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 Qwen announced that its new Qwen3-VL vision-language model is now available on llama.cpp. Teams can run it across CPU, CUDA, Metal, and Vulkan environments, with GGUF-formatted weights provided for model sizes ranging from 2 billion to 235 billion parameters. This makes it possible to experiment locally or in the cloud without custom tooling.
In related developments, DeepAgents kicked off a mini-launch week. Founder Harrison Chase revealed three key additions: a virtual filesystem plugin for agent data storage, a no-code UI that lets anyone build and configure agents in minutes, and the DeepAgents CLI for scripting and automation. Together, these tools give teams multiple ways to prototype and deploy autonomous workflows.
Meanwhile on the tools and applications side, LangChainAI rolled out its OpenAgent Framework for the Open network. Designed for decentralized finance AI and decentralized science use cases, it offers built-in compute verification and rapid agent orchestration—so you can ensure trust and scalability in distributed environments. Additionally, LangChainAI released the Langrepl CLI, a terminal-based interface for assembling LLM agents with persistent conversation memory and seamless integration into LangGraph Studio.
On the product management side, George Nurijanian shared a North Star metrics playbook tailored to various business models. This comprehensive list helps PMs pick the single, most meaningful metric—whether you’re running a marketplace, a subscription service, or a free-to-play platform. Separately, he showcased how a Chime product manager uses Cursor to draft PRDs, consolidate stakeholder feedback, and automate repetitive tasks across Confluence, Notion, and Jira. By centralizing all workflows in one interface, this approach eliminates context switching and speeds up delivery.
Across the industry, Aakash Gupta challenged the oft-cited 9 percent adoption rate of AI in enterprises. His analysis shows that 44 percent of large organizations are now using AI in at least one business unit, signaling a major shift in corporate priorities. In other news, Aravind Srinivas confirmed that the Perplexity Assistant “actually works,” highlighting its edge in delivering reliable answers and setting a new bar for AI assistants.
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!