We all want to deploy the best software possible to delight our customers and please our product owners. There’s always one more feature, another performance improvement, and code we just wish we wrote better.
When Chuck Yeager became the first pilot to fly faster than the speed of sound, he set off a race around the world to do the same with a plane full of paying passengers. The United States, Russia, the UK, and France all wanted a piece of the inevitable fortune to be made building aircraft to cross oceans faster than sound itself.
We’ve all had that experience where we’ve planned the perfect discussion only to have it hijacked by a passionate side-person, lose focus halfway through, or produce the exact same takeaways as you had before you began the discussion.
Friction is a common, and necessary, part of team growth—but when left unchecked, team friction is unhealthy for you, your coworkers, your company, and ultimately your end users.
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.
When bootstrapping new teams, they need to go through the standard process of forming, storming, norming and performing. And in the context of fast-growing companies, with their own level of uncertainty, how can we achieve high performance when teams and goals are constantly changing?
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.
It’s all well and good for the agile manifesto to recommend self-organising teams, but what does that actually mean in practice? What’s the best way to do it, how far should you take it? Total anarchy is probably not the answer here… right?
How many talks, articles, and podcasts have you seen about organizational change, and how to implement it? How many of them talked about what we can learn from non-human psychology? This is that talk.