corvus-cornix

Some of the formatting for emphasis and em-dashes looked a bit iffy. It's hard to imagine AI wasn't involved, at least an an editor or to discuss ideas. To be clear, I don't think there's necessarily anything wrong with this.

I feel like Go has a similar role to Java. Although it's mercifully free of inheritance and the functional stuff they've bolted on.

Rust has a similar role to C++ but reads more like Python and Elixir's lovechild.

I'm looking at engineering job specs at the moment and it's very wearisome that every company seems to have pivoted from highlighting the unique value they provide to customers to putting AI front and centre in their employer branding. My eyes immediately glaze over at what may have been the result of "Claude, take this HR/marketing/whatever copy and inject some AI".

I've adopted the tools because they're useful, but businesses need to chill. AI seems to amplify existing bottlenecks within organisations, so we should probably tread carefully when it comes to pushing the tech. Fix the organisational problems first and hedge our bets.

I wonder if anyone reading this was around during the dot-com bubble because maybe it felt the same...

Data recently scraped from Glassdoor and Crunchbase.

I've also found LLMs to perform poorly at DevOps tasks. Perhaps there's a lack of training data. On the bright side this hints at better job security for platform engineers.

Goal: Setup a minimal working example where pods in GKE and EKS can access two buckets, one in S3 and another in GCS with no static credentials or runtime configuration. In other words, running the below commands should just work from within a pod in both clusters: