YoYo: Git for AI 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 in AI product launches and updates: LLMs From Scratch on GitHub, updated by Sebastian Raschka, now includes a key-value cache. This lets models reuse past states to reduce redundant computation and boost inference efficiency. Next, YoYo, described as a “Git for Vibe coders,” is an open-source extension by Jason Zhou that brings version control with branching and merging support to AI-generated code in Cursor and Claude Code, simplifying UI and UX iteration. Turning to AI tools and applications: LangChainAI published a guide for GraphRAG on setting up Neo4j knowledge graphs and sharing multi-LLM benchmark results to analyze legal contracts. Additionally, LangChainAI rolled out a real estate document agent that combines Tensorlake and LangGraph, using signature tracking to automate processing, flag missing or forged signatures, and streamline verification. Jason Zhou also introduced a code tagging system that lets teams assign tags to code segments and track feature progress end-to-end, making workflows up to ten times easier. On product management insights and strategies: Aakash Gupta launched a free course covering five essential skills for AI PMs, including exercises in prototyping, observability, evaluation frameworks, determining when to use RAG, fine-tuning, or prompt engineering, and practices for collaborating with AI engineers. In related news, Aman Khan shared frameworks defining the evaluation role for AI product managers, featuring insights on end-to-end evaluation planning from Hamel Husain and Shreya. Meanwhile, Teresa Torres recommended adapting the Opportunity Solution Tree framework to each team’s context, with examples for remote and hybrid teams to support continuous discovery. In industry developments and news: Bolt announced the Supabase Startup Challenge, giving developers access to a full-stack platform—database, authentication, and storage—to scale emerging projects to millions of users. On a different front, DeepLearningAI highlighted Columbia University research showing that LLM-based agents can be manipulated via malicious links on trusted sites, prompting a call for new security guidelines. Lastly, Dharmesh Shah reflected on his TEDx Boston talk and accompanying article, detailing practical strategies for collaborating with AI in the workplace. 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!