Digests » 55


Swarmia helps you ship faster without compromising culture or quality

Best engineering teams get better all the time. Swarmia lets you measure your ways of working and adopt team habits followed by industry’s best performing organizations.

this week's favorite

The case for 'Developer Experience'

There’s been a lot of buzz around APIs, “no code,” and “low code”: Developers can add new features more easily than ever before! While it’s true that this new wave of tools has helped developers build bigger systems, and build them faster, it turns out that developers are now spending their time worrying about an unintended consequence: How exactly are they supposed to manage and coordinate these fast-moving, heterogeneous systems — and free themselves to build?

The mentorship diamond

For almost everyone in our industry: there is someone around who has more experience than you. That person will have some things you can learn from them.

“Get off the Floor” and other career advice from Microsoft, Looker, Reddit & Twitter

Dig into Nick Caldwell’s resume, and you’ll see leadership posts at an enviable list of startup staples — Reddit, Looker, and now Twitter. But less typical these days is the 15-year stint he put in at Microsoft beforehand. His tenure at the company culminated as a founding member and eventual GM for Power BI, one of the company’s biggest success stories. It was only after accumulating this deep bedrock of experience that he took on his first startup role at Reddit, where he led the engineering team through hypergrowth, scaling from 35 engineers to 150.

How many people can someone lead?

My answer is generally 5-7 people for an experienced leader, but many factors affect the final number. Some of these factors include their leadership scope, other leadership roles, the experience level of the leader, the experience level of the team, and the level of organisational bureaucracy.

On making architectural decisions

It’s hard to argue that the same goal can be achieved by different means. Without restrictions, any decision will be acceptable, and the choice of a supplier of certain technologies, development approaches and utilized patterns and platforms will not have a fundamental impact on the success of the goal.


FREE Guide to Harnessing Distributed Compute in Python

Learn about the growing demand for distributed compute, typical data science working environments, why iteration and speed are critical, and examples of workflow challenges. Instantly download your copy now.

Join over 6,500 readers for a free weekly email with fresh news, articles and tutorials.