BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Ainave//Events//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
UID:qconnewyork.com
DTSTAMP:20261028T073807Z
DTSTART;VALUE=DATE:20261215
DTEND;VALUE=DATE:20261217
SUMMARY:QCon AI New York 2026
DESCRIPTION:### Overview\nQCon AI New York 2026 is a two-day\, in-person AI engineering conference focused on the practical challenges of running AI systems in production. Senior engineers and practitioners share lessons from systems they build and operate\, including what worked\, what did not\, and the trade-offs involved. The event is intended for senior software engineers\, software architects\, Staff+ engineers\, ML and MLOps engineers\, platform and security engineers\, and engineering leaders responsible for production AI.\n\nThe conference takes place December 15–16\, 2026\, at The Westin Jersey City Newport\, 479 Washington Boulevard\, Jersey City\, New Jersey. The venue is one PATH stop from Lower Manhattan. QCon AI is organized by C4Media\, the team behind InfoQ and QCon.\n\n### Program\nThe program addresses six areas: agent architecture and authority\; operating agents in production\; evaluation and continuous improvement\; context and model serving\; AI-assisted software engineering\; and engineering leadership and adoption.\n\nFeatured sessions include Nancy Wang of 1Password’s keynote\, “When Software Becomes a User: Identity and Authorization for Agents in Production\,” on defining what agents may do and under whose authority. Pratik Agarwal of Figma will discuss provisioning and securing production agents\, including warm pools and availability improvements. Ronak Nathani of LinkedIn will explain the skills\, tools\, and server-side guardrails used by LinkedIn’s Kubernetes operations agent across more than 500\,000 nodes and 5 million pods.\n\nFabio Flores of DoorDash will cover the evaluation loop behind the company’s agentic ordering system\, including an LLM judge calibrated against human reviewers. Fan Yang and Rajat Shah of Netflix will discuss a shared platform serving machine-learning and generative-AI models. Min Chen of LinkedIn will present an approach to high-signal AI code review at scale\, while Liz Fong-Jones of Honeycomb will reflect on the company’s initiative to increase engineering output while maintaining quality.\n\nOther listed speakers and contributors include Victor Dibia\, Nathen Harvey\, Joey Wang\, Diego Iruretagoyena\, and Clémence Burnichon. The program is selected by a committee of working senior engineers chaired by Hien Luu\, with Faye Zhang and Wes Reisz among its members. The committee invites speakers based on production experience and aims to keep the program vendor-neutral\, with sponsored talks separate from the editorial program. The full program is scheduled to be published by early November.\n\n### Format and attendance\nThe event features talks and keynotes\, opportunities to ask speakers questions and connect with peers\, attendee socials\, lunch and coffee breaks\, and an exhibitor area. Tickets also include on-demand access to most presentation recordings and slides for 12 months\, beginning four weeks after the conference. Team discounts are available for groups of three or more\, and QCon alumni receive a discount. Registration fees are non-refundable\, but tickets may be transferred to a colleague for free until December 11\, 2026.\n\n### Practical details\nThe venue is inside The Westin Jersey City Newport\, and accommodation options are available through the event’s hotel information. The conference is designed for practitioners moving AI work beyond prototypes\, with sessions on agent permissions\, evaluations\, inference costs\, model serving\, code review\, and organizational practices.\nhttps://qconnewyork.com?ref=ainave
LOCATION:New York\, United States\, US
URL;VALUE=URI:https://qconnewyork.com?ref=ainave
END:VEVENT
END:VCALENDAR