How Box builds for Enterprise AI

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Future Proof: Building AI Products that Last

Paragon

8 episodes

2 days ago

Future Proof brings top Product and Engineering leaders in B2B SaaS, working on AI products, to share learnings, discuss challenges and the latest developments in the future of B2B software. Producer: Forrest Herlick Host: Ethan Lee

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How Box builds for Enterprise AI | Aaron Levie

Future Proof: Building AI Products that Last

33 minutes 19 seconds

5 months ago

How Box builds for Enterprise AI | Aaron Levie

Welcome to the first episode of the Future Proof Podcast: Building AI Products That Last! In this episode, we chat with Aaron Levie, CEO and founder of Box, about what it takes to build successful Enterprise AI products.

We cover:

Why good data is a moat / flywheel for AI products
The importance of access controls in RAG
Building broad or building deep
APIs, MCPs, A2A

(00:00) Clips

(00:30) Intro

(01:40) Box's AI strategy

(04:45) RAG use cases with proven value

(09:05) Horizontal vs. deep product strategy

(11:14) Prompts as IP

(12:05) Importance of secure RAG in enterprise AI

(16:28) Ingest vs. agentic queries

(19:10) APIs, MCPs and Agent-to-Agent

(21:20) Moats and network effects for AI companies

(26:49) Risk of bad data

(29:48) A few large AI agents vs. many niche AI agents

Scale your AI product's integration roadmap with Paragon at https://useparagon.com/?utm_source=podcast/utm_campaign=ep1