Podcast
What’s Next for Consumer AI? | Josh Elman Joins A16z
The a16z Show
- Siri Found My Dinner From A Text
- Josh Elman recounts using Apple’s new assistant to navigate to a dinner by finding a text message with the address.
- The assistant pulled data from messages and calendar to avoid a wrong turn a few blocks away. (Time 0:06:54)
- Consumer AI Should Augment Everyday Life
- AI can shift from productivity/work replacement to enhancing everyday life and personal experiences.
- Josh Elman argues natural language interfaces and personalization let people create, customize, and explore things previously hard or impossible for consumers. (Time 0:08:20)
- Chat Is A Launchpad Not A Replacement
- Chat-style interfaces are a powerful starting substrate but won’t replace rich apps and experiences.
- Elman expects chat to get users into apps faster, then users will spend time in immersive, visual experiences like games. (Time 0:13:58)
- AI Discovery Will Use Creators And Agent Referrals
- Discoverability for AI-native products will be multi-channel: creators, virality, search, and ‘generative optimization’ by agents.
- Elman predicts assistants that refer out to vertical apps will boost discovery and create ecosystems. (Time 0:21:24)
- Prioritize Retention Before Scale
- Focus on retention over raw acquisition; get a small group to move their lives onto your product before scaling.
- Elman says build a product people can’t go back from, then repeat and expand from that core. (Time 0:24:30)
- Robinhood Grew With Share Giveaways And Word Of Mouth
- Josh Elman explains Robinhood’s early growth: product-first word of mouth, strong design, Reddit buzz, then a referral that gave actual shares.
- The giveaway-share mechanic acted like a lottery and amplified organic excitement efficiently. (Time 0:27:37)
- Musical.ly Became TikTok Through A Creation Loop
- Elman recounts Musical.ly’s loop: easy creation, curated feed, and cross-posting to Instagram that created influencer stars.
- ByteDance acquired and scaled it with paid ads, but retention from personalization made those ads effective. (Time 0:31:55)
- Design Pricing Around Inference Costs
- Charge consumers when inference costs are meaningful; users are willing to pay for valuable AI features.
- Elman notes easier in-app payments and advises moving cheaper inference to device while sending complex work to the cloud. (Time 0:36:45)
- Labs Won’t Win Every Consumer Use Case
- Large incumbents and major assistants will dominate some layers, but many consumer opportunities remain for startups.
- Elman argues users will expect assistant-like behavior everywhere, creating openings for specialized products and experiences. (Time 0:38:51)
- Build AI That Helps People Spend Time Well
- Build consumer AI that helps people spend time well across life tasks like travel, health, finance, and learning.
- Elman prioritizes consumer experiences over enterprise workflows, highlighting underexplored personal use cases. (Time 0:49:10)