When I decided to try to write a book, the only certainty I had was that I was not an expert on a lot of topics I wanted to write about. So I knew that to make sure I was writing a book that was correct regarding the industry standard I would need to study… a lot. For instance, I have a whole chapter dedicated on software developers: expectations for each phase of the career, the myth of the superhero developer and the “soft” vs “hard” skills.
Being a software engineer at a new company—anywhere—is hard. The codebase is completely new, you have to adapt to new patterns (for both code and culture) and most likely the problem space is completely new to you too.
Many many moons ago, I wrote a blog post about what was like in my first 6 months at Stripe. Since then, a lot has happened including a whole pandemic and me spending every free hour writing my own book. Because of that and many more things, I never got to write a second piece to what I was initially hoping to be a once-a-year kind of blog post.
Julia is a programming language that I heard a lot for some time now and I knew it deserved my attention. However, a number of libraries and frameworks for machine learning and deep learning keep emerging and I ended up prioritizing them first.
This is the translation of the keynote talk I gave at Pycon Brazil 2022. The talk was about leading complex software engineering projects and what is the major skill needed for the job
My participation in technology communities over the last 3 years, lead me to notice that it’s always tricky to show to companies which don’t interact with this technology ecosystem, how beneficial it is for them to get involved. Many people (developers or not) struggle within their companies, trying to show how much they could benefit from this.