Subvolts take Enterprise AI is costly and slow to adopt, despite lab progress. Hear why. May 28, 2026 - Developers
- Learn about the challenges and opportunities in building enterprise AI agents and headless software.
- Business
- Understand the real costs and adoption hurdles for AI in large organizations, and how it impacts budgets.
This episode provides a grounded, expert view on enterprise AI adoption, cutting through the noise.
State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, Rise of Headless, and AI-Proofing Your Job
Audio streams from Matt Turck. Your place is remembered on this device.
From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Aaron Levie, CEO of Box, joins The MAD Podcast to discuss the real state of enterprise AI. He explains why we are still in the early days of AI agents, the high cost of running them, and how progress at AI labs paradoxically slows enterprise adoption. Levie also covers token cost shock, the success of coding agents, the rise of headless software, and the future of jobs in the AI era.
Imagine AI assistants for big companies. This talk explains why they are expensive to run, why they are not yet widely used, and how they might change jobs. It's about the practical side of AI, not just the exciting new tools.
This episode offers a grounded perspective on enterprise AI adoption, moving beyond hype. It's for business leaders and IT professionals navigating AI integration. Levie's insights connect directly to how major labs like Google Gemini and OpenAI are influencing enterprise strategies, particularly regarding agent capabilities and the unexpected costs impacting budgets. Understanding these real-world challenges is crucial for anyone tracking AI's practical impact.
- HostMatt Turck
- GuestAaron Levieco-founder and CEO, Box
- Guest: Aaron Levie
- Title: State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, Rise of Headless, and AI-Proofing Your Job
- Show: The MAD Podcast
- Length: 73 minutes
- Compute Cost: One badly written agent run can cost $1,000 in compute.
- AI Era Stage: Still in 'day one' of the agent era.
Aaron Levie, co-founder and CEO of Box, returns to the MAD Podcast with the clearest read in tech on what AI is actually doing inside the world's largest enterprises right now - not the hype version, the real one. After hundreds of Fortune 500 CIO conversations this year, Aaron explains why we're still in "day one" of the agent era, why one badly written agent run can now cost $1,000 in compute, and why progress at the AI labs is paradoxically slowing enterprise deployment. We get into the token cost shock now reshaping IT budgets, why coding agents have reached escape velocity while the rest of knowledge work hasn't, the rise of headless software and what replaces per-seat pricing, the emergence of the forward-deployed engineer as the hottest job in tech, why Aaron thinks the AI doomers are wrong about jobs, and where startups can still win as the labs move up the stack.
(00:00) Intro
(01:18) Silicon Valley engineering vs. everyone else
(05:35) Are enterprise CIOs actually bullish on AI?
(08:51) Tokenmaxxing & why your AI bill is about to explode
(11:34) The myth of falling token costs and AI spend escaping IT budgets
(17:37) The $5B startup hiding in AI compute
(18:14) The mosaic of models inside every enterprise
(21:28) Why coding works and the rest of knowledge work doesn't
(25:53) The Bob and Sally problem: access control breaks agents
(30:31) Will enterprise AI really take 10 years to roll out?
(32:24) The capability overhang: why faster models slow diffusion
(34:23) Data is the bottleneck (it always was)
(39:02) The rise of internal forward-deployed engineers
(41:23) Why the AI doomers are wrong about jobs
(43:43) Headless software is inevitable
(46:14) What replaces per-seat pricing
(47:37) How Box itself is going headless
(49:42) How the org chart actually evolves
(1:00:33) Future-proofing yourself as an enterprise employee
(1:06:40) Are we all just going to work for OpenAI and Anthropic?
(1:07:11) Where startups can still win as the labs move up
- Tokenmaxxing
- Aaron Levie
- Maximizing the use of AI tokens, often leading to unexpectedly high costs.
- Headless software
- Aaron Levie
- Software that operates without a user interface, often used for backend AI services.
- Forward-deployed engineer
- Aaron Levie
- An engineer who works directly with customers to implement and troubleshoot new technologies.
Same guests, other shows
1 h 05
31 min
1 h59 min
Questions people ask
- Why are enterprise AI agents expensive?
- A single poorly written AI agent run can now cost $1,000 in compute, impacting IT budgets significantly.
- Why is enterprise AI adoption slow?
- Progress at AI labs paradoxically slows enterprise deployment, and issues like access control break agents.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Matt Turck.