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.
Logan Kilpatrick offered fresh insights into building the Nano Banana version of Gemini 2.5’s Flash Image model and sketched its evolution roadmap. This sub-second generator costs about four cents per image and runs in AI Studio’s free build tab, where you can customize demo apps. For example, an AI Ads creator auto-places products like the Pixel 10 into subway scenes or magazine spreads with auto-generated slogans; a social-asset remix tool; and a click-to-edit photo editor for tasks like logo removal. Developers are also exploring its API for masked region edits, multi-image merges, time-travel transformations across eras, stylized renders and even five-second videos using CLIP 2.1 Pro.
In related news from Alibaba, Qwen Chat can now read web pages directly—just paste a URL and watch it digest and summarize content instantly. On a different front, Google’s Gemini App rolled out Storybook, enabling subscribers to craft animated group chats and personalized team send-offs.
Switching gears to AI tools, Philipp Schmid published a walkthrough on transforming a single product photo into a complete visual asset library using adjustable prompts in Gemini 2.5 Flash Image Preview. Separately, Jason Zhou is developing Vibe, a coding environment designed for non-engineers, and has invited San Francisco–based AI startups to prototype and provide feedback.
Turning to product strategy, Pawel Huryn lifted the paywall on Hamel Husain’s Mastering AI Evals guide, providing free frameworks and resources to help build robust evaluation systems. Meanwhile, Nuri Janian pointed out pitfalls in the RICE prioritization method, warning that quantitative scores can misalign with stakeholder needs when estimates eclipse real user impact. Teresa Torres also previewed six key takeaways from her first AI venture, Interview Coach AI, covering everything from problem discovery to solution-market fit.
On the industry front, Andrej Karpathy outlined a shift in language model training from large-scale internet text pretraining to supervised fine-tuning with human-crafted conversations. Additionally, Anthropic AI published a threat intelligence report on AI-driven cybercrime, detailing schemes such as North Korea’s fake job offers and AI-generated ransomware. And in infrastructure updates, Sundar Pichai announced a $9 billion investment in Virginia for AI and cloud services, including a new data center in Chesterfield and expansions in Loudoun and Prince William counties.
In related educational developments, Deeplearning.ai unveiled a Neo4j-backed course on agentic knowledge graph construction. The curriculum covers linking document chunks into entities and relationships for precise retrieval, designing an agent team to define graph schemas, and using Google’s Agent Development Kit to extract data from CSV and Markdown and automate graph creation.
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!