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 today’s agenda, we’ll run through product launches and agent updates, explore new tools for UI composition, dive into PM strategies and industry moves, and wrap up with a hands-on demo from Figma workflow expert AI Jason.
First up, in AI product launches, NanoBanana is now available in the Gemini API free tier under “gemini-2.5-flash-image-preview” for the weekend, announced by Logan Kilpatrick. In related developments, LangChain AI released DeepMCPAgent, a dynamic tool for MCP discovery and agent development built with LangChain and LangGraph, streamlining integration over HTTP streaming and server-sent events with support for major large language models. Another rollout from LangChain AI introduces DeepAgents and Camino AI, location-aware agents that fuse real-time location data with web search to boost spatial research and reasoning capabilities.
Meanwhile on the tools front, Jason Zhou highlighted Shadcn MCP, which lets context engineers search for relevant UI components, retrieve example usage, and auto-import directly from component registries. He also pointed to Framelink Figma MCP’s latest enhancements: beyond downloading Figma’s structure, it now pulls SVG and image assets, significantly improving output quality—especially when you combine it with Shadcn MCP.
Building on that, AI Jason demonstrated how open-source Figma MCP and chassis MCP tools in Cursor or Cloud Code can transform Figma designs into pixel-perfect React UI code. He showed that Figma MCP exports images and SVG assets and can generate a fully pixel-perfect landing page section from a Figma selection in just two prompts. Installation only requires adding the MCP to your environment and supplying a Figma personal access token with read permissions. The chassis MCP server then connects to registries like PL UI, Animate UI, and Chat UI, listing available components and injecting import commands with sample code for tables, badges, and text editors.
Shifting to product management strategies, George Nurijanian shared a four-part PRD framework he wishes he’d had on day one to balance speed and quality when crafting requirement documents. He also recommended Microsoft’s OKR cheat sheet to help teams align objectives and key results. On a different front, Claire Vo contrasted B2B product tiers that set aspirational standards and genuinely help users versus those that impose extra work, underscoring the importance of aligning features with real user workflows.
In industry news, Deep Learning AI reported that using an AI interviewer in 67,000 entry-level customer service interviews led to a 12 percent increase in job offers, acceptances, and retention compared to human recruiters. Separately, Aravind Srinivas noted that Perplexity now includes institutional stockholder data, with details on politicians and insider trading set to arrive soon, giving teams new ways to source investor insights.
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!