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Flattening the AI cost curve at scale

Posted Oct 29, 2026 | Views 3
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Amir Haghighat
Co-founder @ Baseten

Amir Haghighat is the co-founder and CTO at Baseten, an AI infrastructure company specializing in inference. Before Baseten, he led engineering teams at Clover Health and Gumroad.

Amir focuses on the hardest layer of AI: turning large models into reliable, performant, and cost-efficient production systems. His work centers on model-serving architecture, optimized batching, autoscaling, and observability, pushing the industry beyond hype metrics toward real system performance.

He holds a BS and MS in Computer Science from the University of California, Irvine (ICS).

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Corinne Riley
Partner @ Greylock

Corinne Riley is a partner at Greylock, where she leads early-stage investments across AI infrastructure and applications.

She has backed companies at the earliest stages that have since become category-defining businesses, including Baseten, Braintrust, Cogent, Fable, and Resolve AI. More recently, she led Greylock’s investment in Altara, along with several companies still in stealth.

Corinne also built Greylock Edge, the firm’s three-month company-building program for founders working from pre-idea through early product-market fit, with flexible financing and hands-on company formation support. Since launching in October 2023, Edge has helped create seven companies, including Cogent Security, Fable Security, Highstock, and SuperMe.

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SUMMARY

The exponential nature of AI spend is top-of-mind for enterprise teams. Every engineer running agentic workflows against frontier APIs adds to a growing bill, and slowing teams down is out of the question.

Amir Haghighat (CTO and Co-founder, Baseten) and Corinne Marie Riley (Partner, Greylock) will get into what it actually means to own your intelligence - building RL environments leveraging your internal data, using sandbox execution to make that loop safe and reproducible, and knowing when post-training is worth it. They’ll also cover how to clear the security, procurement, and talent hurdles that stall adoption at scale.

Attendees will leave knowing what owning their intelligence looks like in practice, and how to get there faster, cheaper, and more securely.

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CONTENT & TRANSCRIPT


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