Kais Khimji has built much of his career in venture investing, with six years serving as a partner at the renowned firm Sequoia Capital. Similar to other former Sequoia partners—such as David Velez, founder of Brazilian digital bank Nubank—Khimji (pictured left) has long harbored ambitions of launching his own startup. This Thursday, he revealed he has resurrected a concept first developed during his time as a Harvard student roughly a decade ago, transforming it into the AI-powered calendar scheduling company Blockit. In a strong show of support, his former employer Sequoia led the company’s $5 million seed funding round.

“Blockit has a chance to become a $1Bn+ revenue business, and Kais will make sure it gets there,” wrote Pat Grady, Sequoia’s general partner and co-steward who led the investment, in a blog post. While numerous startups have previously attempted to automate scheduling, Khimji believes recent advances in large language models enable Blockit’s AI agents to manage scheduling more seamlessly and efficiently than earlier solutions, including now-defunct companies like Clara Labs and x.ai.

Unlike current category leader Calendly—last valued at $3 billion and reliant on users sharing links to coordinate availability—Blockit is wagering that its AI agents can master the nuanced back-and-forth required to handle the entire scheduling process autonomously. Together with co-founder John Hahn, whose background includes work on calendar products such as Timeful, Google Calendar, and Clockwise, Khimji is building what he describes as an AI social network for people’s time.

“It always felt very odd. I have a time database—my calendar,” Khimji remarked, noting that Blockit aims to finally bridge this disconnect. When two users need to schedule a meeting, their respective AI agents communicate directly to negotiate a time, completely eliminating the typical email chain. Users can activate the Blockit agent by copying it on an email or messaging it in Slack about a proposed meeting. The bot then handles the logistics, finding a mutually convenient time and location that aligns with each participant’s preferences.

Khimji explained that Blockit can operate as smoothly as a human executive assistant. Users simply provide the system with specific instructions regarding their preferences, such as which meetings are fixed and which can be moved based on daily demands. “Sometimes my calendar is crazy, so I need to skip lunch, and the agent needs to know that it’s okay to skip lunch,” he said. The system can even be trained to prioritize meetings based on cues like email tone—for instance, giving higher priority to a request signed “Best regards” over one ending with “Cheers.”

By learning user preferences, Blockit appears to tap into what Foundation Capital partners Jaya Gupta and Ashu Garg term “context graphs.” In a widely circulated essay, the investors outlined a multi-billion-dollar opportunity for AI agents to capture the underlying rationale behind business decisions—logic that previously resided only in a person’s mind.

Already, Blockit is being used by more than 200 companies, including AI startup Together.ai, recently acquired fintech firm Brex, robotics company Rogo, and venture firms a16z, Accel, and Index. The app is free to use for the first 30 days. After that, individual users pay $1,000 annually, while a team license supporting multiple users costs $5,000 per year, according to Khimji.