This is a qualitative methods paper, so statistical significance is not relevant. The rough qualitative equivalent would instead be "data saturation" (responses generally look like ones you've received already) and "thematic saturation" (you've likely found all the themes you will find through this method of data collection). There's an intuitive quality to determining the number of responses needed based on the topic and research questions, but this looks to me like they have achieved sufficient thematic saturation based on the results.
FWIW, I am building a market place app in rails and trying to vibe code the majority of it. Mostly with Gemini CLI + Cursor.
Its been very decent so far. Time will tell if the PMF is there for the MVP, but thats on the product, not the AI generated code slop.
FYI, this was more of a hobby horse + learning project than an "enterprise SaaS requiring SOC2 compliance." I am basically building a toy. So far, I have learned that you can ship code toys very quickly to test a market demand with an MVP.
Sort of a double edged sword there. A big part of the appeal of crypto money is that there is no "centralized daddy." The upside is that your property can't be confiscated by "centralized daddy." The downside is you can lose your keys.
People who do not understand that trade-off have no business buying crypto.
It can be totally anonymous if you can use a non-KYC exchange way of acquiring it. And then again, you can buy monero or zcash, then buy bitcoin again. I could start up a new open source wallet on an air gapped machine, go to a local bitcoin meetup, and buy bitcoin for cash.
Yes, and a motivated man with a heavy wrench could take it too. That doesn't mean that permissionless currency isn't valuable. It just means that my threats have been reduced from nanny took my money and man with wrench to just man with wrench.
With the exception of instagram fb marketplace, meta just looks and feels like a chaotic, sloppy mess of a company. Between the incoherent and buggy garbage that is ads manager (something I have used for my own business) and zuck saying he laid off poor performers (effectively screwing those people for no reason), it all looks like poor business operations. So its no surprise they can't figure out AI even with all the ads profits and brain power.
An adult needs to show up, put zuck back in a corner and right the ship.
> zuck saying he laid off poor performers (effectively screwing those people for no reason)
Were they not actually performing poorly, then? Maybe I'm missing some context, but laying off poor performers is a good thing last I checked. It's identifying them that's difficult the further removed you are from the action (or lack thereof).
You're replying to someone (rightfully) pointing out that you can layoff poor performers without proclaiming it with one of the farthest reaching voices in the industry.
Anyone who's worked in a large org knows there's absolutely zero chance that those layoffs don't touch a single bystander or special case.
Several of my colleagues were laid off. We all worked on the same project. I reviewed their code and was in meetings with them daily, so I know what their performance was like. They were absolutely not poor performers and it was ridiculous that they were laid off and labeled as poor performers. The project was a success too.
From what I heard, Eric Lippert was one of the layoff victims. I find it unlikely that he was actually a poor performer, since he's an industry legend.
"[My probabilistic languages] team in particular was at the point where we were regularly putting models into production that on net reduced costs by millions of dollars a year over the cost of the work.
...
We foolishly thought that we would naturally be protected from any layoffs, being a team that reduced costs of any team we partnered with.
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The whole Probability division was laid off as a cost-cutting measure. I have no explanation for how this was justified and I note that if the company were actually serious about cost-cutting, they would have grown our team, not destroyed it."
It’s such a wasteland. I really think FB is fudging those Facebook user metrics. I might login once or twice a year and realize even marketplace is junk these days.
Marketplace is trash. It is severely broken, the search doesn't work, the filters don't work. It throws in shit you aren't looking for, and constantly misses things that are there. Yet they destroyed Craigslist. Unfortunately its where everybody posts everything and you will sell shit much quicker on there.
Craigslist had the same problem. Once you have a two sided market it is almost impossible to kill your business no matter how hard you screw it up. Unusually Facebook was able to muscle them out, but Craigslist was characterized by years of stagnation where the only thing that happened was they kicked out the prostitutes.
I am not a scala fan and do not care for it, but I upvote for the thorough thought process, breakdown, and debugging of the problem. This is how technical blogs should be written. AI aint got shit on this.
It also looks like it has some improvements for dealing with `null` from Java code. (When I last used it I rarely had to deal with null (mostly dealt with Nil, None, Nothing, and Unit) but I guess NPEs are still possible and the new system can help catch them.)
If you're going to "refresh" a codebase you probably want it to be on the current version of things. Old dependencies rot, like it or not. I don't think there's any timeframe for Scala 2 EOL yet, but new development is happening in 3.
Why not though the upgrade process from 2.13 to 3 is pretty smooth. And you get all the new language features. I can think of a few that I actually like. I’ll just mention enums because it’s a good example.
Not a statistically significant sample size.
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