Hex and OpenAI Convene Product Leaders to Define AI-Era Engineering at April 29 SF Gathering

Pressure is building inside product and engineering teams, and it is not coming from lack of capability. It is coming from expectation. Models respond faster, outputs look sharper, and demos land cleaner than ever, yet the gap between what works in a controlled environment and what holds up in production keeps widening. What used to feel like progress now feels like exposure. The real work has shifted, and much of the startup ecosystem is still catching up to that reality.

That tension is exactly why Product Engineering in the Age of AI carries weight on April 29, 2026 from 5:30–8:00 PM at Hex HQ in San Francisco. Hosted by Hex with OpenAI as co-host, this is a deliberately small, approval-based room. No excess. No passive audience. The premise is clear: product engineering is now the bottleneck, and the teams that solve it will define the next cycle of the startup ecosystem. This is not about showcasing models. It is about shipping systems that hold up under latency, cost, trust, and real user behavior.

The room itself does the filtering. An evening format with light bites and drinks, but the real currency is proximity. Conversations happen shoulder to shoulder, not stage to seat. The kind of environment where a Head of Engineering compares failure modes with a product lead who owns retention, not just features. Hex provides the physical and philosophical container, and OpenAI brings the underlying gravity of the model layer that every serious team is already building on, whether directly or by proxy.

Dan Eisenberg, Head of Engineering at Hex, represents what it means to embed AI into workflows that people rely on, not just experiment with. Rohan Varma, Product (Codex) at OpenAI, sits at the intersection of model capability and developer reality, where constraints shape product decisions. Amol Jain, Head of Product Engineering at Replit, operates inside an environment where code and AI are inseparable, and where product engineering is not a function but a system. Deeni Fatiha, Head of Product for AI at Gamma, is building inside creation itself, where automation either earns user trust or gets bypassed. Each brings a different surface area, but the same underlying pressure that is reshaping the startup ecosystem.

What connects them is a redefinition of the role itself. The AI-era product engineer is not waiting on requirements or wiring endpoints. They are shaping behavior, designing evaluation loops, and making judgment calls on systems that evolve in production. Architecture meets intuition. Data meets interface. The old splits between backend and frontend start to dissolve into pods organized around outcomes that can be measured and defended.

Events like this do not broadcast trends. They compress them. When operators from Hex, OpenAI, Replit, and Gamma share the same room, the conversation moves from theory to calibration. What works. What fails. What holds under pressure. In a startup ecosystem still flooded with demos, this is where product truth starts to separate from product theater, and where the next set of decisions quietly take shape.