Where are the biggest value opportunities in the AI stack?
Most answers highlight value in application layers, proprietary data, and workflow integration, while a few emphasize upgrading infrastructure or data processing as key opportunities beyond foundational models.
7 answers
Answers


Ben Horowitz
Horowitz · Andreessen Horowitz
AI Infrastructure
Ben Horowitz points to AI infrastructure, saying the infrastructure for AI is out of date and not strong enough — much like cloud computing's, which eventually got rebuilt from storage to networking.
The answer starts at 48:40.
a16z Podcast · Listen on Apple Podcasts

Emily Man
Partner · Primary Venture Partners
Applications Layer
Emily Man says she focuses on the applications layer, the last level of the stack, after chips, infrastructure and models; she notes past tech shifts lay the pipes first before building on top.
Run the Numbers with CJ Gustafson · Watch on YouTube

Itamar Novick
Founder & General Partner · Recursive Ventures
Application Layer
Itamar Novick points to the application layer, saying AI infrastructure is in a bubble and application companies delivering end solutions to customers are the ones that emerge, not LLM firms.
The answer starts at 24:20.
The Tech Trek · Listen on Apple Podcasts
Morgan Flager
Managing Partner · Silverton Partners
Proprietary Data
Morgan Flager says the biggest advantage he looks for is a proprietary data and learning advantage, since data few others can access and learning from it or its metadata can sustain an edge others can't copy.
VC10X with Prashant Choubey · Watch on YouTube

Anish Acharya
General Partner · Andreessen Horowitz
Consumer Product Design
Anish Acharya says the opportunity for this technology lies in basic consumer needs—feeling connected, loved, making progress, having fun—and that it is not a model or capability challenge but just a product design challenge.
The answer starts at 1:14.
a16z Podcast · Listen on Apple Podcasts

Julien-David Nitlech
Managing Partner · Iris
Data-Homogenizing Layers
Julien-David Nitlech points to data-homogenizing layers, saying everyone will use them to make data homogeneous and operate automations, since current stacks aren’t fit for automation.
The European VC · Watch on YouTube

Sam Altman
Chief Executive Officer · OpenAI
Workflow Depth & Judgment
Sam Altman says the value is shifting to compute scale, workflow depth and human judgment, and that a founder's moat is the workflow, integration depth and switching costs built around whichever model they use.
The AI Corner · The AI Corner · Read
More Venture Capital questions
View all →- How do you balance risk in your VC portfolio?6 answers
- What qualities do you seek in founders before investing?13 answers
- What skill most improved your investment decisions?9 answers
- How do you support founders facing tough challenges?10 answers
- What practice best assesses founders for long-term investment?10 answers











