stkni

Great analysis! I used to ask a fairly open ended elevator system design question for engineering interviews. There is a lot of mileage in this topic and everyone has an understanding of the basics so the setup costs for the question are minimal. Always generated a lot of interesting discussion.

Think I'm with Larry on this one. Someone should chair the meeting and there should be some expected outcome (decision) from it within the alotted time. If we're 45 mins in and no closer to an answer it's time to assign some investigative actions and regroup? Malicious compliance in this context is good, because it creates an environment where meetings end and everyone gets to pee?

This is seriously impressive. I asked it to create 3 different databases:

- a customer orders database with products with a timeseries of prices, and multiple fulfilments per order. - an issue tracking system with a reflexive user/manager database - a family relationship model

In each case I got it to put in sample model and then asked postgres.new to answer some questions about the data it had inserted. I thought the family model would trip it up, especially when I told it to put in cousins and uncles. But no, it was pretty bang on.

The only thing it didn't quite manage is that some of the relationships are reciprocal (i.e. my sibling also has me as a sibling).

I asked postgres.new to review the data and it fixed some, and i asked it to check again and it fixed the rest. This is a very useful tool that I can see myself using!

I'm genuinely baffled by this, why are the tax filing options in the US so fragmented? Here in the UK there are probably some situations in which you can't use the online, government provided, free service. But I'm going to stick my neck out and say they're fairly niche.

Having lived in the US I know things get complex when you start mixing in state taxes, but this is federal taxes right? Or wrong?

>> And then there's the competition - I early discovered that I could never outperform my competition.

100% this. I'm a bit competitive, but only a bit :). After 20 years of being a dev I realised I didn't want to compete anymore and shortly after that I quit as a dev.

I've now switched more into an analyst role and because I've been a dev i think I know what makes a good analyst because I know what I would have to know to write the code - if it were me. But here's the best part, the mark of a good developer is their attention to detail. And attention to detail is also the mark of a good analyst, but as an analyst you don't have to sacrifice yourself to the detail of tool-chains, stacks and frameworks.

Working on large scale problems as a dev, and doing it right, is slow (with a small number of devs) and chaotic with a large number. But as an analyst I can work at the speed of thought, work on many projects simultaneously, and see the fruits of my ideas take shape as the devs start to deliver them and I shepherd them into existence.

So for now I'm pretty happy, I write code in my spare time for fun and like the OP - I'm back where I need to be.

I have a sort of off-topic question. The marketing for this claims not using STL containers as a selling point. Does anyone know what makes STL containers unsuitable for this use case? Clearly they're not a one size fits all but I'm intrigued to know why you market an unknown container based API over a tried and tested one?

This is a good point. If the users know the difference the costs and benefits between using GPT and not using it then it certainly has value if those users are also willing to accept that not every answer needs to be 100% accurate.

In my experience business people often have a 'nose' for the right number and will bluff it out if the numbers are wrong and they're challenged.

Blue sky things or stuff you're putting in the annual report should be left to hoomans IMHO.

This was my take too. The break-down in communication might not be WHAT is being said but HOW it's being said. This is certainly my experience of being a dev and a manager, sometimes people just seem a bit rude and it's hard to get past.

Is the rudeness excusable? I guess. Especially if I understand where it's coming from. Otherwise it's just rudeness.

And I guess that the point of the article, but you need to get to know people before you can make the judgement of why someone is how they are. That takes time.

This is a great question! When I was a developer I used to develop software the way you were told not to. I did it that way because the requirements were always very vague and a lot of gaps needed to be filled. But when I was a project manager I thought that way of development is wasteful and would rather developers didn't do what I did.

So I suppose the real answer depends on the environment you're in. If the project is meant to be agile then you probably need a bit of interaction with the user to get the job done. If the project is not agile and all the requirements could be known up-front then you're probably wasting effort having programmers determine what those requirements are. IMHO.

Absolutely. Picasso's journey was to transition from stunning realism to a child-like surrealism in later years. In some respects he was trying to unlearn form but keep the aesthetic.

And to be honest some of these MOBA pictures do that too, they're actually not bad at all. It's just perhaps not intentional, but does that matter?

So to call it bad art, is going a bit far.

My first experience of Tcl/Tk was circa 2000. The finance house I worked at had used it to implement a real-time order management system.

Even better was the ability to attach to the running ui or server (yes we had both), replace some of the code on-the-fly, and disconnect. Perhaps not so amazing these days, but it was way ahead of anything else I'd seen upto that point and pretty mind-bending for a C/C++ coder.

>> But if you tweak the hypothesis just a little, the data suddenly confirm it

This is 'data mining' right? And I've occasionally wondered about this, since I don't work in a scientific field but did once make use of the scientific method for some research I did. And yes the findings weren't especially conclusive but I'm not sure I could've tweaked the hypothesis to make it work.

So, had I found something really interesting that didn't fit the hypothesis, is the 'right way' to conduct a new experiment from scratch? So say I did that, and used the 'tweaked' hypothesis, of course I'd find something interesting, because it's already there.

In this new 'pre-registration' framework, how can I correct the problem and pursue the interesting idea but keep the science in-tact? Because, if I used some sort of cross-validation at the outset and I have all the data available I presumably can't change the sample, so the hypothesis presumably has to change.

This would be a great win-win! But wouldn't the sequestered CO2 get released back into the environment and potentially the atmosphere?

But doesn't the comment above yours suggest that the 'yellow' dot thing may no longer be an issue and that now there's variation in the dithering parameters. Suggesting extra ink is not required.

More annoying are the privacy concessions that are the result of secret anti-counterfeiting measures (which is what I assume the measures are for).