Episode 109: Developer Productivity, Real-Time Data Infrastructure, and The Fat-Tailed Nature of Enterprise Software with Nnamdi Iregbulem

Show Notes

(01:32) Nnamdi shared formative experiences of his upbringing, where he spent countless hours building computers, coding up websites, and finding ways to game Google search.

(04:54) Nnamdi described his undergraduate experience studying Economics at Yale University and interning at McKinsey and J.P. Morgan.

(08:10) Nnamdi reflected on the decline of the investment banking industry - given his one year working for the technology, media, and telecommunications group at J.P. Morgan in New York.

(12:52) Nnamdi discussed his career transition into venture investing at ICONIQ Capital, where he deployed over $500 million into high-growth technology companies.

(15:00) Nnamdi reflected on his proudest accomplishments during his four formative years at ICONIQ.

(17:35) Nnamdi talked about his excitement for GitLab, one of his investments.

(21:27) Nnamdi touched on his time getting an MBA from the Stanford Graduate School of Business.

(24:21) Nnamdi also completed coursework in Stanford's Computer Science department (such as CS 231N and CS 224N) during his MBA.

(26:37) Nnamdi explained the venture ecosystem at Stanford, given his experience serving as the Co-President and Vice President of the Venture Capital and Tech Clubs, respectively.

(28:57) Nnamdi unpacked his experience working at Confluent as a product manager and conducting independent research on trends in developer productivity.

(32:23) Nnamdi reflected on his decision to join Lightspeed Venture in mid-2020, investing in early-stage software startups to enhance the productivity of technical knowledge workers.

(34:17) Nnamdi shared how he proved his value upfront in potential deals and started forming his investment theses as a new investor at Lightspeed.

(36:24) Nnamdi dissected the key factors that triggered him to make investments in the seed rounds of Ponder and Voltron Data (in the domain of developer tools).

(40:36) Nnamdi explained his Series A investment in Redpanda and Materialize (in the domain of real-time data infrastructure).

(45:45) Nnamdi shared advice he had been giving his portfolio companies in hiring decisions and navigating growth strategy.

(49:07) Nnamdi walked through his 3-part series on major industry trends, top strategic priorities, and biggest challenges for software and infrastructure startups pushing the developer productivity frontier.

(52:37) Nnamdi shared advice to startups thinking about scaling their developer relations, given the challenge of hiring developer advocates for dev-focused startups.

(56:27) Nnamdi unpacked his 3-part series on the developer productivity manifesto that introduces the developer productivity flywheel, explains how more developers lead to lower productivity, and argues that we are leaving on the table $670B of software by not maximizing developer employment and developer productivity.

(01:01:26) Nnamdi examined his obsession with the fat-tailed nature of high-growth startups, such as why VCs don't index-invest, why Saas monetization is concentrated on the tails, and why product-market fit gets harder to achieve the longer you search for it.

(01:04:26) Nnamdi explained his new and improved SaaS metric called Weighted ACV, which is the weight of the revenue that a customer represents and tells founders where to look if they want to best understand the revenue of their businesses.

(01:07:53) Nnamdi thought about his recognition as equal to his credibility as an investor on a mission to increase total software output by investing in technical tools for technical people.

(01:11:03) Closing segment.

Nnamdi's Contact Info

Lightspeed's Resources

Notes

My conversation with Nnamdi was recorded in May 2022. Since then, many things have happened. I'd recommend checking out:

About the show

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com.

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

About the show

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email khanhle.1013@gmail.com.

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.