Same with waitlists.
It's impossible to avoid capitalism!
1,737 karma · joined November 18, 2012
email-hash: 9ecf6778c92b4d597c80bfda61a2e80a664daa98800d95db36395067756d59ef
Same with waitlists.
It's impossible to avoid capitalism!
And instead just "sync" a code folder from one main repo (perhaps containing common domain models) to other repos?
Basically the Go philosophy that a little bit of copying is better than a lot of dependency?
Postgres made the foundational design decision that every update is an insert leaving behind a stale row that'll get cleaned up eventually with its MVCC model. It's great for non-blocking read-heavy workflows (presumably the most common), but it suffers for the inverse.
For example, I wrote a simple job queue in Postgres, which had a lot of contention over the oldest rows non-terminal rows. It had many runners trying to either mark a row as completed or claim a row by atomically marking it as started and returning the row's contents (using the "skip locked" functionality). This ran much faster using similar semantics on MS SQL Server or MySQL because they have in-place updates, not an append-only tuple log.
""" A popular story that made the rounds a few months ago was “an LLM wrote a web browser in one week, completely autonomously! It’s buggy but it works.” I won’t deny that it’s an impressive demo, but in a practical sense … what was accomplished? We trained on every open-source web browser ever written to produce a version of “git clone firefox” that’s orders of magnitude more expensive, slower, and buggier. """
I do agree with you that the quotes cited out are literary constructs used by humans, and there's a risk we get trigger-happy in calling out AI-slop. Still, those are just the most obvious tells — there were absolutely other, less notable mannerisms that confirmed it for me. If you interact enough with an LLM, you can become quite good at detecting their output through subtle subconscious cues that are hard to put to words.
I do wonder where some of the tropes came from. Claude tends to say "____ is doing a lot of work in this sentence", yet I don't recognize that as a common construction for humans overall or even a specific community (e.g. journalists). Perhaps I'm just unfamiliar with some vernaculars found in training data. Yet sometimes, it legitimately feels like they've actually developed a lingo of their own — an emergent property.
I find it all truly fascinating (along with other feelings…), and I never expected computers to be able to "understand" language anywhere near the degree we see today. Will it soon plateau, requiring another breakthrough? Or is there plenty of juice left to squeeze?
Not only that, almost everyone on this forum walks around with a device that shares their identity and location with unscrupulous companies (cell phone carriers) whose data is available en masse to the government. (N.B. I have an iPhone and appreciate and even _trust_ all the privacy work put into it; however, the cell phone tower thwarts location tracking, and participation in social networks thwarts face tracking.)
I've long thought that rather than try to limit the information about us, we ought to _flood_ the Internet with information about us. Make the data available untrustworthy.
Or, accept it. So long as it remains in the hands of corporations and not solely the government, it guts both ways — a senator can no longer be publicly opposed to same-sex equality legislation while engaging in a homosexual relationship themselves.
AI seems to be pushing us down the former road.
Maybe a good compromise is to use 1pw for most TOTP but keep your gmail / iCloud and a few others in an iPhone only app?
Gmail is what scares me the most. It’s basically keys to the kingdom.
^ This was written 100% by hand. Let's have Claude proofread it and make any suggestions:
I'd argue the opposite — I reach for AI because I care about the recipient. It helps me express my thoughts more precisely and eloquently than I might off the cuff, and I'll often edit the result to make sure it sounds like me.
Presuming that an LLM-assisted email signals indifference seems like a category error. The care is in what you're trying to communicate, not which tool you used to get there. -- https://claude.ai/share/3d3d1a78-381c-4fcf-9354-69b10f2d6f4a
Triple backticks also aren't recognized. However, if you indent by I believe 4 spaces, it formats it in a fixed width font presuming it's code.
Let's try (4 spaces):
func main() {
fmt.Println("Hello, HN!")
}
None for comparison:func main() { fmt.Println("Hello, HN!") }
For my own resumé, I include the stack used at each job which I feel strikes a fair balance.
If it's something like "Refactored the apartment list service improving P99 Latency from 2s to 180ms", it definitely boosts the resumé in my mind. A good engineer would be measuring their impact and likely have numbers like that off the top of their head.
But if it's like "Increased revenue by $18.7M by reducing time-to-first-interaction latency from 2.3s to 117ms, increasing conversion by 47% and LTV by 28%," with the same fidelity on each bullet, I'm very skeptical.
--
I don't summarily reject AI-written resumés to be clear, as honestly, it's basically a necessity at this point to be competitive with others; it'd be putting yourself at a severe disadvantage on pure principles in a way that has no real positive net effect on society. Even if you disagree with AI resumé screeners, you're only hurting yourself — especially at a time that has the largest impact on your compensation (i.e. negotiating salary at job start is one of the most valuable ways to spend your time since it will pay you back every paycheck).
Though I _do_ tend to question resumés that look like they were written almost entirely by an LLM without the candidate providing significant context and refinement.
People jay walk when there's no traffic all the time, that's totally fine. This is a totally different act of passive aggression.
That said, I’m open-minded and obviously thinking about this given moving to my own domain.
What’s the evil behavior you’ve experienced? I’m down to move off if I’m oblivious to something…
When I look at Google, I see a company that is fully funded by ads, but provides me a number of highly useful services that haven't really degraded over 20 years. Yes, the number of search results that are ads grew over the years, but by and large, Google search and Gmail are tools that serve rather benevolently. And if you're about to disagree with this ask yourself if you're using Gmail, and why?
Then I look at Meta or X, and I see a cesspool of content that's driven families apart and created massive societal divides.
It makes me think that Ads aren't the root of the problem, though maybe a "necessary but not sufficient" component.
Whenever I'm approaching a border crossing (e.g. in an airport), I'm sure to discreetly click power 5 times. You also get haptic feedback on the 5th click so you can be sure it worked even from within your pocket.
But your hypothetical manager who needs employee scheduling software isn't paying for the coding, they're paying for someone to _figure out_ their exact needs, and with a UI that fits their preference, ready to go in no time.
I've thought a lot about this and I don't think it'll be the death of SaaS. I don't think it's the death of a software engineer either — but a major transformation of the role and the death if your career _if you do not adapt_, and fast.
Agentic coding makes software cheap, and will commoditize a large swath of SaaS that exists primarily because software used to be expensive to build and maintain. Low-value SaaS dies. High-value SaaS survives based on domain expertise, integrations, and distribution. Regulations adapt. Internal tools proliferate.
I also use en dashes when referring to number ranges, e.g., 1–9