Life at Strange Loop Labs
Writing down exactly what work looks like at Strange Loop Labs is difficult. A core tenet of ours is Find Problems. Certainly, this is our starting point for how we work with customers. But it’s also something we apply to every part of Strange Loop.
One of the worst traps a company can fall into is inertia. The processes that led to past successes can become untouchable, the assumption made that they are forever integral. This is degenerative. Companies, customers, markets, and technologies change; the best way to work yesterday is often not the best one today. At Strange Loop, we look for problems in everything we do. The way we sell and market our products, support our customers, deal with operational issues, provide performance reviews, hire new people, train our models: all of these are being continually questioned, poked, prodded, and refined in search of a better way of doing things.
Our ability to find problems and experiment with solutions means we are forever learning and improving and changing the way that we work. Nevertheless, there remain a set of tenets, that layer on top of Find Problems, that are always true and transcend each evolution of our company. They provide the best guide to what working at Strange Loop is like.
Always Be Learning
Software and customers are changing constantly, as technologies improve and markets change. Therefore, the only sustainable competitive advantage is the ability to learn.
We continually discover better ways to leverage technology and serve customers. We also continually learn about how our customers work and the challenges they face, so that we can build them better solutions.
Build Quality In
We define a high-quality product as one that works the way customers expect it to and is easy to modify in the future. Adding quality in after a product has been released can be difficult: customers will be using it and finding bugs, which creates support load that steals time away from everything else. Therefore, we build quality in from the start, even if doing so means that a feature takes a little longer to build. The time is paid back quickly.
Always Be Shipping
When we’re building a product, we make a long list of assumptions about how we think customers will use it. Naturally, some of those assumptions are wrong, but we only find out which ones when our product is in the hands of real customers. We therefore try to ship small increments of a product sooner to customers, and seek their feedback as quickly as possible.
Make Incremental Improvements
Our products are never perfect. There is an infinite list of features we could add, and bugs we could fix, and latencies we could optimize to make them better. Unfortunately, though, we don’t have an infinite amount of time to do them all! Occasionally we will schedule time to make a large improvement, but most of the time we focus on making small, incremental improvements as we go. These small improvements compound over time: each one makes the system easier to develop and operate, which frees up more time, which allows more improvements to be made.
Fail Better Next Time
We will fail sometimes. Our services will go down, or our accuracy will be poor, or our features will be too difficult to use. This is a natural part of product development. When it happens, no blame will be apportioned, because everyone involved was already trying to do their best. Instead, in these moments of failure, our focus is on what we can gain from it. We dissect what went wrong, possibly come up with some action items, but above all else learn.
Create Leverage
We deeply embed our engineers with customers, so that we can understand their problems inside and out. Unlike a consulting firm though, we have no intention of hiring thousands of engineers to scale. This means we find ways to create more with less. We do this by building levers into every system we touch so that we can move mountains.
Think About The System
The success of our company is the result of a large, interconnected, network of “things”. There are customers, and engineers, and a CEO, and a CTO, and services, and databases, and machine-learned models, and public clouds, and many more things. All of these interact in unpredictable ways to create a complex system. When we’re doing our work, though, we only operate on one tiny part at a time. This makes it hard to see the forest for the trees. When making decisions, we do our best to think at the level of the system, and do things that will benefit it as a whole.