George Sivulka
Showing 1–3 of 3 transcripts.
- a16z37 min
Reasoning Models Are Remaking Professional Services
Hebbia, founded by George, positions itself as an AGI-native platform designed to automate complex, high-stakes financial workflows by leveraging scaling laws and deep research capabilities to process proprietary, unstructured data. The platform delivers quantifiable ROI for buy-side firms by reducing due diligence time from weeks to seconds and enabling analysts to screen 137% more opportunities through pre-built agents and infinite context windows. Looking forward, the company aims to transform private markets into a structured ecosystem similar to the Bloomberg Terminal while driving a broader economic shift where AI agents contribute over 50% of global GDP within a decade.
Carlos Delatorre, CRO @Harness: Why Every Sales Rep Should Do Pipeline Generation | E1251
Carlos Delatorre, Harry Stebbings, George Sivulka
This session outlines a rigorous sales methodology for early-stage companies, emphasizing that founders must personally develop repeatable sales plays and hire only after validating process scalability. The discussion details operational strategies such as mandating pipeline generation for all account executives, utilizing specific weekly rhythms like "Pipeline Generation Tuesdays," and prioritizing innate traits over experience during hiring to reduce attrition. Furthermore, the event provides a framework for accelerating ramp times through structured training and leading-indicator metrics while leveraging AI to enhance productivity and shifting the industry's reputation away from traditional stereotypes.
George Sivulka, Co-Founder & CEO @Hebbia: The Future of Foundation Models | E1250
George Sivulka, Harry Stebbings
George, a former NASA intern turned Stanford PhD dropout, founded Hebbia in 2020 to build AI agents that perform deep financial analysis rather than relying on standard retrieval methods. Supported by investors Peter Thiel and Mike Volpe, he developed the company while living in a closet, focusing on high-stakes use cases like credit agreements to validate enterprise AI value. He projects that a shift toward scaling at inference and orchestrating multiple models will drive $100 trillion in economic value over the next six decades, positioning Hebbia to redefine the agentic application layer.