Levie Argues Evals Will Gate Enterprise Adoption of AI Agents
Box CEO Aaron Levie argues enterprises cannot automate work they cannot measure, so evals are essential for adopting AI agents. He says domain-specific evals will become a major opportunity, and a quoted post notes data labeling firms expect Fortune 1000 customers to drive revenue and company evals may become proprietary IP.
Original post · 1 min read
We can test our deterministic processes through software, but most enterprises have no useful way of understanding how their non-deterministic processes are working today. Specifically the work that agents are doing for them.
Evals are mission critical for enterprises adopting AI because you have no other way of knowing what’s working, what’s broken, what changed, what improved, what you can do more of, etc. if you don’t have a good sense of how agents work in your environment today. All changes, upgrades, and deployments are downstream from good evals.
Not only are we going to get vastly more domain specific evals over time for the labs and across the industry, but every enterprise will also need a clear sense of how agents are performing in their environment as well. Huge opportunity.
Alex Lieberman @businessbaristaJust spoke to one of the big data labeling businesses.
Few interesting insights:
- They predict the majority of their revenue will come from Fortune 1000 enterprises, not labs in a few years
- They believe every company will want to own their intelligence, but owning intelligence does not necessarily mean using open source models
- A company’s evals will become their main proprietary IP given the improvement in agent performance after properly setting up & running internal eval environments
- Most enterprises haven’t graduated from coding agents and it’s largely due to not having the proper e…






