Tony Gentilcore - Glean, the $7.2B Startup Sam Altman Warned Investors About

Earlier this year, the "SaaSpocalypse" wiped out something like $2 trillion of SaaS market cap in a matter of weeks — so I sat down with Tony Gentilcore, co-founder of Glean and formerly one of the minds behind Google Search and Chrome, to figure out what's actually happening to software in the agent era. We get into a lot: why Tony thinks outcome-based pricing (the model Sierra and Decagon are famous for) won't survive, and why companies will drift back toward per-seat. Why the "no Chinese models" rule every enterprise swears by tends to evaporate the moment finance sees the token bill — and why Nemotron, GLM, and Kimi are already good enough to matter. The story behind Sam Altman reportedly telling VCs that if they backed Glean, OpenAI didn't want them as investors (Tony's reaction: "we took it as very flattering"). We also dig into the messier reality of AI at work — how it's saving employees around 11 hours a week while quietly costing them 6 back in what Tony calls "bot sitting and bot shitting," why hard token caps on engineers don't change behavior, how CTOs are blowing through their annual token budgets a quarter into the year, and why the roles of product manager, designer, and engineer are collapsing into one. If you care about where software, pricing, and enterprise AI are all heading, this one's worth your time. Chapters: 00:00 Welcome and Setup 00:56 Glean Origin Story 03:08 Enterprise Search Signals 05:07 LLMs Inflection Point 08:08 Early Product Workflow 09:45 Search Evals and Privacy 12:05 From Chatbots to Agents 13:45 Agent Use Cases 17:08 Lessons and Puck Direction 19:08 Bot sitting, bot shitting, and slop 24:44 Token Budgets and ROI 30:59 AI Trends and Moats 35:03 Training and Fine Tuning 38:03 Why Enterprises Fear China Models 39:58 Sovereignty Backlash Watch 40:26 The time Altman called out Glean 41:19 Org Roles Become Builders 44:10 Future Work Voice First 48:17 Vibe Coding vs Quality 52:20 SaaSpocalypse Evolution 54:19 Pricing Tokens Win 55:37 Outcome Pricing Doubts 57:02 Audience AI Review Overload 58:53 Subsidies and Model Choice 01:01:18 Context Layer Interoperability 01:04:52 Build vs. buy: rolling your own Glean 01:07:47 Shadow AI and the coming security mess 01:12:22 Who actually competes 01:13:36 Wrap-up and thanks