Comment by godelski | Hacker News Reader

Comment by godelski | Hacker News Reader

My personal belief is just that AI assistants feel faster, not that they actually are. I'm sure they are in some specific circumstances but on average. They feel faster because your work is different, you put in different energy. I don't want to say easier (probably is) because just context switching has similar effects. People are really not reliable self evaluators. It's always the top comment on any post about some psychological study but never for these AI things. Truth is it's hard to find objective measurements. Lines of code, commits, things shipped, etc aren't strong metrics.

But I think the opening of the article is important, it asks why products aren't getting better [0]. We all feel this, right? There's so much low hanging fruit that could make our lives less frustrating but is never done because it isn't flashy. Like Apple, you got all that AI but you can't use a regex to merge calendars? Google, you can't allow a test task to be made in the past (extra helpful when it repeats). Wikipedia still uses the m address and you go to the mobile site from desktop if you don't manually remove? I could go on and on but I think we're just in the wrong headspace.

[0] imo products are getting worse, but that decline started before GPT

I‘m not sure I believe that when just yesterday, I ran a bunch of data analysis, simulation, and visualization based on a single csv and produced 5-10 decent matplotlib plots in a 90 minute back and forth between OpenAI canvas, vscode, python and jupyter. I didn’t believe some of my results and then discovered some problems of the dataset itself, so there was some „real work“ done in those 90mins.

I can say with certainty that I wouldn’t know how to wield matplotlib and pandas with such fluency in an hour, even though I am perfectly able to read the implementation and query for some relevant intermediate results to check my mental model.

Granted this is not the world’s most complex problem, but that is a good example of the domains where these tools are incredibly useful and productive already (I didn’t have to consult the docs even once). So in a way I think of LLMs as very good interfaces to the docs :)

I often feel that the UI aspect of new technologies is underappreciated. All our computers (even grep) are turing complete. This means software engineering is fundamentally a discipline of building better user interfaces that allow us to do whatever we want more easily.

I am always curious how other people experience these things as so useless :)

The one use case I’ve found LLMs excel at is using a new library. Even if it gets a lot of the API wrong, figuring out most of the setup / boilerplate is useful.

It's hard to judge without knowing. Yes, when something is rather routine (i.e. there are many examples, especially in similar formats) LLMs will almost always write this code with little to no issues. But outside that things get far harder to evaluate, especially without seeing it.

  > I often feel that the UI aspect of new technologies is underappreciated.

I do too. But I should also mention that the human language interface is not a great UI. I mean how often do you miscommunication with your boss?

  > other people experience these things as so useless

Who said useless?

Most of my work is data analysis, and it's the area I find LLMs are most difficult to use, and potentially dangerous!

I really worry when I think of how less experienced colleagues and Excel power-users might approach a pandas/matplotlib workflow with an LLM.

Very normal example from the other week. I've got a big csv of housing data, poking around I spot a bunch of very weird things in the prices: cheap places where I'd expect high prices, a strange bicameral distribution. I spend a few hours thinking about it before taking it up with the colleague who'd provided the data. There's a bug in the scraper that's messed up a bunch of values!

It'd be super-easy to naively run a simple LLM-driven analysis and miss this sort of thing.

When you're "building things" with AI, feedback is immediate. You press a button, it doesn't work as expected, the charts you can quickly run up don't give the same signals.

I worry about the same thing. Even with traditional tools people mess it up all the time. It's in the same way too, treating your algorithms like black boxes. To really do data analysis you have to understand your data and understand what you're algorithms are doing/what they mean. Too often people just naively plug in numbers and take a result. Unfortunately it's not that easy. I work "AI" just accelerates this problem and brings it to more domains

> imo products are getting worse, but that decline started before GPT

Yes, and it's not going to change until the motivations and methodologies that drive the corporation change. All these LLMs are just reinforcing their MBA mentality, which is to try to do more with less, which just ends up being more enshittification.

The money people only care about one thing, and one thing only. I say that the only real qualification for being a manager is to be willing to prioritize money over people. I've had exactly one good manager in my career, because he knew his role and respected that I knew and was passionate about mine while respecting his.

A main problem with all these huge software companies is that they are too busy chasing new features while letting long-existing bugs remain the bane of the users' experience. There's no "lets fix the current issues before we embark on new projects" mentality. I literally encountered this exact mentality in a dumb little marketing company 25yo. Different time, very small company, same dumbasses running the show.

When large software tries to be adapted beyond its initial design specs, it will eventually collapse under its own weight. At some point, a fundamental redesign must occur to prevent change grinding to a halt.

  > There's no "lets fix the current issues before we embark on new projects" mentality.

Yeah I think this ends up being just monopoly behavior. Like a few times a year I drive through The Bay and every single time am left wondering "How is Google Maps so bad here?" Things like it'll tell me the exit number but numbers are small and names are big (give BOTH. Different strokes for different folks?) or how it'll tell me to get into one lane and then want me to make an impossible turn from that lane. There's a freeway interchange where for years it has told me to use either lane and the exit is literally two lanes with each one going a different direction...

It comes off as feeling like no one is dogfooding their software. Which to me says something really really bad. Either no one internally is using the software they are building (so don't believe in it), no one is paying attention, and/or internal reports are flat out ignored. This should kill any business that doesn't have a monopoly.

It is crazy to me that they push new features with the justification of better user experience while there's a lot of stuff that can be done to make user experience better for cheaper, faster, and is far more impactful.

Sure, there's cool things like when I jump on WiFi my friend's iPhone asks them if they want to share the password with me, but are we really so fucking dumb that we think we know what is happening on each other's screens simultaneously as ours? And that "whoops, I backed out" or "whoops, I clicked off the dialogue" and then you can't repeat the process so I got to manually type in the damned thing anyways? Or just today, I was listening to music with my partner, turned on airplane mode, it turned off bluetooth, I turned it back on, and then I had to click "share" again and she had to... again pair her headphones. Even though she's in my family (they still haven't figured out that I don't care that her airpods are following me and that my airpods in my pocket are not in fact lost). There's so much of this fucking shit that every day normal people (aka my tech illiterate parents and family) complain about (and me!). I think a problem is that we also dismiss "complainers" on software teams. You need at least one grumpy fucker. The one that's not saying things are impossible, but the ones that are saying things are broken AND trying to fix them. We have too many people that are just putting their fingers in their ears and pretending problems don't exist.

And don't get me started on ML (being a ML researcher myself). I don't understand how this community can confidently claim to control "AGI" (or even Stupid AI (SAI)) when details or issues are not just ignored, but we gaslight people who bring them up. Our fucking job is to recognize limits so we can fucking fix them...

> You need at least one grumpy fucker.

"Now we're two." --Batman

Not just grumpy, but grumpy who wants to fix things. Criticism >> complaints.

Just want to make sure we're on the same page ;)

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