Rethinking hiring at an early stage deep tech startup

In October of last year, we made a conscious decision to pause our traditional hiring practices. Instead, we embraced a paradigm shift by introducing finite tasks at fixed rates within our community. The driving force behind this change?

Let me walk you through the thought process...

Breaking Traditions

In the early 2010's I founded a company called Nodejitsu — a platform as a service for Node.js and a competitor to Heroku. Nodejitsu was an unusual company for a lot of reasons. One thing was, Node.js was far from production ready. It was a big risk. But we were sure it would stabilize, and it did. Nodejs turned out to be one of the largest and most successful open source projects in history. We made a good bet.

Another unusual thing was, we were a remote-first company. At that time, remote-first companies were mostly unheard of. It gave us an edge, because we could hire the best people from anywhere. And with modern tools, productivity was easy to measure, and feedback loops stayed tight. Another good bet.

Unearthing Inefficiencies

Since then I've leaned into remote-first and async communication, and it's paid off. But remote or not, full-time people have significant hidden costs. People go idle — even with clear goals and excellent incentives, productivity fluctuates. People burn out. People have personal issues. They introduce entropy. Another thing is, an employee's life can't and really should not revolve around their job.

Pioneering a New Era

Over the past decade, the landscape has transformed dramatically. The market is overflowing with talented developers, each brimming with enthusiasm to tackle intriguing problems.

Our product is "deep tech"; what we're building hasn't been built before. It takes an unusual breadth and depth of many different skills to build project like this.

Introducing finite tasks at fixed rates has proven to be a game-changer. It brings clarity to expectations, planning, and budget forecasting, leaving no room for idling. This approach mitigates burnouts, minimizes political maneuvering, and reduces interpersonal conflicts. While acknowledging that the fractional-first model might not suit every deep tech product, it's undeniably propelling us forward at an accelerated pace. 🚀