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 Setup00:56 Glean Origin Story03:08 Enterprise Search Signals05:07 LLMs Inflection Point08:08 Early Product Workflow09:45 Search Evals and Privacy12:05 From Chatbots to Agents13:45 Agent Use Cases17:08 Lessons and Puck Direction19:08 Bot sitting, bot shitting, and slop24:44 Token Budgets and ROI30:59 AI Trends and Moats35:03 Training and Fine Tuning38:03 Why Enterprises Fear China Models39:58 Sovereignty Backlash Watch40:26 The time Altman called out Glean41:19 Org Roles Become Builders44:10 Future Work Voice First48:17 Vibe Coding vs Quality52:20 SaaSpocalypse Evolution54:19 Pricing Tokens Win55:37 Outcome Pricing Doubts57:02 Audience AI Review Overload58:53 Subsidies and Model Choice01:01:18 Context Layer Interoperability01:04:52 Build vs. buy: rolling your own Glean01:07:47 Shadow AI and the coming security mess01:12:22 Who actually competes01:13:36 Wrap-up and thanks