@levie: Agents will use software 100X more than people. When that happens, theres a huge need for guardrails on what the agents…
Summary
Box CEO Aaron Levie argues that AI agents will use software 100X more than people, requiring guardrails, authoritative data sources, logging, and collaboration features; platforms enabling headless interactions will be best positioned.
View Cached Full Text
Cached at: 06/23/26, 01:49 PM
Agents will use software 100X more than people.
When that happens, theres a huge need for guardrails on what the agents are doing so they don’t leak data or change the wrong information, authoritative sources of truth for them to work with, logging and auditing of what they’re doing, the ability to collaborate with people through these systems, and more.
A simple query on any given agentic task could pull in more data than a user touches in a month. As a result, there are lots of categories of software that when it goes headless that the usage and value go up substantially. Agents will end up using our CRM data, documents and corporate knowledge, analytics data, and other information far more than people ever did.
The platforms that can move toward the model of powering these headless interactions, and have a business model and technology strategy to support this, will be in the best position in the future.
Podcast Alpha (@PodcastAlphaX): Levie now uses Salesforce 5x more than at any point before.
The Box CEO @levie connected Salesforce’s MCP server to Claude Code. Now he runs customer and market intelligence queries he would never have bothered pulling up by hand.
The agent removes the friction. The underlying
Similar Articles
@levie: If you’re trying to understand the dynamic of real world agent adoption this post is a great place to start. Everyone g…
Aaron Levie shares insights on real-world AI agent adoption, arguing that agents are more like managing a process than chatting, and require workflow changes for big upside.
@levie: The deployment of AI in the enterprise beyond just interacting with a chatbot will unequivocally take real work to alig…
Aaron Levie discusses the significant challenges of deploying AI agents in enterprise workflows, including fragmented data, legacy systems, and the need for change management, highlighting the growing role of deployment companies.
@levie: One reason why we’re going to get uneven diffusion rates of agents is because different workflows in the enterprise are…
Aaron Levie argues that AI agent adoption will diffuse unevenly across industries because enterprise workflows vary in alignment with continuous digital work, unlike coding where agents thrive. He highlights the need to reengineer business processes for AI agents.
Agents will become a discovery layer
The article argues that AI agents will shift from workflow automation to becoming a discovery layer, choosing tools, vendors, and sources for users, making agent visibility critical for founders. The author introduces Rankpad as a solution to this challenge.
AI agents are starting to look less like software and more like employees
The article argues that AI agents are evolving from being evaluated solely on intelligence to requiring operational reliability, governance, and team integration akin to human employees, highlighting the need for new infrastructure layers.