OpenAI Introduces gpt-realtime Speech-to-Speech Model

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. OpenAI just introduced gpt-realtime, their best-in-class speech-to-speech model for developers, alongside significant updates to the Realtime API. These enhancements deliver low-latency, bi-directional voice interactions, making it possible to build seamless, real-time conversational experiences across apps. On the image front, Gemini Flash 2.5—nicknamed Nano Banana—offers a major leap in both speed and quality for image generation and editing. In a recent interview, Jeff Dean explained how the model processes complex scenes faster while maintaining high fidelity. Beyond simple picture tweaks, Nano Banana taps into world knowledge to visualize map locations. Jason Zhou demonstrated how developers can generate detailed geographical graphics on demand. Meanwhile, Andrew Ng’s DeepLearningAI has launched a new course on Retrieval Augmented Generation. It teaches product teams how to ground large language models through retrieval to boost factual accuracy, covering techniques for hallucination mitigation, balancing prompt length, and managing compute costs. Ng also highlighted the power of parallel agents, showing how running tasks concurrently can dramatically scale AI speed and performance without making users wait for one response at a time. In related technology news, Claire Vo reported some hiccups with the GPT-5 API. Users are noticing typos, punctuation errors and occasional nonsensical output. She’s working directly with the OpenAI development team to iron out these glitches and restore reliable responses. Shifting to product strategy, Lenny Rachitsky detailed Microsoft’s move to planning in “seasons” rather than fixed quarterly or annual cycles. This approach helps teams adapt roadmaps more dynamically in a fast-moving market. Teresa Torres also rolled out her latest Tools of the Trade guide for continuous discovery, inviting product managers to share the research and collaboration tools that drive their innovation processes. Turning to the industry landscape, OpenAI plans a major expansion through a $30 billion annual deal with Oracle under the Stargate program. This agreement will support a 4.5-gigawatt data-center build on top of last year’s 1.2-gigawatt site in Texas, fueling the compute needs of next-generation AI. Over at Microsoft, Asha Sharma, the AI platform product strategy lead, provides insights drawn from supporting 80,000 startups and enterprises. On Lennys Podcast, Sharma described AI products as continuously learning organisms. She forecasts an “agentic society” where AI agents replace traditional org charts with dynamic, task-based work charts. One key takeaway: once a foundation model tops 30 billion parameters, it’s more cost-effective to apply post-training loops—fine-tuning and reinforcement learning—instead of investing heavily in additional pre-training. Today’s platforms already help over 15,000 customers deploy millions of agents, and the shift from static GUIs to code-native, composable interfaces—leveraging text streams, APIs, and agent collaboration—enables continuous evolution of AI 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!