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.
LangChainAI has released LangChain 1.0, introducing production agents with cleaner imports, dynamic prompting, middleware hooks, and tight integration with LangGraph for data persistence, streaming outputs, and seamless human handoffs.
In related news, DeepLearningAI unveiled Moonshot AI’s new Kimi K2 Thinking and Kimi K2 Thinking Turbo models. These trillion-parameter mixture-of-experts alternate cycles of reasoning and tool use, outperforming other open-weight LLMs on complex, multi-step tasks.
Meanwhile, Google’s Gemini 3 Pro and Meta’s Nano Banana Pro just got a boost: Logan Kilpatrick’s team is now online 24/7 to support customers scaling with these models, offering higher API rate limits for faster development.
Moving to AI tools, Andrej Karpathy introduced llm-council, a ChatGPT-style web app that dispatches user queries to multiple models—like OpenAI’s GPT-5.1—via OpenRouter, letting you compare responses side by side.
On the prototyping front, Reforge rolled out Build, an AI prototyping tool for product managers, complete with a one-month free trial to rapidly spin up and test new concepts.
On the product management side, Lenny Rachitsky pointed out that 70–80% of design challenges stem from helping users understand what a product does, not just removing friction points.
Separately, George from prodmgmt.world recommended a Wesley Kao talk as the definitive guide to managing up, revealing the frameworks your manager relies on but rarely shares.
Aakash Gupta also broke down four essential skills for AI PMs—crafting AI PRDs, rapid prototyping, product strategy, and AI evaluation—to earn and hold a seat at the table.
In industry developments, Guillermo Rauch made the case for “vibe coding,” arguing that shipping early over perfection lets teams communicate ideas more effectively and iterate faster.
Meanwhile, DeepMind co-founder Demis Hassabis attributed major AI breakthroughs to world-class research, engineering, and infrastructure working in tight alignment with relentless focus.
Looking at the chip market, Gupta noted that if Google wins the AI race, Broadcom could book up to $4 billion a year in co-development revenue, securing its position as the second-largest AI chip vendor by revenue, behind Nvidia.
Over on LinkedIn, Marc Baselga outlined three “gravitational pulls” squeezing AI startups—incumbents bolting on AI, horizontal giants like ChatGPT, and instant clones—and urged founders to ask, “What becomes possible now that wasn’t on the table before?”
Peter Yang shared how the Wispr Flow team pivoted from a brain-to-text wearable to a voice-first AI product that now boasts 70% user retention and 40% month-over-month growth by focusing on product–market fit and sustained engagement.
And finally, Pawel Huryn demonstrated how GPT-5.1 agents can autonomously plan, execute, reflect, and adapt using a concise system-prompt and a four-step loop—Plan, Execute, Update, Finish—to tackle complex, 30-step tasks across more than 20 integrated tools.
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!