383: From Zero-to-One to a Billion in ARR: Why monday.com Is Rebuilding Its Product Thinking from Scratch, with Daniel Lereya, CPTO at monday.com

Send us Fan Mail

Daniel Lereya is Chief Product and Technology Officer at monday.com, the AI work platform trusted by 60% of the Fortune 500 and valued at approximately $8 billion. He joined the company when it had 30 people and $4.5M ARR, and has since grown his team from 5 to nearly 900 people as monday.com crossed $1 billion in ARR.

In this episode, Daniel draws on nearly a decade of scaling one of the world's most adopted work platforms to share what it actually takes to rebuild product thinking from scratch when AI changes everything you thought you knew.

In this conversation, we discuss:

• Why the instincts that made monday.com successful are the exact ones Daniel says had to be dismantled to build AI-first products. • What the critical difference is between building a demo that impresses and an agent that actually works in production, and where most teams get it wrong. • Why Daniel believes wrapping AI inside rigid workflows produces better results than giving agents full discretion, and what monday.com learned the hard way. • What happened when 2,000 of 3,000 monday.com employees started building their own apps in just two weeks, and what it revealed about the future of who gets to build software. • Why Daniel argues that when an AI agent makes a mistake, the real question leaders should be asking has nothing to do with the technology. • Why the biggest barrier to AI adoption is not the technology itself, and what Daniel says companies must stop waiting for before they start.

Explore:

00:00 Why AI Adoption Is Harder Than It Looks 00:53 Introduction + AI Commerce Standards: Google, OpenAI & Visa 04:30 Daniel Lereya's 9-Year Journey Scaling monday.com to $1B ARR 09:00 How AI Forces a Complete Reset in Product Thinking 12:25 The "AI Month" Initiative: Pausing R&D to Rebuild from Scratch 14:57 Building AI Products When the Output Is Non-Deterministic 20:47 What 250,000 Customers Taught Us About AI in the Real World 25:38 Responsible AI: Guardrails, Governance, and Data Control 31:28 Who Is Responsible When an AI Agent Makes a Mistake? 37:04 The Future of Work: Humans, Agents, and What Comes Next

Resources:

Subscribe to the AI & The Future of Work NewsletterConnect with Daniel on LinkedInAI fun fact articleOn How we can take back control from Big Techhttps://peoplereign.io/podcast/