This is one from me, I hope you like it. Concept maps were originally introduced as a teaching/learning tool (particularly for kids) by Joseph Novak, and have been later used by the cognitive task analysis people (cf. Gary Klein) to establish baselines for expertise.
It was for a Java project. It makes sense, if you can’t bend the usual tools (maven, gradle, make) to do your bidding, roll your own. I’m surprised bazel wasn’t tried, from my (extremely) low experience with bazel I’d expect it to support solving this problem.
It seems like an excellent tool for initial setups. We do have something similar internally, but built by us and with all the bells, whistles and corner cases that we need. Because in the end, corner cases are where the magic sauce is.
Quite long but very interesting. Probably the point that caught my attention the most is Neo4j, a graph database provider, raised $325M at a more than $2B valuation. That’s the same valuation as Redis Labs (which, support, of course, Redis).
This seems to match very well my experience. At my previous work we had a very small team so any requirement for a new kind of report having to look back eons or a dashboard for a really complex set of data was heavily pushed back, trying to figure out why it was needed. And quite often we could convert a significant amount of work into basically an alert email, or a ping when something changed behaviours. Or a one-off request instead of a recurrent, expensive job.
I tried working in VR as a gimmick soon after getting a Quest and found the headset too heavy for comfort, even with the elite strap, which distributes weight better. Also, the Quest LED panels feel too bright for me. But of course the screen real state you get is freaking awesome.
This reminds me of Wardley mapping in a way. Once something becomes a commodity (for example, deep learning with TPUs/GPUs) new possibilities open, like self-driving cars or dog-or-muffin. Higher execution speed is thus similar.