Google DeepMind’s Tulsee Doshi says AI’s next phase depends on user trust

Welcome to AI Decoded, Fast Company’s weekly newsletter that breaks down the most important news in the world of AI. I’m Mark Sullivan, a senior writer at Fast Company, covering emerging tech, AI, and tech policy. This week, I’m focusing on the research and product approach behind Google’s array of new AI products and features, announced this week. I also look at a major recruiting coup at Anthropic, and at some new numbers about small business’s adoption of artificial intelligence. Sign up to receive this newsletter every week via email here. And if you have comments on this issue and/or ideas for future ones, drop me a line at sullivan@fastcompany.com, and follow me on X @thesullivan. An interview with Google DeepMind product VP Tulsee Doshi Google announced a slew of new and updated AI products and features at its I/O developer conference this week, including personal AI agents, code generators, search tools, and a new “world model” for generating physically accurate video. Much of it runs on the company’s latest Gemini 3.5 models, developed inside Google DeepMind. We spoke with DeepMind’s product VP, Tulsee Doshi, about the thinking behind their development and application. What does the tension between safety and product quality look like at DeepMind here in mid-2026? You’re evaluating not just for traditional harms, but you’re now evaluating for things like sycophancy. You’re evaluating for things like agent safety and bringing that forward, and then you’re building the guard rails around the product experience to make sure that you have the right verifications in place. There’s always a trade-off between blank response rate—not responding to a user because you maybe don’t want to answer about a particular topic—[and] answering in a nuanced way, and then answering in a way that maybe goes too far. That’s always the spectrum that we’re trying to find the right balance on. Personally, I feel assured by an age