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Ravi Gupta

Showing 1–3 of 3 transcripts.

  1. Sequoia Capital51 min

    Josh Woodward: Google Labs is Rapidly Building AI Products from 0-to-1

    Josh Woodward, Ravi Gupta, Sonya Huang

    Google Labs operates as an autonomous unit dedicated to rapidly prototyping frontier AI products, prioritizing market validation over immediate technological perfection. Key initiatives include Mariner, a computer-use agent currently targeting enterprise automation, alongside Veo, a generative video model solving physics constraints while shifting industry models toward pay-per-output. The organization accelerates innovation by blending veteran engineering with diverse creative talent to launch ideas within 50 to 100 days, ultimately aiming to replace passive consumption with steerable, asset-driven user experiences.

  2. Sequoia Capital39 min

    Using AI to Build “Self-Driving Money” ft Ramp CEO Eric Glyman

    Eric Glyman, Ravi Gupta, Sonya Huang

    Ramp CEO Eric Gleiman champions a "zero-touch automation" strategy that utilizes large language models to execute invisible financial tasks, allowing over 25,000 companies to automate expense reporting and achieve average annual savings of 5%. This approach replaces traditional chatbot interfaces with self-driving money systems that automatically classify vendors and complete reports, marking a shift from routine data entry to high-value strategic work for finance leaders. By prioritizing enduring customer pains over temporary tech trends, the company positions itself to disrupt legacy financial institutions through non-bank innovation that mimics the operational efficiency of "self-driving" transformations in other industries.

  3. Sequoia Capital1h 13m

    Sierra co-founder Clay Bavor on Making Customer-Facing AI Agents Delightful

    Clay Bavor, Ravi Gupta, Pat Grady, Brett Taylor, Karthik Narasimhan, Robbie

    Former Google leader Clay Bavore and Brett Taylor founded Sierra in late 2022 to deploy proprietary AgentOS-branded AI agents that replace traditional navigation with natural language interactions for major brands like Weight Watchers and Sonos. The company addresses specific large language model limitations, such as hallucinations and data silos, by utilizing supervisor agents and a declarative SDK to achieve over 70% autonomous resolution rates for complex customer tasks. Sierra's unique resolution-based pricing model and proprietary TAU Bench benchmark underscore a strategic shift toward industrial-grade AI that prioritizes factual accuracy and task reliability over raw model size.