Zapier is doing hundreds of millions in ARR, has 800 employees, and has more AI agents than people. That ratio isn't an accident.

Wade Foster, CEO and co-founder of Zapier, built one of the most capital-efficient software companies in history on less than $1 million in venture funding. When GPT-4 launched in March 2023, he called a company-wide "code red" (a term he'd never used before) and stopped the entire company for a week-long hackathon. What happened next reshaped how Zapier hires, operates, prices its product, and thinks about the future of software.

In this episode of Founded & Funded, Karan Mehandru sits down with Wade to unpack:

1. Why ChatGPT didn't trigger urgency at Zapier, but GPT-4 did — and the specific signal Wade used to make that call
2. How Zapier went from 10% AI tool adoption to 90%+ across the company in a single week
3. The pricing overhaul that simplified Zapier's model around task-based usage and why agents made seat-based pricing structurally broken
4. Why Zapier's head of HR became the Chief People and AI Transformation Officer, and what that reveals about who actually leads change inside organizations
5. The "build first, run always" framework Wade uses for deploying AI agents safely inside enterprise workflows

For founders and operators navigating their own AI transformation, this is a practical, unfiltered look at what it actually takes from a CEO who's in the middle of it.

Full Transcript: https://www.madrona.com/zapier-has-more-ai-agents-than-employees-heres-how-that-happened

Chapters:
(00:00) – Introduction
(01:44) – Zapier Today: Hundreds of Millions ARR, 800 Employees, More Agents Than People
(06:16) – Why ChatGPT Didn't Trigger Urgency — But GPT-4 Six Months Later Did
(07:12) – Code Red: Stopping the Entire Company for a Week-Long AI Hackathon
(08:00) – How Zapier Moved AI Adoption From 10% to 90% of Employees in One Week
(10:11) – Managing the Psychology of Change When Numbers Still Look "Okay"
(13:11) – Why Companies in the Middle Ground Face the Hardest AI Transformation Problem
(15:01) – From Bottoms-Up Adoption to Systematic ROI: The Two-Phase AI Rollout
(17:00) – Why Zapier's Head of HR Became the Chief AI Transformation Officer
(19:54) – Refactoring the Legacy Monolith: Writing Code for Agents Instead of Humans
(21:25) – Zapier's Pricing Overhaul: Why Task-Based Usage Beats Seat Pricing
(23:26) – Why Agents Will Choose What Software to Buy — and What That Does to SaaS
(28:03) – The Build-First, Run-Always Framework for Enterprise Agent Governance
(29:40) – Wade's AI Hiring War Council: A Multi-Agent System He Built That Morning
(34:14) – The Leadership Profile That Thrives When the Job Is Rebuilding, Not Scaling
(40:08) – If You're Starting a Company Today, Distribution Is the Bottleneck
(42:10) – Why AI Deals Are Hard to Renew and the Rise of the Field Delivery Engineer

What happens when AI agents — not humans — become your primary customer? That's not a hypothetical. It's already happening, and the founders who recognize it earliest are rebuilding their entire infrastructure stacks from scratch.

In this live episode of Founded & Funded from our IA Summit in Seattle, Madrona Venture Partner Jon Turow sits down with Parag Agrawal, former CEO of Twitter and founder of Parallel Web Systems, and Nikita Shamgunov, who led Neon through a rapid AI pivot before its acquisition by Databricks.

What they cover:

• Why Parag is building a new search index from the ground up — and why existing ones weren't designed for AI agents
• The moment Nikita realized Replit agents were spinning up databases 4x faster than all human developers combined — and what that forced him to do
• How to pivot an established company in weeks, not months, when your customer base suddenly changes
• The "pagers vs. iPhones" framework for knowing when to lean into disruption vs. protect what you have
• Parag's two-person hiring rubric for teams operating in deep uncertainty
• Why Nikita added the head of product for ChatGPT to Neon's board — and what that signaled to the market
• The "two-way door" model for giving agents real autonomy without catastrophic downside

Whether you're building infrastructure, running an AI-native startup, or trying to figure out where your product fits in an agent-first world — this conversation will sharpen your thinking.

Full Transcript: https://www.madrona.com/twitter-ex-ceo-web-built-for-humans-make-it-work-for-ai-agents-nikita-Shamgunov-parag-agrawal

Chapters
(00:00) – Introduction
(01:52) – Parag Agrawal: Why Parallel Was Built for AI Agents From Day One
(03:22) – Why Existing Search Indexes Don't Work for AI Agents
(05:08) – Nikita Shamgunov: How Replit Agents Outpaced the Entire World on Neon
(08:27) – The Pager-to-iPhone Decision: Lean Into Disruption or Get Left Behind
(11:13) – How Neon Built an AI Team in Two Weeks and Launched MCP Before Anyone Else
(13:41) – Firing Bullets: Why a 4-Out-of-9 Batting Average Was Good Enough
(15:37) – Parag on the Two Types of People You Need to Take Concentrated Risk
(21:08) – Building Trust in Agents: Evals, Confidence Scores, and Read-Only Infrastructure
(23:32) – Nikita's Two-Way Door Framework for Agent Autonomy
(25:35) – Parallel Execution: Fork Environments and Let Agents Compete

What does it really take to sell an AI-native product into the Fortune 500?
In this episode of Founded & Funded, Madrona Managing Director Matt McIlwain sits down with two founders deep in the trenches of enterprise AI adoption, Esha Joshi (Co-founder, Yoodli⁩) and Anup Chamrajnagar (Co-founder, Gradial.)

Their companies are selling into some of the world's most complex organizations, like Google, SAP, Snowflake, Databricks, and more. And they break down what founders often underestimate about enterprise AI sales.

They dive into:
Why most AI pilots fail and how to prevent it
The "three-legged stool" of enterprise sales
How AI review boards are reshaping buying cycles
Securing long-term contracts
Pricing AI: seats vs. usage vs. outcomes
Navigating non-deterministic AI failures with customers
Building champions who accelerate their careers with AI

If you're building an AI-native company and selling into enterprises, this is for you.

Full Transcript: https://www.madrona.com/this-is-how-fortune-500-companies-are-buying-ai-today

Chapters:
(00:00) – Introduction

(03:37) – Early AI Pilots: What Worked (and What Didn't)

(05:01) – Sell Pain, Not Features

(06:25) – Why Enterprise Expectations Are Higher Now

(07:48) – Moving From "Wow" Factor to Durable Outcomes

(09:17) – How to Structure a Pilot That Converts

(10:35) – Expanding Beyond the Initial Wedge

(13:41) – Turning Pilots Into 12-Month Contracts

(14:47) – Navigating Procurement & AI Governance Boards

(16:02) – What's Changed (and What Hasn't) in Enterprise Sales

(16:45) – How to Increase Deal Velocity

(19:39) – Using AI to Improve Your Own Sales Ops

(20:20) – Are You Replacing Jobs with AI?

(23:14) – Building Career-Accelerating Champions

(23:46) – When AI Outputs Go Wrong (Real Stories)

(25:23) – Why the Pilot Never Stops

(29:04) – Pricing AI: Seats vs. Usage vs. Outcomes

(34:48) – Go-To-Market Partnerships That Unlock Enterprise

(37:25) – The Role of Forward-Deployed Engineers

(38:44) – Final Advice for AI Founders Selling to Enterprise