Why Enterprise AI Adoption Is Slower Than You Think — Aaron Levie (Box) + Harrison Chase

Short summary

Aaron Levie (Box CEO) and Harrison Chase (LangChain co-founder) examine why AI agents excel at coding but lag in enterprise knowledge work—exploring permissions, domain specificity, and the 'Jevons paradox' of headless software. They detail Box's agent harness architecture using Deep Agents, MCP, and token optimization strategies. The discussion bridges product design with real enterprise adoption challenges.

• •Coding agents work due to clear semantics; knowledge work agents fail because of permission models, domain complexity, and user trust barriers
• •Box is building with Deep Agents, MCP, and headless design—prioritizing developer integration over tight product wrapping
• •Enterprise AI adoption depends on token budgets, model selection tradeoffs, and reconceiving disintermediation as business advantage

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