Now that said, I don't want to minimize the difficulty in modernizing software at a corp like HD. It's wildly more difficult than most people can appreciate. I've consulted for companies trying to do it, and there are lots of challenges with legacy systems, migrations, and plenty of non-technical challenges as well.
Shout out to Wal-mart for genuinely kicking ass at this though. I'm quickly becoming an Onn fanboy. Genearlly speaking, great products at great prices, from their USB cables up to their smart speakers and more. You can really tell from the product design and implementation that they are letting the nerds geek out and have fun! That in turn enables me to do the same :-)
1/2 in
1/4 in
1 in
3/8 in
3/4 in
Specialty
Here is the same list in decimal to make the insanity plainly obvious: 0.5
0.25
1
0.375
0.75
What sadistic lunatic made that sort order?! It's not based on size and it's not alphabetic.It seems like a cheap and simple thing to offer your customers a little extra safety.
Anybody interested in starting a platform agnostic service to do this?
GitHub Advanced Security blocks the push, I believe.
It seems ( only seems, because I have not gotten around to test it in any systematic way ) that some variables like context and what the model knows about you may actually influence quality ( or lack thereof ) of the response.
Sometimes it would take a few minutes in the morning before my Mac would even recognize 'hey, there's a watch' (typing in my full password was usually much quicker than waiting for the watch unlock).
Sometimes whatever notification happens that triggers the watch to vibrate and allow the double-squeeze-to-accept action would just... not.
Other times the above notification would pop up about 8-15 seconds after the prompt on the screen.
It was inconsistent enough I got _really_ good at typing my password, since it was normally quicker than waiting on the Apple Watch.
Contrast that with the Touch ID, that's always ready to go.
I've been building accounting tools for years. AI can generate a function to parse a bank statement CSV pretty well. But can it handle the Barclays CSV that has a random blank row on line 47? Or the HSBC format that changed last month? Or the edge case where someone exports from their mobile app vs desktop?
That's not even touching the hard stuff - OAuth token refresh failures at 3am, database migrations when you change your mind about a schema, figuring out why Xero's API returns different JSON on Tuesdays.
The real paradox: AI makes starting easier but finishing harder. You get to 80% fast, then spend longer on the last 20% than you would have building from scratch - because now you're debugging code you don't fully understand.