Only 36% of AI-aware Americans expect AI to mostly help their country, according to a Gallup and Microsoft survey. Reid traces that unease to three forces: fear that the future will be worse than the present (which AI amplifies when prosperity has not reached much of the country), an instinct to protect what Americans have, and doubts about who will share in AI’s gains. With Aria Finger, he makes the case for winning at AI while spreading its prosperity, including through AI and robotics in manufacturing. They also examine HackerRank’s Chakra AI interviewer and why hiring should remain a team decision. Finally, OpenAI’s plan to test visual ads in ChatGPT raises another question: can a free AI assistant earn trust while carrying advertising? Reid calls for a clear separation between ads and answers, enforceable commitments, and third-party audits.

For more info on the podcast and transcripts of all the episodes, visit https://www.possible.fm/podcast/

Protecting people online shouldn’t depend on whether a company keeps its safety tools effective, affordable, and available. ROOST founding president Camille François joins Reid Hoffman and Aria Finger to explain how a nonprofit is turning trust and safety into shared infrastructure. She digs into why social media was a blip in how we build tech, what Discord did after Twitter bought Smyte and shut it down, and how two people running a fandom app caught 19 cases of child exploitation in two weeks. A daycare switching its Alexa wake word to "computer" becomes a lesson in how the next generation should relate to machines. They also examine why policy without tools is ineffective, how a shared safety commons helps startups compete, and what it will take to make safety as invisible as encryption.

Reid Hoffman sees promise in an AI buildout and wants its financial risks in the open. He and Aria Finger unpack a Financial Times report on up to $300 billion in AI infrastructure guarantees largely absent from the balance sheets of technology companies. They explore California Governor Gavin Newsom’s push for independent lab auditors and an AI kill switch, and discuss what effective federal oversight could look like. Reid explains how these proposals differ from the 2024 bill he opposed and makes the case for an international cyber treaty. A Truth Social poll to rename AI also prompts a debate about why “artificial” sells the technology short.

Can America lead in AI while making life better for everyday Americans? Reid Hoffman and Aria Finger weigh in on Dario Amodei’s call to pace the frontier, and Reid makes the case for America’s dual mandate: leading in AI while delivering prosperity for the many. Anthropic researcher Evan Hubinger puts his personal estimate of AI-driven extinction risk above 10%. They unpack that warning alongside Sam Altman’s support for slower development and David Sacks calling Anthropic and OpenAI a cartel. Reid identifies biological threats, cyberattacks, and job disruption as the real risks, makes the case for steering over pausing, and explains why kill switches matter. From data centers that don’t raise local electricity bills to a free AI medical assistant for every American, they explore what rebuilding public trust could require.

Read “AI for All Americans” on Substack: https://reidhoffman.substack.com/p/ai-dual-mandate

Reid Hoffman and Parth Patil argue that if your AI experiments always work, you’re not pushing hard enough. Wrapping up the Tokens to the Future series, they revisit seven grantees’ experiments with $1,000 a week each in tokens. Their conversations span Dungeons & Dragons worldbuilding, an iOS game built in a weekend, and personal agents whose usefulness compounds over years. They explore how AI can shift more people from execution-focused “cog jobs” to creative “spark jobs,” and why expertise can sometimes make new possibilities harder to see. Throughout, they ask what to delegate and where story, pacing, and judgment still demand human direction. Plus, Parth’s example of ChatGPT picking seven for a “random” number raises a bigger question: how do you get surprise from a system built to predict?

When AI can fake your CFO’s face and voice, what still counts as proof of identity? Infosec Analyst Dozie Anazia joins Reid Hoffman and Parth Patil to explain how AI is transforming cyberattacks, penetration testing, and autonomous defense. Drawing on projects including the Breakfast news app and Aegis URL scanner, he shows how Claude and Codex can build software, uncover an XSS flaw, and run a pen test—while still falling short of unsupervised network defense and elite human hackers. They explore purple teaming, agent-versus-agent review, and the advantage defenders retain over attackers. Plus, one low-tech defense against a stolen voice: a family safe word.

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/

AI strategist Matthew Tiemann is building toward a world where AI agents work around the clock—and humans step in for the decisions that matter. Across his work at energy services company Foundry-Logic and his personal projects, he uses Claude Code, Codex, and Fable to automate knowledge work and accelerate software development. Those projects range from an AI-assisted iOS game to a personal dashboard informed by his goals, to-do list, and Oura Ring sleep data. Drawing on experience across data analytics, supply chain, robotics, logistics, and energy, Matthew joins Reid Hoffman and Parth Patil to explore proactive “heartbeat” agents and shared context. They also discuss adversarial review, 12-hour human check-ins, and AI’s limits in subjective judgment—revealing why human vision and alignment remain essential.

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

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.

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.