I definitely become more attracted to companies with high quality blog posts on things I'm interested in. The right blog is a really big signal that I'd be interested in the work at the company.
Besides picking the next company, great blog posts can be a real help in sanity checking the work that's happening in our team. I've noticed even senior engineers treating good blog posts from big companies as "See, we're not crazy".
Right now I'm operating in the data science platform space at my company, and have been reading a lot more company blogs than usual. Wayfair is a company I now know of after an engineer I really respect shared on Twitter "Bayesian Product Ranking at Wayfair"[1].
Lyft, on the other hand, disappointed me with "How Lyft Designs the Machine Learning Software Engineering Interview"[2]. That post sounds like it could have been victim to what Dan notes as:
> Approval/editing process mainly de-risks posts, removes references to specifics, makes posts vaguer and less interesting to engineers
I was the eng blog lead at Lyft until recently, and ran it for years. We have a really lightweight process: just needs to be approved by your director, and copy-edited by someone on the blog team. Process usually only takes a week or two. You should probably check out the other posts on the blog.
We aim our posts towards a number of audiences. Our posts related to our interview process are to let candidates know what to expect when they're coming in for specific interview types. We actually get very high traffic to those posts, and we've gotten strongly positive feedback from candidates about those posts, so we've written them for a number of positions.
We also have posts oriented towards working with non-engineering teams, mentoring, engineering processes (like writing tech specs), and other things that aren't only technical deep-dives, because we believe in diversity of content.
Fair enough. So not true that an editing process watered down that particular blog post. I still maintain that that blog post is too wishy-washy, and others agree[1].
I've read other posts on Lyft's blog that are awesome. I did not intend to say that Lyft's blog is bad in general.
Besides picking the next company, great blog posts can be a real help in sanity checking the work that's happening in our team. I've noticed even senior engineers treating good blog posts from big companies as "See, we're not crazy".
Right now I'm operating in the data science platform space at my company, and have been reading a lot more company blogs than usual. Wayfair is a company I now know of after an engineer I really respect shared on Twitter "Bayesian Product Ranking at Wayfair"[1].
Lyft, on the other hand, disappointed me with "How Lyft Designs the Machine Learning Software Engineering Interview"[2]. That post sounds like it could have been victim to what Dan notes as:
> Approval/editing process mainly de-risks posts, removes references to specifics, makes posts vaguer and less interesting to engineers
1. https://tech.wayfair.com/data-science/2020/01/bayesian-produ...
2. https://eng.lyft.com/how-lyft-designs-the-machine-learning-s...