Building an AI Life Co-Pilot with Claude Code

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. First up, Phil Schmid announced that Google AI Studio’s Gemini API for the Hackathon has boosted Nano Banana’s free rate limit to 200 calls per day, giving developers more room to prototype without hitting caps. In related news, Pawel Huryn published a free guide on building AI product strategy and leading AI initiatives, and he’s also launched the Maven AI PM Strategy Course, currently ranked number one on that platform. On the tooling front, LangChain AI rolled out a technical series showing how to build an AI Review Article Writer with LangGraph’s multi-agent architecture—fully automating academic review paper generation from literature ingestion to draft completion. Shifting to product management strategy, Microsoft’s Chief Product Officer, Aparna Chennapragada, has declared that Prompt Sets are the new PRDs, and Aakash Gupta laid out the essentials PMs need to transition from static requirements to prompt-driven design. Another key template comes from OpenAI leader MiqJ: a proven six-step sprint for AI experiments covering hypothesis definition, metric-setting, rapid iteration, and learn-share cycles. Meanwhile, George from prodmgmt.world urged PMs to serve as strategic filters for leadership, distilling diverse inputs into concise, high-quality recommendations that guide decision-making. In industry compensation news, Aakash Gupta pointed out that AI product managers at OpenAI now start around $300,000 annually, while Google’s packages begin north of $400,000, and he mapped out five skill levels for career progression. Separately, Pawel Huryn observed a growing trend of CEOs deploying AI agents in the cloud to replace onsite roles once thought to require in-office presence. Over on the AI agent side, Alex Finn demonstrated how to install Claude Code via entropic.com/cloudcode and invoke it with the “claude” command in any terminal—including Cursor—turning your editor into a programmable AI co-pilot. He showed off a “/newsletter researcher” command that scrapes and analyzes competitor newsletters to generate subject lines and drafts in his voice, as well as a “/daily brief” slash command that fetches overnight tech news into a streamlined dashboard. Finally, product leaders Oji and Ezinne Udezue explained how generative AI is reshaping the PM role: static PRDs are obsolete, so teams must validate “sharp problems,” automate low-value tasks, and devote more time to customer insights and go-to-market strategy. They outlined the “shipyard” model—a pod structure bundling PM, engineering, design, user research, data/ML, and product marketing under controlled chaos—and advised embedding large language models at the core to tackle well-defined, high-pain challenges rather than layering AI onto legacy products. 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!