Is the traditional "per-seat" SaaS model officially obsolete?

In 2016, Ron Gabrisko joined a startup with less than $1M in ARR. It was a company of 50 engineers and a product beloved by developers who had never even spoken to a sales rep. Ten years later, Databricks is a $134B giant doing $5.4B in ARR and they are still growing at a staggering 65% year-over-year.

No CRO in history has built a revenue engine this fast, from this early a starting point. Ron didn't do it by following the standard Silicon Valley playbook; he did it by pioneering Consumption-Based Pricing and leveraging Open Source as the ultimate top-of-funnel engine.

In this masterclass, we break down:

• Consumption vs. Seats: Why Databricks tied its pricing to the "most basic unit of value" and how it fueled a $100B+ valuation.
• The Open Source Funnel: How to monetize a community without "locking them in".
• Building Trust with Engineers: Why Ron hires "really technical sales folks" to add value rather than just pitching.
• Scaling through Innovation: Why Databricks didn't stop at one product, but built a sticky ecosystem (Spark, Delta, MLflow).
• The GenAI Future: Why owning and protecting your data is the "secret sauce" for the next decade of AI.

Timeline : 00:00 – The $5.4B Machine: Intro01:20 – Joining Databricks at sub-$1M ARR with 7 PhD founders04:12 – Selling to engineers: hiring "really technical sales folks"06:29 – Killing the SaaS Seat: consumption and the "most basic unit of value"09:22 – Net retention 130%: the multi-product open source strategy14:53 – Planning 65% YoY: the science of forecasting19:03 – Structuring 5,000+ sellers: verticalization and outcome-based selling29:11 – "Don't give your data to us": the data ownership philosophy33:54 – Usage-based vs value-based: why pricing is public on the website

On this episode of BILLIONS, I’m sitting down with Reggie Marable, the Chief Revenue Officer at Sierra.

Reggie’s path wasn't a straight line. He went from being a professional linebacker in the CFL to working in a Sprint call center, and eventually rose to become the Head of Sales for Slack North America. After years at Salesforce, he walked away to join Sierra as employee #23.

Founded by Bret Taylor (former Salesforce Co-CEO) and Clay Bavor, Sierra has reached a $10B valuation and is on a path to $100M ARR in just seven quarters.

Their secret? A business model that should terrify every legacy SaaS founder: Outcome-Based Pricing.

In this masterclass, we break down:

• The Sierra Sprint: How to scale to a $10B valuation in record time.
• Service as Software: Why Sierra only charges customers when a problem is actually resolved.
• The Sales Shift: Why Reggie left a massive leadership role at Slack for an early-stage startup.
• Hiring for the AI Era: Why Reggie looks for "humble, hardworking, and low-ego" talent over pedigree.
• The Recovery: How getting fired earlier in his career became the foundation for his $10B mindset.

TIMELINE :

00:00 – "If your dreams don't scare you...": The Muhammad Ali mindset.

01:17 – From the CFL to a Sprint call center: Reggie’s raw beginnings.

04:07 – The "fired" moment: How losing his job led to a total reinvention.

05:33 – The Salesforce & Slack era: Mentoring 200+ people and scaling Slack North America.

10:00 – Why Reggie left Slack to become employee #23 at Sierra.

12:23 – Outcome-based pricing: Why the "per seat" model is dying.

16:20 – AI agents in the wild: Real-world results for Cigna, Singtel, and Sonos.

19:00 – The resolution model: Charging for solved problems, not software access.

31:15 – Operational cadence: How a $10B startup manages its weekly rhythm.

35:50 – Hiring strategy: Why "humble and hardworking" beats high-ego sellers.

44:10 – The "diversity" advantage: Building high-performance teams through inclusion.

47:16 – Reggie’s final advice: "Success is a winding road."

REFERENCES :

Today on BILLIONS, I'm sitting down with Larry Aschebrook, the guy who invented a market that Wall Street didn't think existed.

Larry started personally buying shares in Twitter and Uber on the side and he realized: there are thousands of employees sitting on life-changing paper gains, with zero liquidity, waiting for companies that might never IPO.

So in 2011, he quit his safe university job and launched G Squared, a fund to solve that problem. Nobody took him seriously. The secondary market was "taboo." Companies thought selling shares meant you were failing.Today, he manages $5 billion.

He turned a $150M Spotify bet into $1 billion. He made $800M on Coursera. And the market he built is now worth $140 billion a year.

Larry, welcome to BILLIONS.TIMELINE :

00:00 : The psychology of the secondary market pioneer.

01:13 : Quitting a decade-long career for a "ghost" market.

03:23 : The Hustle: Cold-calling alumni for early Twitter and Uber shares.

05:41 : The $150 million Spotify bet and the $9M personal risk with zero collateral.

11:19 : Data Arbitrage: How Larry knew record labels were secretly buying Spotify.

15:43 : Scaling G Squared: From a $35 million pool to $7 billion AUM.

20:05 : Why DPI (Cash Back) is the only metric that matters, and why paper gains are a lie.

25:09 : The Scars: Learning from the "quick commerce" collapse and other losses.

37:09 : The Future: OpenAI, SpaceX, and the evolution of private liquidity.

53:12 : Advice for Founders: Why you must hire "grinders," not just pedigree.

REFERENCES :

• Daniel Ek 

• Spencer McLeod

• Mitchell Green

• Jim Simons

• Elon Musk 

• Spotify 

• Twitter 

• Uber 

• Palantir 

• Coursera 

• Anthropic 

• OpenAI 

• SpaceX 

• Stripe 

• Wiz 

• Toast 

• Netflix

• Apple Music 

• Instacart 

• Postmates 

• Meituan 

• Alibaba 

• Turo 

• Getaround

• Klarna 

• Revolut 

• Databricks 

• 23andMe 

• Gorillas 

• Pagaya⁠

Is the traditional SaaS model officially dead ? On this episode of BILLIONS, I’m sitting down with Matthew Fitzpatrick, the man Fortune 500 CEOs called when they didn’t know what to do with AI.

Matthew walked away from one of the most prestigious roles in tech, leading 1 000 engineers at McKinsey’s QuantumBlack Labs to lead Invisible Technologies.

Invisible is the "invisible" engine behind the AI revolution.

They don't just build software; they provide the RLHF (Reinforcement Learning from Human Feedback) and the data that trains the models the entire world is building on.

With $100M raised at a $2B+ valuation, Matthew is proving that the future isn't in selling tools, but in selling outcomes.

In this masterclass, we break down:

• The McKinsey Exit: Why a top AI leader "jumped ship" for a $2B startup.
• The Death of SaaS: Why "Outcome-based pricing" is replacing the subscription model.
• The Enterprise Gap: Why 90% of companies are failing to get AI into production.
• The Scaling Laws: The truth about data bottlenecks and the future of AI training.
• Process as Code: How Invisible integrates human intelligence with AI to solve "impossible" problems.

TIMELINE :

00:00 The data bottleneck: Why Enterprise AI is currently "stuck"

01:01 Why McKinsey’s AI chief left to lead a $2B unicorn

02:33 The "Four Platforms": How Invisible actually works

05:58 SaaS vs. Outcomes: The pricing model of the future

09:19 Why the "AI Bubble" reality check is coming

15:12 The "Capability Gap" holding back the Fortune 500

22:15 RLHF & Data: Building the workforce behind the major models

31:42 "Process is Code": The new architecture for billion-dollar companies

41:10 Matthew’s advice for founders: Don't just build a "wrapper"

48:20 The future of the "Invisible" empire

REFERENCES :

• Mary Meeker

• Elon Musk Étude MIT Sloan

• Étude NBER (National Bureau of Economic Research)

• Article Bloomberg

• McKinsey & Company 

• Quantum Black 

• Invisible Technologies 

• SwissGear 

• Y Combinator

• WeCP (We Create Problems)

• Databricks 

• Snowflake

• Jevons paradox 

• Reinforcement learning from human feedback (RLHF)

• Chain-of-thought reasoning 

• Revolut

On this episode of BILLIONS, I’m sitting down with Ben Cera, the man who helped Travis Kalanick (Uber Founder) build CloudKitchens, and who is now building the "God Mode" for startups: Polsia.

Polsia is an AI that builds and runs companies autonomously. No employees, no meetings, just 24/7 execution. Ben is currently at a $6M annual run rate with a 30% week-on-week growth and he plans to hit $100M ARR in just 3 months. If you want to understand how AI agents are replacing the traditional SaaS model and how "Product-Market Fit" has become a search problem, this is your masterclass.

In this episode, we break down:

• The CloudKitchens Era: Lessons learned from building a global giant with Travis Kalanick.

• The Autonomous Blueprint: How Pulsia builds companies from scratch without human intervention.

• $100M ARR in 90 Days: The aggressive growth strategy behind the AI revolution.

• The "SaaS-pocalypse": Why the software you use today is about to be replaced by agents.

• The "Taste" Economy: Why humans are moving from "builders" to "orchestrators."

TIMELINE :

00:00 "Click a button, get a company": The vision for Polsia

01:12 Building with Travis Kalanick: The CloudKitchens masterclass

04:45 The $100M ARR Plan: How to scale an AI company in 90 days

09:30 Why Product-Market Fit is just a "Search Problem"

15:10 The SaaS-pocalypse: Replacing legacy software with AI agents

22:40 How Polsia finds demand and builds products autonomously

31:15 The Meta Ads Strategy: Scaling from $10/day to millions

38:50 Why "Taste" is the only human skill left in the AI era

45:10 Influencer-led distribution: The new "Billion-dollar" funnel

53:05 Ben’s advice for founders: Stop building for others, build for yourself

REFERENCES

• Travis Kalanick (X/Twitter) 

• Rick Rubin 

• CloudKitchens

• Future Foods

• Polsia

• ChatGPT 

• Claude

• Sora 2 

• Uber 

• Meta Ads 

• Shopify

• Stripe

• Universal Paperclips

• Wikipedia / Craigslist / Amazon 

• HubSpot 

• DoorDash

On this episode of BILLIONS, I’m sitting down with a legendary architect of the SaaS world: Jason Cohen, founder of WP Engine and Smart Bear.Jason has "cracked the code" twice, using two diametrically opposite strategies:The Pure Bootstrap: He built Smart Bear to millions in profit with zero outside funding, eventually leading to a unicorn valuation.The VC War Machine: He raised $250 million from Silver Lake for WP Engine, scaling it to $400M in revenue and 200,000 customers by 2024.This is a masterclass in capital efficiency. Whether you are a solo-founder or a venture-backed CEO, Jason’s framework for building "enduring companies" is the raw truth you won't hear in most boardrooms.TIMELINE : 00:00 - Why AI products almost never work01:20 - Switching from Bootstrapping to $250M VC rounds04:51 - The SaaS-pocalypse: The truth behind HubSpot & legacy decline09:30 - Solving legacy problems with AI-powered search16:17 - Experts vs. Muggles: The three categories of AI products21:55 - Why evergreen insights beat AI hype26:06 - The Power Move: Firing yourself as CEO to save the company34:01 - The "301 Redirect" strategy for management transitions40:48 - Hidden multipliers and the labor of love44:02 - The Raw Truth: Post-exit depression and infinite optionality58:25 - Redefining identity: Leveraging accumulated wisdomREFERENCES :

Lazar Jovanovic is the world's first official "Vibe Coding Engineer." Working at Lovable (the AI startup that hit $100M ARR in just 8 months) Lazar is proving that the future of software engineering isn't about syntax; it's about taste and intent.In this episode, we dive into how Lazar ships production-grade apps for a $6.6B unicorn without writing a single line of manual code. We discuss the "SaaS-pocalypse," why ignorance is a superpower in the AI era, and how you can transition from a traditional role to a Vibe Coder.TIMELINE : 00:00 - Meet the world's first "vibe coding" engineer01:06 - Why "not knowing how to code" is your new superpower04:43 - Is software maintenance dead in the age of AI?09:15 - The Lovable story: hitting $100M ARR in 8 months15:42 - The end of bootstrapping? Vibe coding vs. the old way24:16 - SaaS-pocalypse: the future of software interfaces29:47 - Beyond code: the only metrics that matter for AI products37:01 - Will enterprises ever adopt AI-generated code?44:35 - The "Aladdin & Genie" trick for mastering AI prompts56:05 - How to become a vibe coder (no permission required)REFERENCES :

• Warren Mason

• Kurt Cobain 

• Pieter Levels.

• Marc Lou

• Victor Wembanyama 

• Elena Verna

• Jony Ive

• Lovable 

• Claude 

• OpenAI

• Shopify 

• Stripe 

• TechCrunch 

• Salesforce 

• HubSpot 

• 28 Days of Lovable

• She Builds

• Aladdin and the Genie

Today on BILLIONS, I'm sitting down with Des Traynor, co-founder of Intercom.

In 2023, his company was stuck at 10% growth. Customer service teams were shrinking. The old model was dying.

So he did something radical: he launched an AI agent priced at $0.99 per resolved conversation. Not per seat. Per outcome.

The result? Growth doubled to 25%. $343M in revenue.

And a complete reinvention of a $1.3B company in 18 months.

TIMELINE :

00:00:00 - 00:01:02 : Des Traynor - Intercom

00:01:02 - 00:05:22 : The $1.3 billion bet on AI : moving 15 days after ChatGPT launched

00:05:22 - 00:09:08 : Why building AI is not building SaaS

00:09:08 - 00:12:51 : The "torture test" for engineering reliability

00:12:51 - 00:20:14 : Developing the "white smoke" moment for product

00:20:14 - 00:25:16 : Defining what "good" looks like in AI

00:25:16 - 00:34:53 : The Blockbuster warning: Adapt or die

00:34:53 - 00:40:27 : Killing hallucinations with actor-critic logic

00:40:27 - 00:48:55 : Outcome-based pricing and the future of CRM

00:48:55 - 00:55:56 : The end of frontline customer service jobs

REFERENCES :

• ⁠Fergal Reid⁠ 

• ⁠Ciarán Lee⁠ 

• ⁠Eoghan McCabe⁠

• ⁠Marc Andreessen⁠ 

• ⁠If Anyone Builds It, Everyone Dies⁠

• ⁠OpenAI / ChatGPT⁠

• ⁠Zendesk⁠

• ⁠Salesforce⁠ 

• ⁠Fin.AI⁠

• ⁠Gong⁠ 

• ⁠ClickUp⁠

• ⁠DALL-E⁠

• ⁠Cursor⁠ 

• ⁠Windsurf⁠

• ⁠Devin⁠

• ⁠Claude Code⁠

• ⁠Attio⁠

• ⁠Clarify⁠

• ⁠Netflix⁠

• ⁠The Cheeky Pint

Today on BILLIONS, I'm sitting down with Des Traynor, co-founder of Intercom.In 2023, his company was stuck at 10% growth. Customer service teams were shrinking. The old model was dying.So he did something radical: he launched an AI agent priced at $0.99 per resolved conversation. Not per seat. Per outcome.The result? Growth doubled to 25%. $343M in revenue. And a complete reinvention of a $1.3B company in 18 months.TIMELINE :

00:00:00 - 00:01:02 : Des Traynor - Intercom

00:01:02 - 00:05:22 : The $1.3 billion bet on AI : moving 15 days after ChatGPT launched

00:05:22 - 00:09:08 : Why building AI is not building SaaS

00:09:08 - 00:12:51 : The "torture test" for engineering reliability

00:12:51 - 00:20:14 : Developing the "white smoke" moment for product

00:20:14 - 00:25:16 : Defining what "good" looks like in AI

00:25:16 - 00:34:53 : The Blockbuster warning: Adapt or die

00:34:53 - 00:40:27 : Killing hallucinations with actor-critic logic

00:40:27 - 00:48:55 : Outcome-based pricing and the future of CRM

00:48:55 - 00:55:56 : The end of frontline customer service jobsREFERENCES :

• Fergal Reid 

• Ciarán Lee 

• Eoghan McCabe

• Marc Andreessen 

• If Anyone Builds It, Everyone Dies

• OpenAI / ChatGPT

• Zendesk

• Salesforce 

• Fin.AI

• Gong 

• ClickUp

• DALL-E

• Cursor 

• Windsurf

• Devin

• Claude Code

• Attio

• Clarify

• Netflix

• The Cheeky Pint

Today on BILLIONS, I'm sitting down with Wilfried Juncker.

He's the Managing Director for Odoo's Americas a Belgian software unicorn that just hit a €8 billion valuation.

Under Wilfried's watch, Odoo's Americas operation exploded from 35 people in 2016 to over 950 in America only.

In this episode, we're digging into how Wilfried built Odoo's American war machine, what it takes to conquer a new market from scratch, and how he's fighting high SMB churn while scaling at breakneck speed.

While SAP and Oracle charge millions for ERP, Odoo's open-source model is democratizing enterprise software and Wilfried built the Americas war machine that's making it happen.

Wilfried, thanks a lot for being here!

TIMELINE :

00:00:00 - 00:01:05 : Odoo's explosive growth from 70 to 2,000 employees

00:01:05 - 00:02:30 : The early days and Wilfried's journey at Odoo

00:02:30 - 00:05:25 : Entering the US market with channel partners strategy

00:05:25 - 00:09:25 : Open source model and freemium conversion tactics

00:09:25 - 00:14:20 : Building the partner ecosystem and revenue sharing

00:14:20 - 00:18:07 : Scaling partner relationships and management approach

00:18:07 - 00:24:12 : Hiring and retention philosophy - promote from within only

00:24:12 - 00:27:14 : Industry specialization vs size-based team structure

00:27:14 - 00:34:32 : Managing SMB churn while maintaining growth

00:34:32 - 00:42:17 : Demo-first culture and bottom-up sales approach

00:42:17 - 00:48:20 : Resource allocation and offline marketing strategy

00:48:20 - 00:52:27 : Unconventional customer acquisition tactics

00:52:27 - 00:54:29 : Building local ecosystems and final thoughts

REFERENCES :

- Oracle NetSuite

- Microsoft Dynamics

- SAP

- Acumatica

- Sage

- Epicor

- Infor

- QuickBooks

- HubSpot

- GitHub

- Lemlist

- Clay

- Lucia

- NPR

- NASA