We closed on a house last week. It was our first time buying a home, and it was as unnerving as exciting. We plan to do some work on the house before we move in, and it has opened a whole can of worms. We had to make so many decisions and did not have enough time. I never cared about the brand of the toilet in my apartment, but now I needed to know enough to pick a new toilet. I never knew that there were dozens of white paints, each with a minutely different tone.
I was overwhelmed. Then, a wise person told me to take one step at a time and to learn to enjoy the process. We will live in the house for a long time and have plenty of time to tinker with it. I tend to rush the process so that I can mark it as “done.” But some things in life cannot be completed (your house will always have an eyesore) and are more about the journey. I will take this opportunity to internalize that.
Software Engineering ⚙️
This is not the first time an unverifiable claim has been made for JS tooling. I wish there were established JS parsing, formatting, and bundling benchmark tests as there are for CPU or graphics cards. Then, instead of a company benchmarking its competitors’ products, each can focus on its own. With that, we can improve on tweets like this.
It is an exciting idea to centralize the usage metrics of the tools at a company. We spend a lot of time and energy understanding the value of the tools during the renewal period. So even a basic centralized usage database will save so much time. I feel like all SaaS tooling companies should provide an API to collect usage data.
Many tech pundits talk about “bloat” when discussing the recent layoffs. I disagree with that labeling. A thousand engineers are a lot and expensive. But they can be there for a number of different reasons: scaling an existing product, taking a bet on a new product, or improving the team’s productivity. Knowing their challenges and priorities from the outside is impossible, and it’d be good to have some humility and empathy.
This article raises an interesting question. Is it anti-competitive if landlords use the same algorithm to set their rents? What if that algorithm uses the landlords’ private data? How can we know the algorithm does not use those private data?
Also, one memorable quote from the article: “One of the algorithm’s developers told ProPublica that leasing agents had “too much empathy” compared to computer generated pricing.”
The poor buyer experience of Ticketmaster is a clear example of a monopoly hurting consumers, from tech failure to ticket scalping. Taylor Swift tickets are now going over $20,000.
As tech companies struggle, tech media struggle as well. I enjoyed reading Protocol (I had linked to quite a few of their articles) and will miss it.
Interesting Finds 💡
Remember this article about using Generative AI to brainstorm new product ideas? Notion productized it.