In a software-driven world, attracting and retaining top tech talent — from software engineers to data scientists — is becoming table stakes for teams looking to gain a competitive edge. But amid labor shortages, companies are now turning to software developer tools to help their teams do more with less. Nnamdi Iregbulem, partner at Lightspeed Venture Partners, explores how democratizing software development and investing in productivity tools can make teams more efficient.


Why is developer-centric productivity tooling such an important category moving forward?

  • Tech-skilled labor shortages necessitate tooling that optimizes developer output. The demand for technical talent continues to rise as software increasingly becomes an integral part of every industry. Developer tools not only enable existing technical talent to operate more efficiently, but also lower the barriers to software development for non-technical talent, creating immense value for companies looking to improve productivity across the board.

What are the business models that might be attached to this category?

  • Open-source models are the standard, but other business models with higher growth potential are emerging. “Open source is still a common business and distribution model for technical tooling and infrastructure, but companies are increasingly asking themselves whether or not they truly need to be open source,” Iregbulem says.
  • ‘Source-available’ hybrid distribution models help vendors benefit from community building while maintaining a competitive moat. “The vendors get the same benefits of open source regarding transparency that engenders customer trust and broader community building, while avoiding giving away too much for free or creating strategic risks/incentives for competitors to offer a modified version of their solution,” he says.
  • Consumption- and usage-based billing models are proliferating as they enable vendors to wedge into lower value markets. Customers only pay for what they use, directly tying cost to the actual value delivered. “As a vendor, consumption pricing often enables you to sell to customers with lower initial contract value, easing friction and reducing potential objections for cost-conscious customers,” he says. But forecasting challenges present risk: “Unless you have a very good sense of your organization's usage patterns, costs can quickly spiral out of control."

What are some of the potential roadblocks?

  • “As tooling matures and platform products emerge to offer suites of capabilities under one roof, startups face an increasingly hostile competitive landscape,” Iregbulem says. “In domains where seat-based pricing is common, incumbents can offer extremely low pricing on a per-developer basis, setting the bar for the rest of the market.” Startups are facing tougher go-to-market conditions as they try to compete at prices below their marginal costs. “In addition, developers nearly always have free alternatives to paid solutions. Given their own technical skills, they tend to be more willing to go DIY – crafting an in-house solution that still gets the job done.”
  • Adoption could fall flat if organization’s are unable to move beyond hype and establish actual use cases. “For example, despite all the excitement, hype, and promise for machine learning within the enterprise, most organizations are running few, if any, of the ML models in production." Many in Silicon Valley are still surprised by the number of companies that are yet to transition to the cloud. “Innovative technologists and startups are biased toward the future and perennially ‘ahead of their time’. They often build tomorrow's solution today. This can lead to over-investment ahead of real demand, which has been a major underlying story of the last decade of technical tooling, especially the last few years."

Despite all the hype for machine learning within the enterprise, most organizations are running few, if any, ML models in production.

Nnamdi Iregbulem~quoteblock



saidbyblock~ via Email Correspondence
Nnamdi Iregbulem

Stripe's mission is to grow the GDP of the internet; mine is to increase total software output. Every company is becoming a software company, but not every worker is technical.

While the ranks of software engineers, data scientists, and other technical knowledge workers have risen significantly over the years, demand for these individuals has completely outstripped supply.

As a result, we have a severe labor shortage among technical talent, a critical risk for the future of the software economy. Most companies struggle to hire developers, as the competition is fierce. Big tech companies can offer salaries that mere startups cannot afford.

If we think startups are the most innovative sector of the economy, constraints on their ability to hire developers mean less software gets shipped as a result. If we want to grow software output and shipped code, but we can't grow inputs like technical talent, our only recourse is to substantially improve the productivity of current and future technical workers.

That's why I look at every investment through the lens of productivity — how does this product or tool help organizations ship more code without more people? Better tooling also opens up software development and data science to a larger group of people, attracting more bright individuals to our industry and helping alleviate some of the talent bottleneck.


Q: What do other market participants or observers misunderstand about these categories?:

A: "Investors often underestimate how much better a new technical tool has to be, relative to the status quo, in order to capture the hearts and minds of users. Developers and data scientists are inundated with tooling. There's a new shiny object practically every day, and it's often a coin flip whether or not they actually enhance productivity rather than merely distract from the core work.

In this context, it's quite difficult to separate from the noise. It's a little bit like the mobile market today compared to when smartphones originally came out. I remember getting my first iPhone and immediately going to the App Store and loading it up with apps. I'd check the App Store every day for new things to play around with. But over time, one's app use stabilizes around a few core applications, and the rate at which you download new apps collapses. At this point, I visit the App Store once a month at best, and usually just to download a particular app, not to browse idly.

Likewise, while technical knowledge workers are often early adopters who like trying out new things, it's extremely rare that they actually change their "starting lineup" of tools. ‘10X better’ is really just the minimum in this category."

Investors often underestimate how much better a new technical tool has to be, relative to the status quo, in order to capture the hearts and minds of users.

Nnamdi Iregbulem


Contrary to popular opinion, public cloud providers are unlikely to cause major competitive disruption within the productivity tooling space. Public cloud providers are mostly concerned with “infrastructure consumption, which maps most directly to compute, storage, and networking,” Iregbulem says. Productivity tools consume many fewer resources than infrastructure solutions, making them less attractive targets for the public cloud players. Those large cloud companies are also much better at architecting infrastructure services than they are at building developer-facing products. Here, companies like Atlassian, GitLab, and GitHub have the advantage, especially given their focus on building communities — an element that “continues to be a strong competitive moat for developer-centric startups,” he says.


The 2022 EVC List honors the top 50 rising starts in venture capital. Terra Nova’s Thesis Brief series showcases each investor’s insights and category expertise.

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