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 launch front, Google AI Studio rolled out a redesigned landing page showcasing the work of Ammar, ahead of a broader public beta. In related news, OpenAI rolled out GPT-5 to all users—Free, Plus, Pro, and Team—with double rate limits for Plus and Team, and teased mini versions of GPT-5 and GPT-5 Thinking. Separately, Sebastian Raschka released an analysis of open-source gpt-oss, tracing its advances since GPT-2 and benchmarking it against Qwen3.
Switching gears to tools and applications, Anthropic published a video masterclass on practical AI at work, Andrej Karpathy shared a files-to-prompt script for loading project contexts into chat sessions, and LangChain demonstrated building stateful AI agents with LangGraph and SingleStore vector storage.
In the tutorials space, All About AI released a step-by-step guide to running GPT-5 locally with Cloud Code. It covers copying the JavaScript Quickstart, fetching Anthropic’s MCP docs, cloning the gpt5mcp repo, setting your API key, and launching the server with npm. After sending a ‘hello’ prompt to confirm responses and tuning reasoning effort and temperature, you switch to plan mode to design a Go-based Tetris app, iteratively debug UI and controls, and refine fixes with screenshot feedback until the game works.
Meanwhile on the growth front, Nick Turley from OpenAI traced ChatGPT’s evolution from a 10-day hackathon project called ‘Chat with GPT-3.5’—rapidly greenlit into public release by a single tweet from Sam Altman and surprising its creators with strong retention and viral growth—into a platform serving 700 million weekly active users and 5 million business subscribers. Pricing was set at $20 for Plus and $200 for Pro via a quick Van Westendorp survey. He also highlighted that GPT-5, OpenAI’s frontier model with state-of-the-art reasoning, coding, and writing performance, faster dynamic thinking, and refined output, is now available free to all.
Turning to product management strategy, Teresa Torres urged teams to expand their opportunity space before ideation and recommended cross-functional trios of PM, designer, and engineer to accelerate delivery and boost collaboration. Separately, Shreyas Doshi introduced “Corporate Algorithms” that shape organizational decisions and offered tips for clearer product leadership.
And in industry news, DeepLearningAI reported that heavy reliance on AI companions can lower satisfaction and affect mental health, while Rowan Cheung noted a gap between fast-paced AI Twitter dialogue and general users still mastering basic ChatGPT prompting. Finally, Sebastian Raschka argued that Google’s Gemini could become a market leader despite quieter marketing.
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!