AI startups are increasingly using revenue figures as a key tool to attract top talent, turning financial milestones into powerful recruiting signals. In a market where competition for skilled engineers, product leaders, and AI researchers is fierce, companies are no longer relying solely on funding rounds or high valuations to stand out. Instead, they’re spotlighting annual recurring revenue (ARR) to prove they’re not just riding a hype wave, but building sustainable, enterprise-grade businesses. Take Sierra, the AI customer support startup co-founded by Bret Taylor and Clay Bavor, which recently hit $100 million in ARR—up from $20 million just a year prior. Despite its strong backing, high-profile founders, and over $600 million raised, the company still feels the need to broadcast this number. Taylor argues that Sierra’s revenue model—based on long-term, upfront contracts with enterprise clients like SoFi, Wayfair, and Rocket Mortgage—makes its ARR more reliable and meaningful than the inflated figures some AI startups use, which are often derived by multiplying a single strong month by 12. Unlike usage-based or pay-as-you-go models that can quickly erode with churn, Sierra’s model mirrors that of established enterprise software companies like Salesforce and ServiceNow. Customers sign 12-month or longer contracts, pay in advance, and have a 30-day grace period to pay after signing. This creates a more predictable and sticky revenue stream, which Taylor says signals durability and trustworthiness—qualities that matter deeply to both investors and job seekers. The message is clear: working at a company with real, contracted revenue from Fortune 1000 and regulated industries is more valuable than joining a startup with flashy demos and volatile user growth. Taylor compares the current AI landscape to the dot-com era, where the real differentiator wasn’t just innovation, but the ability to build a lasting business. “As a candidate, you want to work for the company that’s going to end up being the leader,” he said. This shift is reflected in how other startups are talking about their numbers. Loveable recently announced it doubled its ARR to $200 million in just four months, while Cursor revealed it has passed $1 billion in annualized revenue. These figures are not just financial metrics—they’re recruitment tools, designed to attract talent who want to join companies with proven traction and long-term potential. Sierra’s expansion plans reinforce this ambition. With around 300 employees today, the company is preparing to nearly triple its footprint in San Francisco with a 300,000-square-foot lease in China Basin—among the largest office deals in the city since OpenAI’s move. The expansion signals confidence in growth, particularly in international markets and customer-facing roles. Taylor also sees the future of AI as moving from a fragmented “best-of-breed” phase to a consolidation wave, where only the strongest players survive. Sierra isn’t actively acquiring yet, but it’s positioning itself to be one of the leaders when that moment comes. In today’s AI race, revenue isn’t just a sign of success—it’s a badge of legitimacy. For startups, proving they have real customers and sustainable income is now just as important as raising capital or announcing a new model. In a crowded field, ARR has become the new currency of credibility.