AI Engineering that Delivers: Blueprint to Impact

This track brings together the team's shipping state‑of‑the‑art systems to unpack how modern AI moves from prototype to production. Across sessions, you’ll see how code-first copilots are built and evaluated (Anthropic), how enterprise research agents ground answers in proprietary knowledge (Glean), and how reinforcement learning optimizes large‑scale marketplaces and ads (Meta). We’ll dive into AI content generation and agent‑based simulation for creative and safety‑aware workflows (Pinterest + Veris AI), personalization with LLMs that balances latency, cost, and relevance (DoorDash), and the emerging Model Context Protocol for interoperable tooling and orchestration (Browserbase). 

Expect concrete patterns for retrieval and data pipelines, multi‑agent design, online/offline evals, guardrails and governance, observability, and continuous improvement loops, so technical leaders can deliver scalable systems that are reliable, compliant, and measurably impactful.


From this track

Session

Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash

Tuesday Nov 18 / 10:35AM PST

In this talk, we’ll walk through how DoorDash is redefining personalization by tightly integrating cutting-edge large language models (LLMs) with deep learning architectures such as Two-Tower Embeddings (TTE) and Multi-Task Multi-Label (MTML) models.

Speaker image - Sudeep Das

Sudeep Das

Head of Machine Learning and Artificial Intelligence, New Business Verticals @DoorDash, Previously Machine Learning Lead @Netflix, 15+ Years in Machine Learning

Speaker image - Pradeep Muthukrishnan

Pradeep Muthukrishnan

Head of Growth for New Business Verticals @DoorDash, Previously Founder & CEO @TrustedFor, 15+ Years in Machine Learning

Session

Deep Research for Enterprise: Unlocking Actionable Intelligence from Complex Enterprise Data with Agentic AI

Tuesday Nov 18 / 11:45AM PST

Deep Research as a consumer product redefined the AI space delivering true impact to many by searching through hundreds of websites, deeply thinking through the content, and generating a comprehensive report.

Speaker image - Vinaya Polamreddi

Vinaya Polamreddi

Staff ML Engineer; Agentic AI @Glean; Previously @Apple, @Meta, and @Stanford

Session

Engineering at AI Speed: Lessons from the First Agentically Accelerated Software Project

Tuesday Nov 18 / 01:35PM PST

Claude Code is the first developer tool built specifically to maximize AI development velocity.

Speaker image - Adam Wolff

Adam Wolff

Engineer and Individual Contributor to Claude Code @Anthropic, Previously @Robinhood, @Facebook

Session

Automating the Web With MCP: Infra That Doesn’t Break

Tuesday Nov 18 / 02:45PM PST

AI agents are only as strong as the infrastructure beneath them. In this talk, we’ll walk through the architecture behind Browserbase’s model context protocol (MCP), built to support stateful browser automation at scale.

Speaker image - Paul Klein

Paul Klein

Founder @Browserbase, previously Director of Self-Service & Engineering Manager @Mux, Co-Founder & CTO @Stream Club, Technical Lead @Twilio Inc.

Session

From Content to Agents: Scaling LLM Post-Training Through Real-World Applications and Simulation

Tuesday Nov 18 / 03:55PM PST

This talk presents a comprehensive journey through modern AI post-training techniques, from Pinterest's production-scale content discovery systems to enterprise agent training through Veris AI’s simulation.

Speaker image - Faye Zhang

Faye Zhang

Staff Software Engineer @Pinterest, Tech Lead on GenAI Search Traffic Projects, Speaker, Expert in AI/ML with a Strong Background in Large Distributed System

Speaker image - Andi Partovi

Andi Partovi

Co-Founder @Veris AI, Making AI Agents World-Ready

Session

Improving Meta Generative Ad Text using Reinforcement Learning

Tuesday Nov 18 / 05:05PM PST

Reinforcement Learning with Performance Feedback (RLPF) unlocks a new way of turning generic GenAI models into customized models fine-tuned for specific tasks. This approach is especially powerful when combined with in-house data and performance metrics.

Speaker image - Alex Nikulkov

Alex Nikulkov

Research Scientist (RL lead for Monetization GenAI) @Meta

Track Host

Faye Zhang

Staff Software Engineer @Pinterest, Tech Lead on GenAI Search Traffic Projects, Speaker, Expert in AI/ML with a Strong Background in Large Distributed System

Faye Zhang is a staff AI engineer and tech lead at Pinterest, where she leads Multimodal AI work for search traffic discovery, driving significant user growth globally. She combines expertise in large-scale distributed systems with cutting-edge NLP and AI Agent research pursuits at Stanford. She also volunteers in AI x genomic science for mRNA sequence analysis with work published at multiple science journals. As a recognized thought leader, Faye regularly shares insights at conferences across San Francisco and Paris.

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