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How Warp Went From YC to a $60M Series B

Warp (YC W23) recently announced a $60 million Series B and now serves more than 1,000 customers, processing over $600 million in payroll annually and on track to surpass $2 billion in the next year. In this episode of Founder Firesides, YC's Harj Taggar sits down with Warp founder and CEO Ayush Sharma to discuss how the company found its way into one of enterprise software's most competitive markets and why AI is fundamentally changing how software companies should be built. https://www.joinwarp.com Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs 00:50 - From India to MIT 03:10 - Betting on an Unsexy Problem 05:18 - The Wedge That Started Warp 09:49 - What "AI-Native" Really Means 12:31 - Building a Different Kind of Company 14:00 - Why AI Favors Technical Founders 16:42 - The Next Generation of Enterprise Software 21:25 - Why Investors Backed Warp 25:11 - The Future of Employee Management

Harj TaggarhostAyush Sharmaguest
Jun 26, 202626mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Warp’s AI-native HR platform: from payroll wedge to $60M growth

  1. Ayush’s founder journey runs from a small town in India to MIT, where he specialized in machine learning before turning to startups.
  2. Warp began after the team abandoned a consumer social app and chose an “unsexy” schlep problem: automating painful payroll and compliance setup for fast-growing companies.
  3. The initial wedge—multi-state payroll tax compliance—was timed to remote-work complexity and is structurally harder than sales tax because a single employee triggers full compliance obligations.
  4. Warp’s definition of “AI-native” goes beyond AI features: it aims to run compliance and operations with agents so the company and its customers don’t have to scale headcount linearly.
  5. Investors (Battery-led) moved quickly as “AI-native HCM” emerged as a major enterprise category lacking a clear next-generation leader, and Warp positioned itself as both system-of-record and system-of-intelligence.

IDEAS WORTH REMEMBERING

5 ideas

An “unsexy” compliance problem can be a powerful wedge.

Warp deliberately targeted messy payroll tax and compliance workflows that many founders avoid, betting that high pain plus complexity creates room for a new platform to win.

Multi-state payroll complexity is a structural tailwind post-COVID.

As distributed hiring became normal, compliance triggers earlier; unlike sales tax thresholds, payroll compliance can start with hiring just one person in a jurisdiction.

AI-native means redesigning the company, not just the UI.

Ayush contrasts incumbents staffing 30–40% of headcount in support/ops/compliance with Warp handling broad jurisdiction coverage with roughly 1–2 tax specialists by using AI automation.

Systems of record stay valuable, but risk being relegated to “dumb databases.”

Ayush argues incumbents like Workday face the danger that external agents orchestrate the real work while the system-of-record becomes commoditized storage.

The defensible frontier is “systems of intelligence” built on trusted records.

Warp’s strategy is to combine shared-truth data with native agents, permissioning, guardrails, and workflows so the orchestration layer is inside the platform, not outside it.

WORDS WORTH SAVING

5 quotes

I just remember one of the days that I spent-- I think I had all these fires going on in the company, and then on top of that, I had to, um, figure out how to make, like, a New York withholding and Department of Labor's account. Um, and it was one of the most frustrating things I ever spent my time on. And I was like, "There's no way nobody has com- tried to completely automate this."

Ayush Sharma

I think in some ways I was motivated to start it because it is unsexy.

Ayush Sharma

But in payroll, you just need one person. You just need to hire one person in one jurisdiction, and you have to comply with the entire tax jurisdiction apparatus.

Ayush Sharma

Up until recently, we had only one, one and a half tax person. One full-time, one part-time.

Ayush Sharma

I think that net-net, I believe that with AI, it's in favor of technical founders.

Ayush Sharma

From India to MIT and ML backgroundPivot from consumer app to B2B payrollSchlep blindness and “unsexy” problem selectionMulti-state payroll as a wedge vs sales taxAI-native/agent-native platform architectureSystems of record vs systems of intelligenceSeries B preempt and roadmap: benefits, IT, device management, customer agent

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