As AI companies rave about how their products are revolutionizing productivity, Senator Bernie Sanders wants the tech industry to put its money where its automated mouth is.
Does anyone here actually see productivity improvements to their roles from using AI?
I’m a telecoms engineer and I see limited use cases in my role for AI. If I need to process data then I need something that can do math reliably. For document generation I can only reliably get it to build out a structure and even then I’ve more than likely got an existing document the I can use as a structure template.
Network design, system specification and project engineering are all so specific to the use case and have so few examples provided in public data sets that anything AI outputs is usually nonsense.
Am I missing some use cases here?
Also, if you do see productivity improvements from AI, why would you tell your employer? They want a 5 day working week but they know what they expect to be achieved in that week, so that’s what they get.
Document that code I wrote 7 years ago, suggest any security or efficiency changes. It’s surprisingly adept at that.
Give me the changes to NixOS 25.05 configuration.nix to add wadroid. Fails with an error, paste the error back into prompt. Oh, you need these kernel modules that are no longer default as of 25.05 make this change. Different error paste it back, Make this one last change and then reboot. It works. I spent a total of 5 minutes on it. If I were just using Google and screwing around that might have been half a morning.
OBS is giving me a pixel resolution warning. AI: it’s one of your cameras or some media you’ve added in an unsupported format. Give me a quick shell script to run through all of my media directories in this tree and convert all the MP4 video that’s yuv720 to a supported format in new tree so I can swap them out in the end with no risk. 30 seconds later it’s there. Yes, I can write that but I’m not going to have it done in 30 seconds. And if one of the files errors I just shove the error right back in the AI. I don’t personally care why one in 50 images failed I just want them to be converted and I’m far enough along and Dunning Kruger scale that I honestly don’t really care about what I don’t know as long as I can learn a little more and still get the job done.
Give me a python script to go through a file full of URLs and verify the SSL key expiration dates. Have a variable for how far the future to alert and then slack me a message at 10:00 a.m. everyday which URLs and IPs are expiring earlier than that variable. Also a bunch of the IPs don’t resolve to external addresses so you’re going to have to fake the calls to check them. Here’s my slack token in the channel name.
3 minute project
It doesn’t do my job for me but it gets rid of a hell of a lot of tech debt that I’ll never get around to. I won’t give it monolithic complicated jobs because it’s not good at it. But I will absolutely tell it to make me a flask app with stubs for half a dozen features. Or give it the source for a shitty old admin web page and ask it to modernize the CSS and add session logins.
Sure, if I’m not watching it it might do something relatively stupid. But honestly it has about the same odds of catching something I did years ago that was relatively stupid and telling me to fix it.
My gut feeling, based on the kind of repetitive nonsense I see them produce and bang on about, is that a lot of management types see AI efficiency because the work they do is repetitive and easily aided by AI input so they assume everything can be improved by it.
Not to say I don’t see the benefits of a good manager, I just don’t think they are that common.
I do. Part of my job involves writing code and I often don’t even know where to start. When I get the first draft I’ll know which documentation to read, and then I make it actually work. Even when the LLM fails completely, writing its prompt serves as a rubber duck.
So do you frame the problem to the LLM, get it to spit out an example piece of code and then run through that initial attempt to get an idea of how to approach the problem? Kind of like prototyping the problem?
I take it you find that more efficient than traditional code planning methods? Or do you then start building flow charts/pseudo code from that prototype and confirm the logic to build more readable or efficient code?
Claude can spit out powershell scripts up to like, 400 or 500 lines without errors or with minimal, easily debugged errors. Adds things like error correction, colored text, user interaction, comments the code pretty well. Saves me hours every time I fire it up, so that I can in turn save myself dozens of hours with the scripts themselves.
But as far as I tell my boss, there is no AI use, and that’s how we’re keeping that for now/indefinitely
you see, for programming, AI achieved what SQL tried to do with database queries: programming by just telling the computer what you want and the computer figures out the how.
the catch is that human language is imprecise, so if you don’t know how to review what the AI produced, the AI might have written a script to wipe your data in the computer and you don’t even know until you run it and it is too late
The other day it spit out a five line piece of code, except, critically, it had used “archived” where it should have used “received”. Small word difference, huge functionality difference.
It absolutely does help, but we’re gonna have a couple whole new classes of copy/paste errors.
I find it useful for correcting my syntax (when it’s correct 😂) for certain networking devices. I touch so many vendors it’s not always one I can remember all the commands for.
It’s kinda become a Google replacement for me.
I have found certain areas it’s weak and I know when to quit when I’m ahead and it just agrees with me and spits out more incorrect info when I call it out.
Also when are we going to hit an AI feedback loop? 😅
I find the AI summary can be helpful when searching, but also not much more helpful than a summary of the first few search results which are mostly only loosely related paid for advertising …
I feel like AI is just going to end up replacing interns or entry level people, it can do easy tasks that would take a while by hand to do. Which based on how bad the job market seems to have been for people like me just trying to enter it somewhat makes sense.
Does anyone here actually see productivity improvements to their roles from using AI?
I’m a telecoms engineer and I see limited use cases in my role for AI. If I need to process data then I need something that can do math reliably. For document generation I can only reliably get it to build out a structure and even then I’ve more than likely got an existing document the I can use as a structure template.
Network design, system specification and project engineering are all so specific to the use case and have so few examples provided in public data sets that anything AI outputs is usually nonsense.
Am I missing some use cases here?
Also, if you do see productivity improvements from AI, why would you tell your employer? They want a 5 day working week but they know what they expect to be achieved in that week, so that’s what they get.
Yes.
Document that code I wrote 7 years ago, suggest any security or efficiency changes. It’s surprisingly adept at that.
Give me the changes to NixOS 25.05 configuration.nix to add wadroid. Fails with an error, paste the error back into prompt. Oh, you need these kernel modules that are no longer default as of 25.05 make this change. Different error paste it back, Make this one last change and then reboot. It works. I spent a total of 5 minutes on it. If I were just using Google and screwing around that might have been half a morning.
OBS is giving me a pixel resolution warning. AI: it’s one of your cameras or some media you’ve added in an unsupported format. Give me a quick shell script to run through all of my media directories in this tree and convert all the MP4 video that’s yuv720 to a supported format in new tree so I can swap them out in the end with no risk. 30 seconds later it’s there. Yes, I can write that but I’m not going to have it done in 30 seconds. And if one of the files errors I just shove the error right back in the AI. I don’t personally care why one in 50 images failed I just want them to be converted and I’m far enough along and Dunning Kruger scale that I honestly don’t really care about what I don’t know as long as I can learn a little more and still get the job done.
Give me a python script to go through a file full of URLs and verify the SSL key expiration dates. Have a variable for how far the future to alert and then slack me a message at 10:00 a.m. everyday which URLs and IPs are expiring earlier than that variable. Also a bunch of the IPs don’t resolve to external addresses so you’re going to have to fake the calls to check them. Here’s my slack token in the channel name.
3 minute project
It doesn’t do my job for me but it gets rid of a hell of a lot of tech debt that I’ll never get around to. I won’t give it monolithic complicated jobs because it’s not good at it. But I will absolutely tell it to make me a flask app with stubs for half a dozen features. Or give it the source for a shitty old admin web page and ask it to modernize the CSS and add session logins.
Sure, if I’m not watching it it might do something relatively stupid. But honestly it has about the same odds of catching something I did years ago that was relatively stupid and telling me to fix it.
Unless you’re a scammer or a spammer, the answer is legitimately “No”.
My gut feeling, based on the kind of repetitive nonsense I see them produce and bang on about, is that a lot of management types see AI efficiency because the work they do is repetitive and easily aided by AI input so they assume everything can be improved by it.
Not to say I don’t see the benefits of a good manager, I just don’t think they are that common.
I do. Part of my job involves writing code and I often don’t even know where to start. When I get the first draft I’ll know which documentation to read, and then I make it actually work. Even when the LLM fails completely, writing its prompt serves as a rubber duck.
So do you frame the problem to the LLM, get it to spit out an example piece of code and then run through that initial attempt to get an idea of how to approach the problem? Kind of like prototyping the problem?
I take it you find that more efficient than traditional code planning methods? Or do you then start building flow charts/pseudo code from that prototype and confirm the logic to build more readable or efficient code?
Claude can spit out powershell scripts up to like, 400 or 500 lines without errors or with minimal, easily debugged errors. Adds things like error correction, colored text, user interaction, comments the code pretty well. Saves me hours every time I fire it up, so that I can in turn save myself dozens of hours with the scripts themselves.
But as far as I tell my boss, there is no AI use, and that’s how we’re keeping that for now/indefinitely
you see, for programming, AI achieved what SQL tried to do with database queries: programming by just telling the computer what you want and the computer figures out the how.
the catch is that human language is imprecise, so if you don’t know how to review what the AI produced, the AI might have written a script to wipe your data in the computer and you don’t even know until you run it and it is too late
The other day it spit out a five line piece of code, except, critically, it had used “archived” where it should have used “received”. Small word difference, huge functionality difference.
It absolutely does help, but we’re gonna have a couple whole new classes of copy/paste errors.
Makes me wonder what an LLM trained in lojban would accomplish.
So you’re sharing your data with third parties and relinquishing code copyright without telling your boss?
I find it useful for correcting my syntax (when it’s correct 😂) for certain networking devices. I touch so many vendors it’s not always one I can remember all the commands for.
It’s kinda become a Google replacement for me.
I have found certain areas it’s weak and I know when to quit when I’m ahead and it just agrees with me and spits out more incorrect info when I call it out.
Also when are we going to hit an AI feedback loop? 😅
I find the AI summary can be helpful when searching, but also not much more helpful than a summary of the first few search results which are mostly only loosely related paid for advertising …
I feel like AI is just going to end up replacing interns or entry level people, it can do easy tasks that would take a while by hand to do. Which based on how bad the job market seems to have been for people like me just trying to enter it somewhat makes sense.