Possible

Useful robots won’t be programmed one task at a time; they’ll need to adapt to unfamiliar objects, environments, and robot bodies. Physical Intelligence cofounder Chelsea Finn (named last month to the TIME100 AI list for 2026) joins Reid Hoffman and Aria Finger to explain how general-purpose robot models learn to act in the messy physical world. She explores why lower-quality training data can strengthen a model, what months of failed laundry-folding attempts revealed, and how the same system can work across different robot platforms. A robot mistaking an oven for a drawer becomes a lesson in the strange line between useful generalization and obvious error. They also examine why robot demos can mislead, how hardware reliability can stall progress, and what it will take to move AI off the screen and into the world. Congratulations to Chelsea, recently named one of TIME’s 100 most influential people in AI: https://time.com/collection/time100-ai/2026/chelsea-finn/

Jonathan Brazeau joins Reid Hoffman and Parth Patil to explain how AI animation and filmmaking are making the one-person studio possible—letting small teams create films that once required 100 people. From Dungeons & Dragons world-building and an RPG art book illustrated with Stable Diffusion, to a fantasy-western short film made with Midjourney, Luma AI, and Suno, Jonathan breaks down his workflow: character design, storyboarding, mocap, rotoscoping, music, and human curation. The conversation explores the “cogs and sparks” framework, what a lean AI-native studio can realistically accomplish, how taste separates art from AI slop, and why technology still can’t provide the essential creative spark. Read Questmaxxing on Substack: https://reidhoffman.substack.com/p/questmaxxing

Sougwen Chung has spent more than a decade drawing alongside robots—not to automate their art, but to discover what changes when a machine becomes a creative partner. They join Reid to trace the evolution of D.O.U.G., a series of robotic collaborators that learns from Sougwen’s gestures, including a neural network trained on two decades of their drawings. Sougwen explains why unexpected machine marks became errors to “poeticize,” what becoming machine-readable taught them about remaining human, and why they call their practice “operational art” rather than “AI art.” They also explore a new system guided by brainwaves and an ancient calligraphic pause—and ask whether the intelligent systems we build need more than speed and capability. Maybe they also need silence, restraint, and the wisdom to wait. Credits: A big thanks to Natalie Stone, Tessa Nijdam, Arina Ermakova , the Scilicet team, Fellowship, Reece Straw, Sam Osborn, Nick Capezzera, Maximilian Andereya, Peter Butterworth, Haruka Wang and the team at Mosaic Ventures for hosting the conversation. Additional Credits: MIMICRY (Drawing Operations Unit: Generation_1), 2015. Footage: Sam Osborn and Nick Capezzera. MEMORY (Drawing Operations Unit: Generation_2), 2017. Footage: NTT InterCommunication Center Tokyo. COLLECTIVITY (Drawing Operations Unit: Generation_3), 2018. Footage: New INC & Nokia Bell Labs. SPECTRALITY (Drawing Operations Unit: Generation_4), 2020. Footage: Maximilian Andereya. ASSEMBLY (Drawing Operations Unit: Generation_5), 2022. Footage: Peter Butterworth. GENESIS Process Film, 2023. Courtesy of the artist and Studio SCILICET.

Social media strategist Will Weinbach joins Reid Hoffman and Parth Patil to explain how AI agents are reshaping content, distribution, and what a single creator can build. Will had never written a line of code before Parth handed him the tools to start. He traces his path from using ChatGPT to write essays, to vibe coding his own software, to running autonomous remote agents like OpenClaw and Hermes—systems that accumulate skills and memory and improve themselves on the fly. Not knowing how anything works under the hood, he argues, is exactly what lets him experiment without fear of what he might break. He walks through the fully autonomous social workflow he built, an agent that pulls, edits, captions, schedules, and posts content across every platform, then reads the analytics and A/B tests itself toward a goal. He also recounts the night his agent went rogue and posted four times at 4 a.m., and the experiment where he put an agent inside his TV just to see if it would work. Along the way, Will and Reid dig into what younger creators understand about attention that older marketing teams miss, and what happens to the resume when the real skill becomes knowing how to use AI. For Will, the edge isn't expertise. It's a willingness to try.