I'd use an website/app that supports my preferred data ingestion process -- periodically manually downloading my bank & credit transactions (supporting at least one of: csv, qif, and qfx), and allows me to define at least (account, category, description) tuples mapping transaction to buckets (ideally hierarchical).
(Ideally also a focus on viewing trends at various grains and easy drill down, as opposed to "don't buy any more smoothies for the next 11 days, but go ahead and rent more movies soon -- use it or lose it!".)
I see gnucash mentioned as an option for ingesting downloaded transactions. Any others?
I don't know what qualifies as not trying hard enough, but when I meet someone, I expect I'll be able to play back salient chunks of content (precise wording, intonation, clear visuals zoomed in or out) but I'm worried the couple times repeating the name in my head trying to focus on it will, predictably, not stick.
I generally am bad at recalling labels compared to 'content.'
Knowing I need a better system for remembering names, I suppose I should try harder to uncover one.
Speaking of USPS knowing what they're doing, their address normalization replaces our city name with the broader "Minneapolis," but multiple delivery services use that normalization without flowing the zip code through to directions lookup (whether a tech issue or driver retyping omission), which results in drivers calling us from another suburb 15 minutes away as the pizza goes cold.
I grew up in sheltered outer suburbs where it's hard for kids to get around on their own, and older kids turn to some nonproductive amusements -- was surprised to hear a friend tell me he liked (after dusk) freeing trailers to watch them roll into cars.
Same. I've left my garage door open on the way out so many times (in a quiet, unremarkable cul de sac -- neither upscale nor rundown) without consequence that I no longer worry about whether or not I closed it.
The 2003 date on archive.org makes it seem like Easel was renamed to ESL while ESL Investments was building its stake in (major Easel customer) Sears but well before ESL Investments took over Sears.
$/sqft glosses over local labor costs, level of finish, landscaping, etc., which is why you see people suggesting 1-2% of value per year, though you're right that it would be an improvement to separate out the value of labor/materials from the value of a the bare lot.
My first inclination would be to base maintenance cost off cost of rebuilding (optionally overridable) -- in effect, you end up with a much lower percent of total value where you're basically paying for an expensive lot, and a much higher percent of total value in depressed markets (e.g. where you can get 100-year-old 7-bedroom for ~= national median home value).
Another fun, if more subtle divide is right around Hibbing, MN -- step west and water flows down the Mississippi to the Gulf of Mexico, step north and water flows up to Hudson Bay, step southeast and water flows through the Great Lakes to the Atlantic Ocean. https://www.google.com/maps/@47.4206243,-93.0430116,12.7z
It's had that model way before Slack, et al., kind of bolted it on. I've participated lightly in a couple orgs that use Zulip. Zulip's model does a much better job of keeping convos from getting drowned out / lost when pushed off the page, so it's much easier to log in sporadically and meaningfully participate. The apps, especially mobile have rough edges, but I still prefer it to Slack and the like, fwiw.
My and my spouses co-workers seem to be split on whether or not they have young kids at home that they're supposed to be watching while they work. My spouse and I are lucky enough to have help watching our kids and seeing them more as well as getting those prep and commute hours back is such a blessing.
This is one of my favorites. They played it for us when I was at https://www.recurse.com. I half appreciated it then, but it's gotten better with repeat viewings.
Second flaw is even better than that -- author mistakenly asserts 'multiplying all values times 100' is the _only_ way to 'scale all data to ensure positive values.'