No Priors Ep. 122 | With Rippling Co-Founder & CEO Parker Conrad
Parker Conrad’s Founder Journey and Lessons from Failure 00:03
Conrad reflects on his previous company Zenefits, attributing its failure mostly to “dumb reasons” rather than deep lessons
Emphasizes Rippling’s strict approach to regulatory compliance due to Zenefits’ issues in that area
At Rippling, there’s an aversion to operational overhead—preferring deep software investment over manual processes, even if sometimes it’s to their detriment
Suggests that learning from success is more valuable than learning from failure, as failures often happen for arbitrary reasons
Says starting a company was sometimes less about burning ambition and more about having few other viable career options after a setback
Recounts the psychological toll of a failed company and how, at Rippling, the worst moments always felt less dire in comparison to those at Zenefits
Advises against starting companies unless necessary, due to failure being glamorized and the personal cost often being underestimated
Notes the emotional grind and focus required in early company years; initial anger and determination faded over time, replaced by motivations like love for the product and team
Acknowledges that maintaining ambition is challenging, but over time the motivation evolves
Rippling’s Platform Strategy and Contrarian Approach 07:59
From the start, Rippling set out to build a broad, seamless suite of integrated applications (HR, IT, identity, etc.), rejecting the trend of narrow, focused SaaS solutions
Conrad argues that solitary, narrow solutions can’t fund deep investment in foundational capabilities (permissions, reports, analytics, workflow, etc.)
Asserts that platform-based approaches allow for much better customer experiences and R&D leverage
Notes that building with a platform philosophy is how industry giants like Oracle, SAP, Salesforce, Microsoft, and Epic became dominant
Attributes the SaaS era’s focus on niche solutions to the cloud shift that enabled quick wins but believes the bar has risen and integration is now essential
Suggests investors’ expectations for rapid progress favored point solutions, but this window is closing as comprehensive solutions become required
Rippling is structured with both platform teams and application teams, with emphasis on hiring leaders (often former founders) who take full ownership
Seeks individuals who can independently drive outcomes, not just execute narrowly defined tasks
Values people who can tackle seemingly impossible challenges by creatively bridging gaps between organizational goals and real-world constraints
Encourages setting high expectations and believing in people’s abilities to accomplish more than they (or others) assume
Rejects binary “A or B” choices—prefers seeking solutions that accomplish multiple objectives simultaneously
Internal Organization, Coordination, and Ownership 19:00
Notes it’s hard to perfectly filter for “ownership mentality” when hiring; often this emerges through individuals who proactively synthesize problems and find solutions
Pushes for responsibility to be shared deeply within the org, motivating people with the real stakes of achieving company goals
Describes the persistent tension and negotiation between platform and application teams regarding whether to build on shared systems or develop specific features independently
Explains the math: platform investment benefits every product, making it more efficient and vital for scaling versus siloed, disconnected solutions
Competitive Dynamics and Balancing Expansion 27:45
To beat incumbents, Rippling pushes into new horizons by building products and features existing vendors can’t match, often blurring the line between “new” and “bug fix” from the customer’s view
Over 80% of engineering is devoted to maintaining and expanding existing products; only a small fraction is focused strictly on new initiatives
Lean teams are used for new products, leveraging the platform to get further with less headcount
AI’s Impact on Software, Engineering, and Support 30:36
Skeptical of claims that AI will radically reduce engineering headcount in the near term; has not seen major productivity gains from AI coding assistants
Believes that as software development gets easier, the demand and complexity of software will increase, requiring more verticalization and, ultimately, continued investment and hiring
Predicts increased specialization (e.g., “Rippling for ophthalmology clinics”) as building tailored solutions becomes more accessible
Maintains that as the ability to build and support software improves, competitive bar rises, requiring more people at the cutting edge for both engineering and go-to-market
Rippling is “allergic” to operationally intensive solutions due to past experience; prefers automating and scaling through software from the outset
Cautions that retrofitting software to existing manual processes at scale is very difficult and can lead to ongoing operational debt
Emphasizes the importance of determinism in automation for areas like payroll, where correctness is non-negotiable and edge cases proliferate
Data, Governance, and Strategic Durability in the AI Age 40:10
AI’s rise increases Rippling’s focus on data and robust governance
Building AI applications is relatively straightforward compared to building secure permissions, governance, and data pipelines—Rippling’s core platform strengths
Permissions and governance are closely tied to understanding org charts, job roles, and ensuring AI agents properly inherit human user permissions and restrictions