
Written by a model from the transcript; not yet reviewed.
This episode features Andreessen Horowitz partner Josh Elman discussing the evolution of consumer AI products, building lasting software, and his career spanning Twitter, Facebook, Apple, and beyond. The guest and host explore the shift from early internet and mobile products to today's AI agents, examining why utility must precede trust for mainstream adoption and how products must earn the right to expand into new areas. They also examine the future of live shopping, micro dramas, social networks, and why voice interfaces represent just one modality among many for future products. Listeners get an investor's inside perspective on what separates flash-in-the-pan AI demos from durable, habit-forming consumer platforms.
The hosts introduce the episode and welcome Josh Elman, setting the stage for a discussion on consumer AI products.
Josh explains his career trajectory and why he has returned to the investor side at Andreessen Horowitz.
Josh contrasts five‑year‑ago consumer behavior with post‑COVID digital life, highlighting the rise of video calls, gaming, and AI productivity tools.
The conversation shifts to how AI must earn trust and become a habit before it can expand into other features.
They explore why new social networks haven’t emerged and the potential for creator‑focused marketplaces that blend social and content discovery.
Josh describes the vision for personal AI agents that manage schedules, shopping, health, and social planning, becoming a daily companion.
The hosts discuss AI‑generated micro‑dramas and new entertainment formats that deepen storytelling beyond traditional social media.
The discussion turns to voice assistants, their strengths and limitations, and how voice can complement other modalities in AI products.
Josh shares examples of AI doubles, like a virtual Reid Hoffman, that help users prepare for real interactions.
The conversation shifts to how AI tools are priced, often free to gain users before monetizing.
The host reflects on past high upfront server costs and how cloud services lowered barriers for consumer products.
Discussion of how AI inference costs are variable and the need to balance free features with paid ones.
Comparing COVID Tech to AIinsight
The guest explains how COVID normalized video calls and spiked gaming usage, whereas today's AI boom focuses on tools that help people be more present and efficient in the physical world.
Consumer AI Adoption is Earlydata
While developers and tech workers use advanced agent swarms and coding assistants, everyday consumers mostly rely on ChatGPT and Gemini for synthesized searches and brainstorming.
Designing Clothes with AIstory
The guest shares a personal anecdote of designing a black polo sweater completely with AI and having it manufactured in China, showcasing a new paradigm of personalized consumer creation.
The Rise of Micro Dramasinsight
Short-form video has expanded into engaging micro dramas, and AI now allows creators without Hollywood budgets to produce and distribute rich serialized stories.
Multiplayer AI Agent Coordinationstrategy
The host and guest debate the future of group interactions, imagining AI agents that coordinate schedules and social hangouts among friends to bring people together in real life.
The Variable Cost Challengedata
Unlike traditional software with fixed server costs, modern AI applications face variable inference costs that require careful consideration of monetization and consumer willingness to pay.
The Twitter Retweet Debatestory
Recalling his time at Twitter, the guest explains how the controversial decision to launch the retweet preserved the original poster's identity instead of adopting the retweeter's voice.
“It's never been easier to get consumers' attention. The hard part is getting them to stick.”
“We have to bring people step by step into understanding, what does it mean to have AI doing things for you? What does trust mean here?”
“The models got so much better towards the end of last year that they could do long-running tasks. They could actually have loops of improvement. Agentic tasks finally started to work, and the coding and envisioning of something got so much better.”
“If you want to become a very big company, you can't start by trying to do everything, but you have to start by doing a few things really, really well and earn the right to do more.”
“Exactly. It did actually help. We talked about it a ton. So if you can check it out, we'll put in the link in the comments.”
“What got amazing in this era of cloud scaling, Amazon Web Services, all these new stacks, was all of a sudden you didn't need that same set of heavy upfront infrastructure costs.”
“And I think over the next couple of years, we're going to intersect with how much cheaper these can get to build and serve, with how much customers are willing to pay for things that are of value or entertainment for them.”
“Things that I look for in a product are where it has a really clear value that you can describe to somebody. If you start using this product, you get this thing that didn't exist before where people will raise their eyebrows.”
“And if I keep engaging with this product over time, now I know, hey, we really are on to something.”
a16z Partner Josh Elman joins Ollie Forsyth on New Economies to discuss the next wave of consumer AI and what separates a product people try once from one that becomes part of their everyday lives. Josh argues that getting attention has actually become easier, but getting consumers to stick is harder than ever. He explains what he looks for in consumer products, why the best ones start with a narrow wedge and earn the right to do more, and why trust becomes increasingly important as AI agents gain access to more of our personal lives. They also explore personal AI agents, the future of shopping and entertainment, why we haven’t seen another major social network emerge, and how AI could make technology more social rather than less, including agents that help people spend more time together in the real world. This conversation originally appeared on the New Economies podcast.
12,965 words · 3 speakers
Speaker names marked are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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