Check out the conversation on Apple , Spotify and YouTube . Brought to you by: * Jira Product Discovery: Build the right thing * AI PM Certification : Get $550 with code AAKASH550C7 * The AI Evals Course for PMs : Get $1050 off with code ag-product-growth * Maven : Get $100 off my curation of their top courses Today's Episode Today’s guest is at the epicenter of AI - and he hasn’t done any podcasts before . In today’s in-person chat, I sit down with Jake Brill , the Head of Integrity Product at OpenAI. He breaks down: * The GPT-5 launch * How OpenAI builds product * What the PM role looks in the the future with AI * The future of building product and the need to build agents into your product * What it takes to break into OpenAI If you've ever wondered what it takes to work at OpenAI or how to build AI products at scale, this episode is for you . Your Newsletter Subscriber Bonus : For subscribers, each episode I also write up a newsletter version of the podcast. Thank you for having me in your inbox. (By the way, we’ve launched our podcast clips channel as well and we’re going to post most valuable podcast moments on this channel, so don’t miss out: subscribe here .) 1. Integrity’s Role in the GPT-5 Launch Most PMs think about launching products in terms of features and marketing. But when you're serving hundreds of millions of users with breakthrough AI, the real challenge is infrastructure that can handle the surge without breaking. OpenAI’s integrity team played 3 roles in GPT-5 ’s launch. Pillar 1 - Identity Systems Identity systems must scale from normal traffic to potentially 10x volume overnight. The technical challenge involves load balancing, database scaling, and ensuring your signup flow doesn't crash when everyone hits "Create Account" simultaneously. Pillar 2 - Financial Infrastructure Financial systems need bulletproof payment processing and fraud detection as conversions spike. This includes sophisticated fraud prevention - bad actors specifically target new model launches to exploit capabilities with stolen credit cards. Pillar 3 - Safety Systems Safety systems require multiple defense layers: model training, input/output classifiers, and behavioral monitoring. Red teaming happens during model training, at production checkpoints, and continuously post-launch. What most PMs miss is that integrity isn't just defensive - it's an enabler of scale . Without rock-solid integrity infrastructure, even the most advanced AI models can't reach their intended audience. Do you need an integrity team? If you're building consumer AI products at scale, handling sensitive data, or processing payments, the answer is probably yes. 2. How OpenAI Builds Product OpenAI operates with a unique product philosophy that breaks traditional PM playbooks. While most companies start with user problems and build solutions, OpenAI often starts with breakthrough capabilities and figures out how to bring them to humanity. Let’s zoom in on 5 key takeways about how they build product: Takeaway 1 - The Research-First Approach Jake describes this inverted approach: "We've got the best researchers in the world building the most powerful AI capabilities in the world. And sometimes it's like, holy moly, we just had this big research breakthrough . How do we bring this capability to humanity?" This research-first methodology requires unprecedented collaboration between product and research teams from day one, not as an afterthought. Takeaway 2 - Planning That Embraces Uncertainty Their planning process intentionally embraces uncertainty. Teams plan quarterly but assume only 60-70% completion rates . "If you do anything more than that, it probably means you weren't being flexible enough to the needs of the business. If you do anything less than that, probably didn't do a great job forecasting." Plans are written in pencil, not pen , with lightweight documents and async reviews wherever possible. Takeaway 3 - Product Reviews Stay Startup-Style Product reviews maintain startup-style directness despite OpenAI's scale. "People come in, it doesn't matter what level you are, you can talk directly with leadership. You don't have to have a fancy slide deck ." This creates trust through transparency and hiring excellence rather than process overhead. Takeaway 4 - Heavy Slack Culture OpenAI runs almost entirely on Slack. Jake estimates "conservatively like 90% of my written communication is in Slack ." They've built AI agents directly into their Slack channels for Q&A and operational tasks. Takeaway 5 - Iterative Deployment Philosophy The company's belief in iterative deployment shapes how they handle uncertainty. Rather than trying to predict every possible misuse case, they identify non-negotiable risks to mitigate before launch, build monitoring systems for edge cases, and "very quickly respond and build sophisticated solutions" based on real-world usage patterns. "Actually, at the end of the day, it's really helpful to follow OpenAI's appro
