeeze everyone into the office. For executives, investors, and operators evaluating AI companies, the second-order takeaway is that workplace policy is not only a benefits issue. It is a product and learning system. In a world where experimentation, customer feedback loops, and psychological safety are treated as prerequisites for innovation, an in-person culture can become the mechanism that compounds performance, even if it looks counterintuitive in a market trained on remote-first normalization.

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