The a16z Show

Elena Burger sits down with academic and cyber ethnographer Ruby Justice Thelot to explore the increasingly blurry line between internet culture and the real world, and how to tell the difference between a trend that’s actually changing behavior and one that simply feels enormous online.
They use today’s wellness and optimization culture as a case study, from peptides and GLP-1s to protein maxxing, wearables, microplastics, and the quantified self. Ruby explains her concept of “paracontent,” where the conversation around a phenomenon can become much larger than the phenomenon itself, and what social media data can tell us about how these trends move from niche communities into the mainstream.
They also trace the much longer history of body optimization, from changing ideals of thinness to the rise of the quantified self, and ask what comes next as technology gives people increasingly granular ways to measure and modify themselves. Ruby’s prediction: rather than everyone optimizing toward the same ideal, we may see increasingly individualized and sometimes extreme forms of “body futurism.”

Resources:
Follow Ruby Justice Thelot on X: https://x.com/being_on_line
Follow Elena Burger on X: https://x.com/VirtualElena
Read Ruby’s piece “Enshittification” Isn’t Real: https://www.a16z.news/p/enshittification-isnt-real



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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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Ben Horowitz and Erik Torenberg sit down with OpenAI co-founder and President Greg Brockman to discuss why he believes AI has entered a new phase, what OpenAI’s latest models reveal about the path to AGI, and the safety and security challenges that come with increasingly capable systems.
Greg explains why computer use represents such an important step for agents, including models that can work coherently for 24 hours and interact with software through the same interfaces humans use. He also shares how OpenAI deployed 10,000 agents to tackle the Navier-Stokes problem, and why advances in mathematical reasoning could translate into new approaches to science, software, and cybersecurity.
Ben, Erik, and Greg also dig into the “defender’s window” for cybersecurity, how AI could reshape work and entrepreneurship, and what the AI assistant of the future might actually look like: persistent, proactive, personalized, and capable of doing work on your behalf rather than waiting for another prompt.

Resources:
Follow Greg Brockman on X: https://x.com/gdb
Follow Ben Horowitz on X: https://x.com/bhorowitz


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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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World Labs co-founder Justin Johnson joins MTS hosts Theo Jaffee and Sofia Puccini to discuss Atlas, World Labs’ latest world model, and the broader case for AI systems that understand and interact with the physical world.
Justin explains how Atlas approaches three core tasks: generating new worlds, reconstructing real environments from images, and simulating how objects or robots might behave within them. Underlying it is a bigger thesis: just as language models became general-purpose engines for working with text, world models could become a horizontal layer for visual and physical intelligence across industries from entertainment and gaming to construction and robotics.
They also explore how world models could change video games and creative tools, why precise spatial control matters, and the potential for “real-to-sim-to-real” robotics, where a few photos of a physical environment could eventually be enough to build a simulation and adapt a robot to that specific space.

Resources:
Follow Justin Johnson on X: https://x.com/jcjohnss
Follow Theo Jaffee on X: https://x.com/theojaffee
Follow Sofia on X: https://x.com/schisofrenia
Follow MTS on X: https://x.com/mtslive


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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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a16z General Partner Anish Acharya joins Lenny Rachitsky on Lenny’s Podcast to discuss why fears of an AI-driven “permanent underclass” may be misplaced, how AI is changing the way companies operate, and why the opportunity may be less about replacing people and more about dramatically expanding what they can build.
Anish lays out his idea that companies are becoming a series of loops, with agents increasingly handling workflows across engineering, sales, marketing, support, and other functions while humans provide the judgment and new ideas needed to move beyond local maxima.
They also explore why Anish thinks consumer AI should focus less on productivity and more on helping people live richer lives, why moats are often discovered rather than designed, how to develop intuition for different AI models, and why his biggest advice for anyone trying to keep up with AI is simple: make more things.

Resources:
Follow Anish Acharya on X: https://x.com/illscience
Follow Lenny Rachitsky on X: https://x.com/lennysan
Read/listen to the original episode on Lenny’s Newsletter:
Why companies are becoming a series of loops | Anish Acharya (a16z)

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a16z’s Matt Perault sits down with General Partner and Speedrun lead Andrew Chen on the a16z AI Policy Brief to explore what “Little Tech” actually looks like at the earliest stages, and why the realities of building a two- or three-person startup are often missing from policy debates.
Andrew takes us inside Speedrun, where founders are often starting companies from kitchen tables, working with tiny teams, and trying to determine in a matter of months whether their idea can become a viable business. He explains why these founders rarely have the time or resources to engage with policymakers, even as regulation can have an outsized impact on whether and where they build.
Matt and Andrew also discuss how regulatory burdens accumulate for young companies, why startups can choose where to put down roots, the role of ecosystems like Tech Week, and what policymakers can do to hear directly from the founders who may otherwise be absent from the conversation.
This episode originally appeared on the a16z AI Policy Brief.

Resources:
Follow Andrew Chen on X: https://x.com/andrewchen
Follow Matt Perault on X: https://x.com/MattPerault
Learn more about a16z Speedrun: https://speedrun.a16z.com
Listen to more from the a16z AI Policy Brief: https://a16zpolicy.substack.com/


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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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