How Warp Went From YC to a $60M Series B
Warp founder & CEO Ayush Sharma discusses building an AI-native employee management platform in a competitive market, detailing how "unsexy" payroll problems became a powerful wedge and why AI fundamentally shifts enterprise software development. He explains what "AI-native" means for product architecture and company structure, the advantage it gives technical founders, and Warp's vision for "systems of intelligence" to empower customers with AI agents for complex HR workflows.
Ayush Sharma, founder and CEO of Warp—an AI-native employee management platform for high-growth companies—shares his journey and profound insights into building a company fundamentally reimagined with artificial intelligence. Warp, which now serves over 1,000 customers and processes over $600 million in payroll annually, recently secured a $60 million Series B round.
The Origin Story: From Theoretical Physics to “Unsexy” Payroll
Sharma’s path to technology was unconventional, beginning in a small town in India with an early passion for theoretical physics, inspired by Richard Feynman. Despite traditional societal pressures to pursue engineering at top Indian institutions, he pivoted to MIT, specializing in machine learning. His initial entrepreneurial foray was a consumer social app, a common starting point for young technical founders. However, he quickly recognized its limitations for becoming a “really big company.”
This realization led to a crucial strategic shift: identifying and solving “unsexy” problems. Drawing inspiration from Paul Graham’s “schlep blindness” essay and the early days of Stripe, Sharma and his co-founder Adam (Warp’s CTO) recognized the immense frustration and complexity involved in setting up basic corporate functions, such as navigating New York tax withholdings and Department of Labor accounts. This messy, complex, and often overlooked problem became Warp’s initial focus, seeing an opportunity for automation with emerging AI and LLMs (Large Language Models) around 2022-2023.
The Payroll Wedge: A Non-Obvious Moat
Entering a competitive HR tech market, Warp’s initial “wedge” was simplifying multi-state payroll. This strategy, initially met with skepticism during their Y Combinator interview, proved effective due to evolving market dynamics. The increasing prevalence of remote work meant companies were becoming multi-state much earlier in their lifecycles. Crucially, payroll taxes present a far greater compliance burden than sales taxes: while sales taxes often have high thresholds, payroll requires full compliance for even a single employee in a new jurisdiction, navigating thousands of disparate tax regulations. This exploding complexity, combined with the emerging power of LLMs and AI agents, created a significant opportunity that traditional software struggled to address.
What it Means to be “AI-Native”
Sharma defines Warp as an “AI-native employee management platform,” signifying that both its product and its underlying company structure are built from the ground up for AI. This involves two key realizations:
- Comprehensive Platform: Customers, especially scaling startups lacking in-house HR or legal teams, demand an integrated platform that grows with them, covering all aspects of employee management beyond initial payroll.
- Agent-Native Architecture: The entire platform is designed so that all work, particularly deep tax compliance workflows, can be performed by an AI agent. This aims to deliver significant efficiency gains, enabling high-growth companies to scale without linearly increasing their people operations, HR, or finance teams.
Sharma illustrates this difference with a stark comparison: legacy HR tech companies often allocate 30-40% of their headcount to support, tax compliance, and operations. In contrast, Warp, serving over 1,000 customers across all U.S. tax jurisdictions, managed with only 1.5 tax specialists until recently, a testament to its AI-driven automation. This allows Warp to build a fundamentally “different kind of company” with a lean, efficient operational structure.
AI and the Shifting Landscape of Enterprise Software
Sharma argues that the AI era fundamentally favors technical founders. Unlike the “mega-SaaS” era, which he found “boring” and advantageous for distribution-focused founders, AI empowers technically deep founders to build entirely new solutions, unburdened by existing paradigms. He posits a “race” between AI-native upstarts and incumbents: can new entrants become the next-generation foundational software before existing players can effectively retrofit AI onto their legacy systems? He believes retrofitting is challenging, often resulting in “thin chatbots” layered on old architectures. The struggles of companies like Workday, whose stock is down significantly from recent highs, are cited as evidence of the market’s recognition of this architectural vulnerability.
This leads to a discussion on “systems of record” (shared truth databases like Salesforce CRM) versus the emerging “systems of intelligence.” While traditional systems of record offer defensibility, Sharma notes that many SaaS solutions are vulnerable to AI disruption. The risk for incumbents like Workday is becoming a “dumb data store” accessed by external agents, moving all value to the orchestration layer. The future, according to Sharma, lies in systems of intelligence: platforms where agents can natively act on the underlying database with built-in “shared truth,” guardrails, workflows, and permissions. This is where Warp aims to be, building a “super powerful capable system of record platform that is on day one built with intelligence in mind,” recognizing that “most of the API docs are now being read by agents,” and “agent traffic… surpassed human web traffic.”
The Future of Employee Management with Warp’s AI Agent
Warp’s recent $60 million Series B, preempted less than a year after its Series A, reflects investor confidence in its AI-native approach to HCM (Human Capital Management), a category where a clear AI-native challenger was missing. The funding will fuel two critical objectives:
- Platform Expansion: Build out a comprehensive, delightful platform for “all things employee management,” including benefits brokerage (Warp is fully licensed nationwide), in-house device management (a rarity outside of Rippling), global contractor products, and core HRIS functionalities, all with robust integrations.
- Agent Infrastructure: Develop the most capable agent harness and infrastructure for AI to reliably and trustworthily act on sensitive employee data within Warp.
Sharma is particularly excited about the upcoming full general availability (GA) release of the Warp customer agent. Historically, Warp used AI in the background for compliance. Now, this infrastructure will be exposed directly to customers, allowing them to perform any action traditionally done by clicking buttons, but via natural language. This enables complex, customized workflows—such as automatically onboarding a new New York employee by adding them to specific healthcare plans, sick leave policies, provisioning devices, and ensuring state-specific training—all without requiring coding expertise. This empowers customers to automate and optimize their HR processes with unprecedented efficiency.