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

In this episode of Founded & Funded, Ben Gilbert, co-host of the Acquired podcast, sits down with Chase Lochmiller, co-founder and CEO of Crusoe-AI, the company building what it calls AI factories, including its massive campus in Abilene, Texas, which are designed to power this new era of intelligence.

In this conversation, Ben and Chase explore the physical reality behind today's AI revolution. Why modern AI workloads demand entirely new infrastructure. How energy has become the primary bottleneck to scaling intelligence. What it takes to compress multi-year building timelines into months. And how Crusoe's energy-first philosophy, from capturing flared methane to siting facilities near abundant wind power, shaped its path to building one of the world's largest AI computing campuses.

This is a must-watch for anyone building in AI or rethinking infrastructure for the next era of intelligence.

Full Transcript: https://www.madrona.com/the-infrastructure-of-intelligence-inside-crusoes-ai-factory-in-texas

Chapters:
(00:00) - Introduction
(02:46) - Scale and Power Requirements
(03:55) - Job Creation and Construction Progress
(05:11) - Creative Solutions and Manufacturing Capabilities
(06:25) - Modular Design and Infrastructure Optimization
(07:42) - Data Center Construction and Assembly Process
(09:07) - Technical Infrastructure and Cooling System
(10:33) - Power Sourcing and Renewable Energy
(11:56) - Wind Energy Utilization and AI Infrastructure
(13:16) - AI Workload Flexibility and Energy Considerations
(14:38) - Entrepreneurial Journey and Company Evolution
(16:11) - Background in AI and Transition to Data Centers
(17:40) - Early Business Model and Bitcoin Mining
(19:14) - Infrastructure Evolution and Future Outlook
(21:17) - Cloud Platform Services

In this episode of Founded & Funded, Madrona Partner Jon Turow hosts a live conversation with Carina Hong, Founder & CEO of Axiom, and Byron Cook, VP & Distinguished Scientist at AWS.

Carina is building foundation models trained on verified proofs instead of human-written reasoning. Byron leads AWS's automated reasoning group, which secures massive infrastructure with mathematically proven systems.

During this live IA Summit conversation, they explore what it means to build AI that actually reasons and why verified intelligence is critical for domains where being right really matters.

They dive into:
1) Why today's models fail at objective truth in high-stakes domains
2) How verification bridges the gap between correctness and scale
3) What superintelligent reasoning engines might unlock
4) The future of AI in finance, chips, healthcare, and beyond

This is a must-watch for any founder or builder working in AI, infrastructure, or high-consequence systems.

Full Transcript: https://www.madrona.com/can-we-trust-ai-the-future-of-verified-reasoning-in-high-stakes-systems

Chapters:
(00:00:00) Introduction
(00:02:01) Meet Carina Hong & Byron Cook
(00:04:07) Why Next-Gen Reasoning Models?
(00:05:59) Objective Truth & Verification in AI
(00:08:03) Formal Verification at Amazon
(00:09:40) Making Proof Tools Usable
(00:11:14) Proofs vs. Bugs: The Mathematical Approach
(00:13:25) The Market for Reasoning & Scarcity
(00:15:41) From Scarcity to Abundance in Reasoning
(00:17:47) AI Mathematicians & Scientific Breakthroughs
(00:19:59) Collaboration: AI & Human Experts
(00:22:16) Lowering the Cost of Creativity & Experimentation
(00:24:08) Broad Applications of Mathematical Reasoning
(00:25:28) Balancing Theory & Practice in AI
(00:28:14) Customer-Driven Investment in Formal Methods
(00:30:31) Building Toward Superintelligent Reasoning Engines

In this live episode of Founded & Funded, Madrona Managing Director Soma Somasegar sits down with Jay Parikh, EVP of Core AI at Microsoft, to unpack the company's evolution from a software factory to an agent factory

Jay leads the team responsible for Microsoft's core AI stack, the systems that power Copilot, the tools developers rely on, like GitHub, and the infrastructure that makes large-scale AI possible. In short, his group builds the underlying tech that Microsoft and thousands of companies use to create AI-powered applications and agents.

In this conversation, Soma and Jay dive into what Jay calls the Agent Factory, which is a new paradigm reshaping how software gets built in the reasoning era. They explore how AI changes the development lifecycle, why observability and evals are becoming mission-critical for enterprises, what it means to collapse traditional engineering functions, and how organizations should prepare for a world where models, agents, and human builders all collaborate in real time.

This is a must-watch for founders, developers, and enterprise leaders who want to understand what's coming — and how to prepare for a world of real-time collaboration between humans, models, and agents.

Full Transcript: http://www.madrona.com/microsofts-agent-factory-the-future-of-ai-software-with-evp-of-core-ai-jay-parikh

Chapters:
(00:00) Introduction
(2:43) Jay's Background & Microsoft Role
(4:33) The Reasoning Revolution
(6:45) From Software Factory to Agent Factory
(8:38) Building the Agent Factory
(10:54) Impact on Microsoft's Future
(12:49) AI Code Generation & Productivity
(14:46) Shifting Engineering Focus with AI
(16:22) Future of Software Development
(18:17) Real-World AI Productivity Gains
(20:18) Microsoft's AI Infrastructure Investments
(24:01) Challenges with AI Evaluation & Observability
(26:12) Model Choices & Microsoft's Strategy
(28:40) Audience Q&A

Where is OpenAI going, and what does it mean for the broader AI and tech ecosystem? Madrona Partner Vivek Ramaswami sits down with Jason Kwon, Chief Strategy Officer at OpenAI, for a rare behind-the-scenes look at the decisions shaping one of the most influential AI companies in the world.

In this live conversation from the 2025 IA Summit, Jason shares what OpenAI will build, what it won't, and how founders can use that as a roadmap to go big without going head-to-head. They unpack OpenAI's ecosystem-first mindset, what "full-stack AI" really means, and how the rise of agentic AI is reshaping what gets built — and by whom.

They also unpack:

• The real reason OpenAI is investing so heavily in compute infrastructure
• How to interpret and work alongside OpenAI's product moves as a founder, rather than fear them
• Why the most compelling startups bet on model progress, not workarounds
• Where OpenAI wants partners, and where it's staying hands-off
• What reasoning + agentic AI unlock for next-gen products
• How OpenAI is navigating its AGI mission while staying product-relevant

This episode is essential listening for anyone building in AI and wondering: Where should I build — and how will OpenAI operate in the space?

Full Transcript: https://www.madrona.com/how-what-to-build-in-the-age-of-openai

Chapters:
(00:00) – Introduction
(01:17) – Jason Kwon's background and role at OpenAI
(02:43) – What is the "full stack of AI"? (Jason's breakdown)
(04:07) – Where founders should build: Opportunities in the AI ecosystem
(05:43) – OpenAI's partnerships and why compute matters
(06:57) – The "reasoning revolution" and agent capabilities
(07:57) – Agentic commerce: Stripe partnership and agent protocols
(09:15) – OpenAI's philosophy: Platform vs. product, and the value of partnerships
(10:47) – What does AGI mean inside OpenAI? Research focus and company culture
(11:44) – How OpenAI decides what to build (and what not to)
(14:42) – Where OpenAI won't build: Advice/opportunity for founders
(17:31) – Q&A: Profitability, business models, and compute margins
(20:00) – How ChatGPT changed OpenAI: Growth, culture, and leadership
(21:20) – Sam Altman's ruthless prioritization and company focus
(23:20) – Q&A: OpenAI's role in commerce and monetization
(24:55) – Q&A: Application vs. model layer, and the Cursor partnership
(26:48) – Looking ahead: What Jason hopes OpenAI will accomplish next year

In this episode of Founded & Funded, Madrona Digital Editor Coral Garnick Ducken sits down with Investor Rasik Parikh to unpack his journey from public markets to venture capital and what makes a founder stand out.

Rasik shares how working across institutional investing, M&A, and now enterprise AI at Madrona has shaped his analytical mindset and founder-first approach. They dive into how to build information asymmetry as an early-stage investor, why storytelling matters more than metrics in early fundraising, and what Rasik looks for in founders.

Founders building in security, agentic software, or enterprise AI — this one's for you.

Watch/listen to learn:
How Rasik evaluates founders and opportunities
The value of tribal vs. common knowledge in startup ecosystems
How early-stage fundraising and M&A share a key ingredient: Storytelling
What's exciting in enterprise AI and security

Chapters:
(00:00) – Introduction
(02:00) – Early career: Institutional investing & M&A
(04:30) – Lessons from the UW Endowment
(06:00) – Public vs. private markets & long-term thinking
(08:50) – Applying an analyst mindset to venture
(10:00) – The role of founders in early-stage investing
(12:00) – Storytelling in fundraising & exits
(14:00) – Rasik's connection to Madrona & Seattle's tech growth
(16:00) – What Rasik looks for in founders: curiosity, awareness, urgency
(18:20) – Security, enterprise AI, and what excites Rasik in tech
(20:00) – Quick hits: How Rasik recharges & Seattle restaurant picks