If you haven’t played with Pulumi (for configuring cloud services) and Ansible (for local services, shell commands, apt installs etc) you may enjoy them as a way to capture / re-apply configuration.

I do do interviews too. It’s a lot of time and work. A well designed interview can and should be a realistic, rewarding problem solving session where you get to try out collaboration with potential colleagues.

Cheating leetcode interviews with AI doesn’t seem that innovative to me, just adding dishonesty to a broken practice. Destruction is always easier than creation.

Also, as someone who frequently designs and runs SW interviews, it’s totally possible to run interviews that test actually important SW skills like OO design, error handling, and using APIs, which AIs still fail handily.

If you want to do something cool, make an AI to refactor your codebase for maintainability and security.

“Will I have root on my dev machine” is on my list of interview questions, now.

Seems cool!

Does it handle sharing a task list between people? Or syncing between multiple clients / handling concurrent edits?

I see the manual says keyboard commands are the main way to control it. Does it work in mobile?

Looks like you’re putting lots of work into it, thanks for sharing.

Is there a self hosted OpenTelemetry consumer?

Company started on Asana, individual teams jumped to Jira, company eventually followed. I was always accidentally creating blank tickets in Asana.

Part of my inspiration to learn to program was that I wanted to blink my capslock key. Did learn to program, did learn Morse, never did that project.

Yeah, if you don’t want the next dev (or your future self) to accidentally undo that corner case you fixed, better put a unit test on it.

Just being forced to talk about how it’s going and what’s blocking can be helpful, so I’m glad you’re questioning for to be more useful, not doing a little rubber-ducking isn’t all bad.

It wasn’t that long ago that he did a bunch of work to switch from Reddit to Lemmy. So I’m feeling well supported. Though not averse to hearing about other good clients.

Where does the NYPD keep getting these expensive but apparently useless robots?

Right. I care less about 60% less power, and more about will it randomly connect my phone to my car as my partner drives away instead to the speakers I was already using on the desk next to me.

Martha Wells. Finished the Murderbot series, wrapping up the Raksura. All very much of the same cloth, but I enjoy it.

Also recently discovered Naomi Novik’s Scholomance trilogy, I had only read her Temeraire books before.

There’s still a huge racial disparity in tech work forces. For one example, at Google according to their diversity report (page 66), their tech workforce is 4% Black versus 43% White and 50% Asian. Over the past 9 years (since 2014), that’s an increase from 1.5% to 4% for Black tech workers at Google.

There’s also plenty of news and research illuminating bias in trained models, from commercial facial recognition sets trained with >80% White faces to Timnit Gebru being fired from Google’s AI Ethics group for insisting on admitting bias and many more.

I also think it overlooks serious aspects of racial bias to say it’s hard. Certainly, photographic representation of a Black face is going to provide less contrast within the face than for lighter skin. But that’s also ingrained bias. The thing is people (including software engineers) solve tough problems constantly, have to choose which details to focus on, rely on our experiences, and our experience is centered around outselves. Of course racist outcomes and stereotypes are natural, but we can identify the likely harmful outcomes and work to counter them.