Engineering at Thread

We’re working hard to create one of the highest quality engineering cultures around.


We work hard to remove anything that gets in the way of shipping great code. This means minimal meetings, zero politics, fast decision making, and freedom to choose which projects you work on. We don’t track hours, and offer unlimited holiday (and expect people to take it!).


Code quality is one of our highest priorities. Not only is great code a joy to work with, it’s the only way to move quickly over the long-run. We take pride in our work, do thorough code reviews, and leave time every week to work on technical debt.


Personal growth and candid feedback is a huge part of our culture. Code reviews, fortnightly one-to-ones, lunch & learns, retrospectives and more happen constantly. We use kanban (with a physical board) for the team experiments we’re currently running.

Thoughtful about Culture

A lot of people in the startup world seem to confuse culture with perks. We see culture as the collection of shared beliefs and behaviours in the team. It’s the fuzzy, intangible thing that keeps people working together well with minimal process.

When looking for new engineers, data scientists and designers to join the team, we’re seeking a heterogeneity of background and homogeneity of values.

Our values are:

  • User experience obsessed
  • Uncomfortably fast
  • Extreme clarity
  • Candour
  • Act like an owner
  • Relentless self-iteration
  • Enjoy the journey together

Having values like these are meaningless if they don’t alter your behaviour. We assess every potential new hire to determine if they share similar values to us. People are rewarded and promoted internally for living them, and every Friday we do a short retrospective to discuss whether we’re getting closer or further away from our ideal.

Company cultures tend to deteriorate as you scale, primarily because the values you had when you were small get watered down. One of our primary goals as we grow is to avoid this—and indeed strengthen as we scale. We all take an active role in this process.

Continuous deployment

One of the founding principles of Thread is we aim to move uncomfortably fast. We prefer to ship MVPs and collect data, rather than have endless debates (which usually end up with the most senior person’s idea being adopted).

This flows into our engineering practices, too, with continuous deployment a key part of process. We’ve pushed more than 80,000 commits in the few years since we founded the company in 2012.

We prefer lots of rapid, small releases for a number of reasons: you can instantly see feedback from users and how metrics are affected, leading to a shorter feedback loop; it’s a lot easier to debug integration errors; and modular development is encouraged.

Our stack and process

Some of the technologies we use to build Thread include: Python, JavaScript, Elm, Django, React, GraphQL, Redis, AWS, Google Cloud, BigQuery, Memcache, Nginx, Ansible, Jenkins, Docker, Gunicorn, Luigi, Pandas, Scikit-Learn, Git.

We’re big believers in free software, use it extensively, and make time to contribute back.

In terms of process, we focus on rapid, lightweight releases. We discuss our company goals as a team and together come up with a plan of how to achieve them. We pick a metric to focus on, build a scoreboard and display it in on a large TV in the office. (It’s really fun watching it move up-and-to-the-right as you release things!) We do weekly sprints, fortnightly retrospectives, track all tasks clearly in Asana, and bake in time for technical debt each week.

Hard technical challenges

Life is too short to solve easy problems. We pride ourselves on taking on and solving extremely difficult technical problems. Some of the current or upcoming things we’re working on include:

  • Using machine learning to learn someone’s preferences and recommend the perfect clothing for them.
  • Algorithmically determining which size will fit a user perfectly.
  • Automatically detecting the optimal frequency and timing to email users based on historical behaviour.
  • Building systems to scrape millions of URLs per day.
  • Scaling to millions of customers and thousands of orders per minute.
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