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.
In product launches, Google’s Logan Kilpatrick announced that the URL Context tool is now production-ready in the Gemini API, letting models process webpages, PDFs, and images directly via URL with token-based pricing at scale. Meanwhile, Alibaba’s Qwen team rolled out Qwen-Image-Edit, a 20-billion-parameter model that performs precise bilingual text editing in images, preserving style and supporting both semantic and appearance-level edits. Additionally, Sundar Pichai revealed that Flow by Google has generated 100 million videos since its May debut, and Ultra subscribers now receive double the AI credits.
In related developments, Philipp Schmid confirmed that Context URL is generally available in the Gemini API, enabling a single request to ingest websites, PDFs, JSON files, and images. Separately, Perplexity’s finance dashboard now offers live earnings call transcriptions and scheduling for Indian equity markets. On a different front, the LangChain team released Deep Agents for JavaScript, facilitating complex, long-horizon workflows through chain-of-thought reasoning and adaptive tool orchestration.
On the creative side, a recent episode of the How I AI Podcast demonstrated how to use Veo 3 for AI-generated music videos, recreating a Tiny Desk–style concert for Notorious B.I.G. Guests Claire Vo and Anish Acharya walked through a full workflow: prompt engineering with GPT40, video generation with V3, two-stem separation using Demox in Adobe Audition, lip-sync animation via Hedra, and final assembly in Capwing. They also showcased building a Google AI Studio app with Gemini Flash 1.5 that catalogs books from a flip-through video by extracting titles and authors automatically.
Turning to product management strategies, Rowan Cheung shared a role-by-role AI fluency framework to guide hiring at AI-first startups, highlighting acceptable versus exceptional skill levels. In other news, Shreyas Doshi argued that early-stage products benefit more from non-metric goals like “ship X” or “do Y” instead of rigid KPIs, fostering better judgment. Aakash Gupta also weighed in on writing PRDs in the AI era, offering guidelines to craft effective requirement documents amidst rapid AI-driven prototyping.
Looking at industry trends, Arav Srinivas asked the community to weigh in on the best AI releases of the past month, sparking lively discussion. Andrew Ng’s DeepLearningAI released an AI career roadmap eBook covering resume crafting, interview preparation, and overcoming imposter syndrome. Finally, Clement Delangue pointed out that open-world models and 250-million-parameter variants are trending on Hugging Face, indicating a shift beyond traditional large language models.
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!