Designing Multimodal Collaborative Agents for Next-Gen Commerce
Nidhi Kaushik Vyas
- When
- Thursday, July 210:45 AM – 11:05 AM · 20 min
- Where
- Track 2San Francisco, CA · imported from ai.engineer's public schedule feed
About this session
Today's commerce agents wait to be told what to look for. But most users live by a different rule: "I don't know what I want — I'll know it when I see it". If agentic commerce is ever going to cross the chasm, these systems need to stop waiting and start co-shopping. The future of commerce belongs to agentic collaborators that offer a white-glove, personal shopper experience - entirely absorbing the cognitive burden of product discovery, deep research, and validation. Rather than requiring shoppers to input exact search terms or define clear objectives, modern shopping systems will seamlessly guide them from a rough idea to the ideal product. By leveraging multimodal capabilities, these assistants can interpret abstract aesthetic "vibes" to understand user preferences, generate visual references to clarify questions, and enable a highly immersive try-before-you-buy experience to validate products, keeping the user aligned and visually grounded throughout the process. This talk will explore how advanced systems like Gemini work alongside users to clarify their preferences during the discovery process, co-navigate fluidly generated product categories, leverage individual context to filter choices, and produce interactive side-by-side comparisons tailored to the buyer's key priorities. The session will also cover robust auto-rater frameworks and how to design evals for high-agency execution. Attendees building conversational agents, managing complex product data graphs, or creating next-generation multimodal agentic interfaces will gain practical frameworks and insights to deliver highly personalized experiences at scale.
Speaker
Product, Google DeepMind
AI product leader who turns frontier research into products people and companies actually use. Background in multimodal generative systems, I've helped launch high-impact products using multimodal Gemini. Previously, machine learning researcher at Apple, and have contributed to research breakthroughs, as well as scalable, trusted, user-centered experiences.
More in Agentic Commerce
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- Building safe payment infrastructure for machine-to-machine commerceThursday, July 2 · 10:45 AM – 11:05 AM · Leadership 1
- Why Your AI Agent Needs a Wallet: Agentic commerce on Arc with USDC and NanopaymentsThursday, July 2 · 11:10 AM – 11:30 AM · Track 2
- When AI Agents Pay and Sellers Monetize: Building x402 Apps for Agentic Commerce on AWSThursday, July 2 · 11:40 AM – 12:00 PM · Track 2
- x402 isn’t good (yet)Thursday, July 2 · 12:05 PM – 12:25 PM · Track 2
For developers: this programme is open data — JSON, iCal, schedule XML and an MCP endpoint.Show endpointsHide
- JSONEvery published session and speaker, in one request./aie-worldsfair-2026-import/feed.json
- iCalSubscribe in Google, Apple or Outlook Calendar./aie-worldsfair-2026-import/feed.ics
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