Newsletter #20: How big tech tuns tech projects and the curious absence of Scrum
Featured posts from Eventbrite, Algolia, and More
As always, you can read my top discoveries for the last month below. If you like this newsletter, please forward it to others who might be interested.
Companies take different approaches to run technology initiatives. Some companies go all-in with methodologies like Scrum. Some don’t. Others take a bit of a framework that works for them. But how should you run a tech project? No matter how small or big your organization is, there is something to learn from this post. It contains an overview and insights from a survey with over 100 companies represented with key takeaways.
I’m yet to meet an engineer or an individual contributor who loves meetings. Engineers are busy people and have to save as much time as possible. Therefore, we like to be concise and straight to the point. But concise communication isn’t the most effective one. If all we do is laser-focussed, one-sentence communication, we rob ourselves of the impact of what we’re trying to communicate on others. I find this post interesting because it contains practical examples of adapting communication depending on the audience.
Success without a successor is a failure,” they say. To lead effectively, you must develop others to do what you do. As Daniel Micol, a technical fellow at Eventbrite, puts it, “to grow, you need to find or grow other people to do what you’re doing now, so you can then become dispensable and start focusing on something else.”
I like the model presented in this post. It highlights how Daniel Micol scaled his involvement among roughly 40 engineering teams at Eventbrite. If you’re leading multiple engineering teams, this is a good read.
As use cases are different, there is no one-size-fits-all approach for building a recommender system. Depending on the nature of the problem you’re trying to solve, you might find one approach fitting than others. This article from the head of research and development in Algolia describes techniques for building a recommender system.
The modern transformation has made enterprises proficient API machines. If you’re an engineer, chances are you’re spending a sizable amount of your time crafting APIs or consuming APIs in one way or the other. Having worked with APIs for a while, I believe it’s essential to spend some time in the API design phase to avoid some common pitfalls in API design.