Uploaded December 2025 | Updated September 2026, 2 weeks ago
Glean started as a Kleiner Perkins incubation and is now a $7B, $200m ARR Enterprise AI leader. Now KP has tapped its own podcaster to lead it’s next big swing.
From building go-to-market the hard way in startups (and scaling Palo Alto Networks’ public cloud business) to joining Kleiner Perkins to help technical founders turn product edge into repeatable revenue, Joubin Mirzadegan has spent the last decade obsessing over one thing: distribution and how ideas actually spread, sell, and compound. That obsession took him from launching the CRO-only podcast Grit (youtube.com/playlist?list=PLRiWZFltuYPF8A6UGm74K2q29UwU-Kk9k) as a hiring wedge, to working alongside breakout companies like Glean and Windsurf, to now incubating Roadrunner which is an AI-native rethink of CPQ and quoting workflows as pricing models collapse from “seats” into consumption, bundles, renewals, and SKU sprawl.
We sat down with Joubin to dig into the real mechanics of making conversations feel _human_ (rolling early, never sending questions, temperature + lighting hacks), what Windsurf got right about “Google-class product _and_ Salesforce-class distribution,” how to hire early sales leaders without getting fooled by shiny logos, why CPQ is quietly breaking the back of modern revenue teams, and his thesis for his new company and KP incubation Roadrunner (roadrunner.ai/): rebuild the data model from the ground up, co-develop with the hairiest design partners, and eventually use LLMs to recommend deal structures the way the best reps do without the Slack-channel chaos of deal desk.
We discuss:
* How to make guests instantly comfortable: rolling early, no “are you ready?”, temperature, lighting, and room dynamics
* Why Joubin refuses to send questions in advance (and when you _might_ have to anyway)
* The origin of the CRO-only podcast: using media as a hiring wedge and relationship engine
* The “commit to 100 episodes” mindset: why most shows die before they find their voice
* Founder vs exec interviews: why CEOs can speak more freely (and what it unlocks in conversation)
* What Glean taught him about enterprise AI: permissions, trust, and overcoming “category is dead” skepticism
* Design partners as the real unlock: why early believers matter and how co-development actually works
* Windsurf’s breakout: what it means to be serious about “Google-class product + Salesforce-class distribution”
* Why technical founders struggle with GTM and how KP built a team around sales, customer access, and demand gen
* Hiring early sales leaders: anti-patterns (logos), what to screen for (motivation), and why stage-fit is everything
* The CPQ problem & Roadrunner’s thesis: rebuilding CPQ/quoting from the data model up for modern complexity
* How “rules + SKUs + approvals” create a brittle graph and what it takes to model it without tipping over
* The two-year window: incumbents rebuilding slowly vs startups out-sprinting with AI-native architecture
* Where AI actually helps: quote generation, policy enforcement, approval routing, and deal recommendation loops
—
Joubin
* X: https://x.com/Joubinmir
* LinkedIn: linkedin.com/in/joubin-mirzadegan-66186854
Where to find Latent Space
* X: https://x.com/latentspacepod
* Substack: https://www.latent.space/
00:00:00 Introduction and the Zuck Interview Experience
00:03:26 The Genesis of the Grit Podcast: Hiring CROs Through Content
00:13:20 Podcast Philosophy: Creating Authentic Conversations
00:15:44 Working with Arvind at Glean: The Enterprise Search Breakthrough
00:26:20 Windsurf's Sales Machine: Google-Class Product Meets Salesforce-Class Distribution
00:30:28 Hiring Sales Leaders: Anti-Patterns and First Principles
00:39:02 The CPQ Problem: Why Salesforce and Legacy Tools Are Breaking
00:43:40 Introducing Roadrunner: Solving Enterprise Pricing with AI
00:49:19 Building Roadrunner: Team, Design Partners, and Data Model Challenges
00:59:35 High Performance Philosophy: Working Out Every Day and Reducing Friction
01:06:28 Defining Grit: Passion Plus Perseverance
Glean started as a Kleiner Perkins incubation and is now a $7B, $200m ARR Enterprise AI leader. Now KP has tapped its own podcaster to lead it’s next big swing.
From building go-to-market the hard way in startups (and scaling Palo Alto Networks’ public cloud business) to joining Kleiner Perkins to help technical founders turn product edge into repeatable revenue, Joubin Mirzadegan has spent the last decade obsessing over one thing: distribution and how ideas actually spread, sell, and compound. That obsession took him from launching the CRO-only podcast Grit (youtube.com/playlist?list=PLRiWZFltuYPF8A6UGm74K2q29UwU-Kk9k) as a hiring wedge, to working alongside breakout companies like Glean and Windsurf, to now incubating Roadrunner which is an AI-native rethink of CPQ and quoting workflows as pricing models collapse from “seats” into consumption, bundles, renewals, and SKU sprawl.
We sat down with Joubin to dig into the real mechanics of making conversations feel _human_ (rolling early, never sending questions, temperature + lighting hacks), what Windsurf got right about “Google-class product _and_ Salesforce-class distribution,” how to hire early sales leaders without getting fooled by shiny logos, why CPQ is quietly breaking the back of modern revenue teams, and his thesis for his new company and KP incubation Roadrunner (roadrunner.ai/): rebuild the data model from the ground up, co-develop with the hairiest design partners, and eventually use LLMs to recommend deal structures the way the best reps do without the Slack-channel chaos of deal desk.
We discuss:
* How to make guests instantly comfortable: rolling early, no “are you ready?”, temperature, lighting, and room dynamics
* Why Joubin refuses to send questions in advance (and when you _might_ have to anyway)
* The origin of the CRO-only podcast: using media as a hiring wedge and relationship engine
* The “commit to 100 episodes” mindset: why most shows die before they find their voice
* Founder vs exec interviews: why CEOs can speak more freely (and what it unlocks in conversation)
* What Glean taught him about enterprise AI: permissions, trust, and overcoming “category is dead” skepticism
* Design partners as the real unlock: why early believers matter and how co-development actually works
* Windsurf’s breakout: what it means to be serious about “Google-class product + Salesforce-class distribution”
* Why technical founders struggle with GTM and how KP built a team around sales, customer access, and demand gen
* Hiring early sales leaders: anti-patterns (logos), what to screen for (motivation), and why stage-fit is everything
* The CPQ problem & Roadrunner’s thesis: rebuilding CPQ/quoting from the data model up for modern complexity
* How “rules + SKUs + approvals” create a brittle graph and what it takes to model it without tipping over
* The two-year window: incumbents rebuilding slowly vs startups out-sprinting with AI-native architecture
* Where AI actually helps: quote generation, policy enforcement, approval routing, and deal recommendation loops
—
Joubin
* X: https://x.com/Joubinmir
* LinkedIn: linkedin.com/in/joubin-mirzadegan-66186854
Where to find Latent Space
* X: https://x.com/latentspacepod
* Substack: https://www.latent.space/
00:00:00 Introduction and the Zuck Interview Experience
00:03:26 The Genesis of the Grit Podcast: Hiring CROs Through Content
00:13:20 Podcast Philosophy: Creating Authentic Conversations
00:15:44 Working with Arvind at Glean: The Enterprise Search Breakthrough
00:26:20 Windsurf's Sales Machine: Google-Class Product Meets Salesforce-Class Distribution
00:30:28 Hiring Sales Leaders: Anti-Patterns and First Principles
00:39:02 The CPQ Problem: Why Salesforce and Legacy Tools Are Breaking
00:43:40 Introducing Roadrunner: Solving Enterprise Pricing with AI
00:49:19 Building Roadrunner: Team, Design Partners, and Data Model Challenges
00:59:35 High Performance Philosophy: Working Out Every Day and Reducing Friction
01:06:28 Defining Grit: Passion Plus Perseverance




 and Isomorphic for example), it is starting to look like the appetite of Pharma for biotech tools has finally started to grow. Why the sudden interest?
Timestamps:
(0:00) The challenges of starting a biotech lab and generating data from scratch.
(0:55) Introduction of Ron Alfa and Dan Bear from Noetik.
(4:09) The complexity of cancer: Why curing cancer is a misleading concept and the need for new, multimodal data.
(8:24) Identifying therapeutically relevant cancer subtypes to improve clinical trial success rates.
(11:27) The importance of intentional, high-quality data generation in AI biotech.
(17:09) Lessons learned from Recursion Pharmaceuticals regarding batch effects and data design.
(20:14) Introduction to Noetiks core data modalities: Pathology (H&E), spatial transcriptomics, and genomic alterations.
(30:15) The philosophy of self-supervised learning and avoiding bias from electronic health records.
(36:01) Translating latent space embeddings and patient clusters into actionable insights for pharma.
(41:40) Using PerturbMap and in-vivo mouse models to validate human AI predictions.
(53:38) Technical deep dive: The Tario transformer-based model and auto-regressive training objectives.
(1:00:26) The GSK partnership: Licensing OctoVC and the shift toward platform-based biotech deals.
(1:13:55) Advice for small biotech AI startups: Scaling, data conviction, and lessons from scientific history. 🔬 Training Transformers to solve 95% failure rate of Cancer Trials — Ron Alfa & Daniel Bear, Noetik](https://i.ytimg.com/vi/uqM8qjbLRHA/mqdefault.jpg)





