Being faced with an important choice that feels impossible to know the answer to is stressful! This comes up a lot when making business decisions, but also applies to technical choices (e.g. “should my company run 100% on AWS” or “is serverless a fad or a great idea?”).

Documentation can make a big difference. Internal documentation can speed your team up and makes it easier for new engineers to get up and running. External documentation reduces time spent on support questions, and makes your product more usable.

There are many exciting things happening with AI, from which, until recently, JavaScript developers were largely shut out. But things are changing, if you can do `npm install @tensorflow/tfjs` or make an API call, you can now do AI.

We’ve all read the articles and got excited by technologies such as machine learning, deep learning, Tensorflow, Panda and NumPy. A lot of us are also looking at how to incorporate these technologies into our toolset and in the software we are building.

There’s a lot of talk nowadays about the impact that artificial intelligence (AI) will have on testing. There’s a new generation of testing tools being developed that employ AI with promises of making testing much more efficient for us.

Over the past few years, I’ve gained expertise in front-end web architecture. I’ve done this work at Indiegogo, Headspace, for my open source mental health project if-me.org, and in my current role at Mailchimp.