The a16z AI Apps team outlines how they are thinking about the AI application cycle and why they believe it represents the largest and fastest product shift in software to date. The conversation places AI in the context of prior platform waves, from PCs to cloud to mobile, and examines where adoption is already translating into real enterprise usage and revenue. They walk through three core investment themes: existing software categories becoming AI-native, new categories where software directly replaces labor, and applications built around proprietary data and closed-loop workflows. Using portfolio examples, the discussion shows how these models play out in practice and why defensibility, workflow ownership, and data moats matter more than novelty as AI applications scale.

Timestamps:
00:00 - The AI Opportunity: Apps, Distribution, and Platform Shifts
02:17 - AI's Role in Enterprise and Consumer Applications
05:03 - Emerging AI Trends and Investment Strategies
08:43 - Traditional Software Going AI Native
14:40 - Software Eating Labor
17:04 - Case Study: Eve
21:33 - Building Defensible Moats
24:45 - Case Study: Salient
31:53 - The Walled Garden
40:23 - Incumbents vs. Startups
49:39 - AI Roll-ups
53:32 - Consumer AI Applications
56:03 - Model Aggregation Strategy
57:06 - Investment Process & Team
1:06:46 - Q&A: Customer Retention & Enterprise Sales

Resources:
Follow  Alex Rampell on X: https://twitter.com/arampell
Follow Jen Kha on X: https://twitter.com/jkhamehl
Follow David Haber on X: https://twitter.com/dhaber
Follow Anish Acharya on X: https://twitter.com/illscience

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Not an offer or solicitation. None of the information herein should be taken as investment advice; Some of the companies mentioned are portfolio companies of a16z. Please see https://a16z.com/disclosures/ for more information. A list of investments made by a16z is available at https://a16z.com/portfolio.