466 karma · joined April 20, 2021
https://www.nytimes.com/2026/05/23/us/politics/trump-legal-i...
Unfortunately, I heard that the government previously investigated taking action but were lobbied against doing so by pharmaceutical companies that earn revenue from allergy medications.
For any design docs, have them do a walkthrough with the team. If they have to speak to their plan live and answer questions, it will be obvious if they've put thought into it or not.
The same thing can be done for any PRs that have some depth to them like if they touch critical logic or involve complexity.
Why not? This is such an American point of view that sounds similar to why the IRS doesn't offer easier tax filing options.
Actually, these scenarios happen in hockey as well. Teams will pick up character guys who have been through it all who are expected to contribute more off ice than on it. Corey Perry is one who comes to mind lately but they're never given a "coach" title. It's entirely possible though that these players may be expected to be a go-between guy between the coach and younger players to help them manage the pressure or to help with encouragement. They're definitely not getting prime minutes though.
I guess that would possibly be the same expectation of a manager who still codes. I can't see them doing anything critical. It's likely picking up some minor bugs or nice-to-have, low priority feature work. I was a manager before and while I didn't reach 15 reports, I was up to 12 at one time. There's just really no focus time that you need for coding. Maybe that's a bit different with AI but even then you still need to find time to make changes and validate. And that's time that takes away from other higher impact things that you could be doing for the team.
It's because crypto goes in a cycle and now it's down. You should expect layoffs from them again in 2029/30.
Player-coach used to be a thing in professional sports a long, long time ago. There's a reason you don't have it anymore. A coach can't be expected to take the long-term view while also expecting to contribute. Most examples were players near the end of their career and they didn't tend to do very well.
The only place you see it is in fun adult leagues. Perhaps the message then is that Coinbase wants to be less professional and more amateur-like?
Are you only supposed to date girls you're not attracted to?
One thing I noticed when I was doing salsa dancing is that there's a normal distribution for how you "click" with people. With salsa dancing, you change partners frequently so I may have interacted with dozens of people in one night of dancing. I noticed how most people fall in the middle of being fine to dance with and then you get a few outliers where they are either terrible to dance with or are amazing.
It looks like OP found something similar. Out of 35 encounters, he had 5-6 advance to the "prioritization" stage (~14%) and 2 (5%) ended up moving into building a relationship outside of the normal environment you usually interact at. I think that is very relatable. Most people you interact with will be fine to chat with but only a small percentage will be people that you really gel with.
Edit: I see you addressed this elsewhere. Thanks for contributing!
> Then, out of the blue, Satoshi appeared on the list with an email that neatly dovetailed with Mr. Back’s position
> The following year, in 2015, the Bitcoin community fractured over a proposal to increase Bitcoin’s block size. A faction led by two Bitcoin developers, Gavin Andresen and Mike Hearn, wanted to make the blocks much bigger to accommodate more transactions. But this was controversial...
> Mr. Back fiercely opposed increasing the block size. In a series of posts on the Bitcoin-dev list, he warned against Mr. Andresen and Mr. Hearn’s proposal in increasingly strident tones.
> Then, out of the blue, Satoshi appeared on the list with an email that neatly dovetailed with Mr. Back’s position. It was the first time Satoshi had been heard from in more than four years, other than a five-word post the previous year denying a Newsweek article’s claim to have unmasked him.
> Many in the Bitcoin community questioned the new email’s authenticity since another of Satoshi’s email accounts had been hacked. But Mr. Back argued that the email sounded real. In a series of tweets, he called Satoshi’s observations “spot on” and “consistent with Satoshi views IMO” and took to quoting from the email.
I now realize that the Satoshi email was after Hal Finney's death so that changes my opinion.
From OP:
> Satoshi supported big blocks in his writings and empowered the pro-big block Gavin when he disappeared
This isn't correct. In fact, the linked email in the article says the opposite https://gnusha.org/pi/bitcoindev/6EC9DDF352DC4838AE9B088AB37...
Personally, I think Satoshi was Hal Finney.
> But when I reviewed the codebase in detail in late January, the downside was obvious: the codebase was complete spaghetti...It was extremely fragile; it solved the immediate problem but it was never going to cope with my larger vision...I decided to throw away everything and start from scratch
This part was interesting to me as it lines up with Fred Brooks "throw one away" philosophy: "In most projects, the first system built is barely usable. Hence plan to throw one away; you will, anyhow."
As indicated by the experience, AI tools provide a much faster way of getting to that initial throw-away version. That's their bread and butter for where they shine.
Expecting AI tools to go directly to production quality is a fool's errand. This is the right way to use AI - get a quick implementation, see how it works and learn from it but then refactor and be opinionated about the design. It's similar to TDD's Red, Green, Refactor: write a failing test, get the test passing ASAP without worrying about code quality, refactor to make the code better and reliable.
In time, after this hype cycle has died down, we'll come to realize that this is the best way to make use of AI tools over the long run.
> When I had energy, I could write precise, well-scoped prompts and be genuinely productive. But when I was tired, my prompts became vague, the output got worse
This part also echoes my experience - when I know well what I want, I'm able to write more specific specifications and guide along the AI output. When I'm not as clear, the output is worse and I need to spend a lot more time figuring it out or re-prompting.