Google's VaultGemma: First Major AI Model Built with Mathematical Privacy Guarantees

Welcome to GenAI PM Daily, your daily dose of AI product management insights. I’m your AI host, and today we’re diving into the most important developments shaping the future of AI product management. On the product front, Alibaba’s Qwen team rolled out Qwen Code versions 0.0.10 and 0.0.11, bringing a suite of UX and productivity enhancements. You’ll now find Subagents for smarter task decomposition, a Todo Write tool for tracking action items, a “Welcome Back” summary when reopening projects, and a customizable cache strategy to balance speed and resource use. In related moves, the Qwen3-Next-80B-A3B model is now available in AnyCoder, broadening access to an 80-billion-parameter powerhouse for developers everywhere. In other product news, Google’s Jeff Dean introduced VaultGemma—an open language model trained from scratch with differential privacy. His detailed blog post dives into scaling laws for private models, making this a go-to reference for teams building confidential AI systems. Meanwhile on the tools side, Lenny Rachitsky showcased how to prototype a life-changing GetLindy AI agent in just ten minutes, demonstrating frictionless agent-driven workflows. Additionally, Vercel CEO Guillermo Rauch announced plans to open source public evaluations of Next.js and other open source projects, boosting transparency around LLM performance in code generation. Shifting to product management strategies, Lenny Rachitsky shared leadership lessons inspired by Ben Horowitz, urging PMs to build psychological resilience for tough trade-offs and to celebrate incremental wins. Complementing that, Phil Schmid distilled key principles from Anthropic’s blog, emphasizing a single schedule_event call to consolidate workflows on MCP servers and streamline agent tooling. On a different front, Madhu Guru warned against transplanting mobile-era tactics into AI—he argues that rapidly shifting AI capabilities demand fresh patterns, not old playbooks. In the broader AI landscape, DeepMind’s Demis Hassabis highlighted progress at Isomorphic Labs, where teams are designing novel drug candidates for challenging targets. Separately, Anthropic AI emphasized collaboration with the U.S. Center for AI Standards and Innovation and the U.K. AI Security Institute to tighten model deployment safeguards. Finally, DeepLearning.AI shared Andrew Ng’s insights on Coursera’s shift toward skills-based education, the rollout of new AI-driven learning tools, a renewed focus on chatbot child safety, and industry debates over search index sharing. That’s a wrap on today’s GenAI PM Daily. Keep building the future of AI products, and I’ll catch you tomorrow with more insights. Until then, stay curious!