
About this episode
Cadi Zhang joins Reid Hoffman and Parth Patil to explore how generative AI is changing game development, world models, and robotics. Drawing on her work across Unity games, VR teleoperation, AI accounting, and robotics product operations, Cadi explains what virtual worlds can teach embodied intelligence—and why physical robots still lack the tactile, real-world data that can’t be scraped from the internet.
She shares how she uses GPT, Blender, PixelLab, and Aseprite to prototype games faster, including a duck-themed imposter game and PokéTax, her Pokémon-inspired tax-filing game. AI can rapidly generate code, gameplay mechanics, and 3D assets, she says, but it still can’t judge whether a game feels fun, maintain a consistent art style, or model the precise force needed to fold a sheet of paper.
Reid, Parth, and Cadi discuss simulation-to-reality gaps, the limits of current world models, robot safety, humanoid versus task-specific form factors, and why human taste remains the decisive creative skill.
Get every episode summarized
Each time Possible publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.
Email me new episodesFree for 3 shows. No card needed.
Hosts & guests
No transcript yet
This episode has not been transcribed. Request it and it moves to the front of the queue.
More episodes
More from Possible

Can we defend against AI hacks? | Dozie Anazia
Possible
Sep 9, 202640:37failed

Training robots for a world they’ve never seen
Possible
Sep 2, 202659:20pending

Inside an AI-powered personal dashboard | Matthew Tiemann
Possible
Aug 26, 202631:49pending

The whole studio is one guy | Jonathan Brazeau
Possible
Aug 19, 202631:55pending