The OpenAI Forum hosted a conversation between Stack Overflow CEO Prashanth Chandrasekar and OpenAI’s Head of Developer Experience Romain Huet on how AI is transforming software work and the role of developers. Prashanth reflected on his journey from building early hospital management software in C++ to leading Stack Overflow and returning to hands-on coding with modern AI tools, framing generative AI as a platform shift on the scale of the internet. He argued that AI is not replacing developers but changing what it means to be one, creating effectively infinite demand for code and new applications across domains like drug discovery, while increasing the need for engineers who understand fundamentals and can guide, evaluate, and collaborate with AI agents. The discussion highlighted how enterprises are piloting and scaling AI, navigating security, privacy, and governance concerns, and using products like Stack Overflow for Teams plus OpenAI models to power internal assistants that tap institutional knowledge. Prashanth also described how Stack Overflow is evolving—introducing AI Assist, staging areas for questions, opinion-based discussions, and chat—to make learning more empathetic while preserving high-quality, trusted knowledge amid rising AI usage but uneven trust. He closed by advising engineers and universities alike to pair deep foundational skills with mastery of AI tools, emphasizing that those who can do both will be especially valuable as AI lowers the barrier to innovation and accelerates progress in high-impact fields.

The OpenAI Forum hosted educator and data artist Greg Niemeyer from UC Berkeley for a talk on how AI is transforming learning, teaching, and thinking. Building on OpenAI’s mission to ensure broadly distributed benefits from AI, Niemeyer introduced a “Minus AI, Plus AI, Times AI” framework: minus AI for intentionally tech-free, embodied learning; plus AI for transparent, dialectical collaboration with AI; and times AI for AI as a medium that restructures knowledge itself. He proposed a cognitive insight formula—C = Q × T × K where meaningful learning depends on the quality of questions, the strength of trust, and the richness of the knowledge base, emphasizing that if trust collapses, learning outcomes collapse as well. Throughout the talk, he shared concrete classroom experiments showing how AI can either de-skill students or spark creative divergence and multiplayer learning when used thoughtfully and transparently. He closed by urging educators and learners not to choose one mode, but to move wisely among minus, plus, and times AI to keep curiosity, meaning, and our shared “we” at the center of education in the age of AI.