Beyond Coding

Some of the topics we cover this episode, in order: ☑️ The power of the right environment ☑️ Evolving software vs rebuilding it, and the not invented here syndrome ☑️ Trust is very complex ☑️ What does 100% unit test coverage mean? ☑️ The sweet spot of quality and speed My favourite quotes from Albert Brand this episode: - "Are you really going fast when it slows you down later?" - "Isn't speed just another quality?" Enjoy!

Some of the topics we cover this episode, in order: ☑️ Solving practical problems for engineers ☑️ Code reviews are becoming a big problem in our industry ☑️ Leveraging tools to better understand code ☑️ A startup with developers as target audience ☑️ Remote company culture Enjoy!

Some of the topics we cover this episode, in order: - The what and why of Psychological Safety - High performing teams - Awareness of how you act and communicate - Imposter Syndrome - The value of personal feedback

Some of the topics we cover this episode, in this order: - Tips when just starting out - Going outside of your comfort zone - The Full Stack term - The challenges of forming a great team - Stability versus Experimentation - The benefits of teaching

Some of the topics we cover in this episode:  - What Modular Software Development is - When to split your application, and how to split it - The role of Software Architect in a cross-functional team - When and how organisations adapt new tech - Hire for mindset, train for skill, and the joy of working in diverse groups

After seeing the title, you might wonder: "What is MLOps?". That's also what I was thinking... But no worries, Roman and Julian explain exactly what it is! On top of that, we go over how to bring your machine learning model to production, the right way, and some of the challenges you might face along the way.  This episode was recorded live in collaboration with GoDataFest: Festival of Data Technology, and Club Cloud: Global Cloud Festival! Because it was recorded live, the intro is slightly different than what you're used to :) Enjoy!

You might've heard of this new-ish kid on the block: Kotlin! And like all programming languages, it's a tool to get the job done. There is no "right" pick, just pros and cons, and Kotlin is no exception. However, the pros of Kotlin certainly make it sound appealing. One of the main benefits that stood out to me from this conversation is very simple: code clarity. If the use of Kotlin as a language creates clarity for the engineers and teams that use it, it's a very powerful tool that contributes to their productivity. Enjoy!

Pull requests (PRs), the standard way to collaborate in codebases to ensure quality (among other things).. It turns out that they're actually slowing down software development. But how?  Dragan explains how the problem lies in the way it's structured: it's asynchronous. There's a lot of time that passes before the code is merged, and the value is delivered. Large PRs are hard to review and course correct, and small PRs can introduce lots of context switches. However there are ways around this, to have both speed and quality. These ways lie in co-creation: Pair and Mob programming

The idea of a "10x engineer" is popular in Silicon Valley and is used to refer to a rare engineer who can achieve 10 times more than an average developer. We invited Chris Laffra on to discuss this idea, and as you might've guessed, it has to do with making other people more productive. But before doing that, you'll need to focus on your individual productivity and impact, and maximise that to a certain degree.  Sounds interesting? Listen in to find out more! PS: Chris gave me a copy of his book: Communication for Engineers, and in there he wrote: "To be happy, make other people happy". I love it!

As you might know, not every software engineer comes from a computer science background. But why is that? Well.. if you want to learn how to program, there’s not a lot that’s stopping you. Especially nowadays, there’s a lot of content, or even courses and companies, that’ll help you along the way. And as more and more jobs (or parts of jobs) get automated, it might be help to learn about how that automation works in the first place. Just like how we learned to do a lot of math before using a calculator. Caught your interest? Listen in!