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From Models to Production:
Scaling AI in a Multi-Model World
Join a curated group of C-suite and VP-level leaders building and scaling AI, across AI platforms, infrastructure, engineering, and product, for a candid roundtable over an elevated dinner.
Expect actionable insights, meaningful conversations, and an opportunity to connect with industry peers.
Oct 1st, 2026, 6:30 PM PDT - Palo Alto, CA
Hosted by
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Event Details
Who's Invited
This invite-only dinner is designed as a candid, peer-to-peer conversation rather than a traditional panel or presentation.
With a small group of senior AI and technology leaders around the table, the evening will create space to compare real-world experiences, challenges, and approaches to scaling AI, from experimentation and model selection through inference and production.
Come prepared to share perspectives, learn from peers navigating similar decisions, and explore how the AI landscape is evolving as organizations move from individual models to increasingly complex, multi-model environments.
This invite-only roundtable is designed for senior leaders building, scaling, and investing in AI, including:
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CEOs, CTOs, CIOs, and Chief AI / Chief Data & AI Officers
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Chief Product and Chief Business Officers at AI-native companies
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VPs and Heads of Generative AI, AI Applications, AI Product, and Data Science
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Leaders of AI / ML Infrastructure, AI Platform, and Cloud Infrastructure
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VP- and Director-level operators and investors navigating the AI stack
Event Agenda
Oct 1st 2026 at 6:30 PM PDT
6:30 PM – 7:15 PM: Networking Session with Welcome Drinks
7:15 PM – 7:30 PM: Introductions, Opening Remarks
7:30 PM – 8:15 PM: Starters, Facilitated Discussion
8:15 PM – 9:00 PM: Main Course, Closing Remarks
9:00 PM – 9:30 PM: Extended Networking with Open Bar
Venue
The Sea by Alexander's Steakhouse
Discussion Points
From Models to Production: Scaling AI in a Multi-Model World
The AI landscape is rapidly moving beyond model experimentation toward production applications, agents, and AI-native products. As organizations gain access to an expanding range of open-source, proprietary, and specialized models, leaders are increasingly making decisions around model selection, inference economics, performance, and how much of the AI stack they need to manage themselves.
This closed-door discussion will bring together AI leaders and investors to explore how organizations are navigating this transition — from choosing the right models to managing cost and performance at scale, and what it will take to make AI more accessible, flexible, and economically viable in production.
As model capabilities and options expand, how are you deciding which models to use for different workloads, and how do performance, cost, latency, and flexibility factor into those decisions?
As AI moves into production, where are you seeing the biggest challenges around inference economics, model access, and scaling AI applications, and what are you doing to address them?
Looking ahead 18 months, what changes do you expect in how AI applications are built and deployed, and what capabilities will become increasingly important for companies trying to scale AI efficiently?
Registration
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Our events are entirely pitch free, and we prioritize authentic conversations over sales tactics, providing industry leaders with a space to connect, collaborate and share insights freely.
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