The Agent Era: Building Software Beyond Chat with Box CEO Aaron Levie (1h 0m)

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• Release date: 2026-04-21
• Listen on Spotify: Open episode
• Episode description:

  Erik Torenberg, Steve Sinofsky, and Martin Casado speak to Aaron Levie, CEO at Box, about what happens to enterprise software when agents become the primary users. They discuss why coding agents succeed where other knowledge work agents struggle, what abstraction layers mean for the workforce, and how data access and systems of record must change in an agent-first world. Follow Aaron Levie on X: https://twitter.com/levie Follow Steve Sinofsky on X: https://twitter.com/stevesi Follow Martin Casado on X: https://twitter.com/martin_casado Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Summary

• 🚀 Agent-Centric Software Shift: The podcast highlights how AI agents will outnumber humans, demanding software built for APIs and reliability over polished UIs, reshaping enterprise tools.
• ⏳ Slower Enterprise AI Diffusion: Complex domain knowledge in legacy systems like SAP delays AI adoption, creating a gap between agile startups and cautious large firms.
• 🔒 Security and Oversight Challenges: Treating agents like employees raises issues of prompt injection and data leaks, requiring new governance models beyond human analogies.
• 💰 Underestimated Economic Boom: AI opportunities are vastly larger than current models suggest, with agents enabling micropayments and exploding resource consumption like past tech waves.
• ⚡ Compute Budget Wild West: Engineering teams face unprecedented budgeting for tokens, balancing experimentation waste with efficiency in an elastic, high-stakes environment.

Insights

• Why does the diffusion of AI capabilities in enterprises take longer than Silicon Valley anticipates?
  • Time: 0:00 – 30:37
  • Answer: Enterprise systems like SAP encode deep domain knowledge and organizational logic that can’t be easily replaced by AI agents or ‘vibe coding,’ requiring extensive integration and security measures. Legacy layers persist due to compatibility and policy needs, slowing adoption despite agent potential. This gap allows startups to innovate faster while large firms grapple with risks like data leaks and system fragmentation.
• How do persistent software layers influence the path of AI agent integration in enterprises?
  • Time: 0:44 – 40:45
  • Answer: Past tech waves promised to eliminate middlemen but layers endured for organizational logic, compatibility, and policy; agents will adapt to these rather than flatten them. Systems like ERP won’t be ‘vibe coded’ away, slowing diffusion but enabling gradual enhancements like on-demand integration. This favors building better backends over interface overhauls, with agents selecting tools based on semantics and performance.
• How will the proliferation of AI agents force software companies to redesign their architectures for agent-scale interactions?
• In what ways will AI agents transform human roles by elevating skills to higher abstraction levels?
• How might treating AI agents like human employees reshape enterprise security and governance?
• Why are current economic models underestimating the AI opportunity by an order of magnitude?
• What challenges will engineering teams face in managing AI compute budgets amid explosive growth?

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