So I am so ewhat pro AI. But hear me out. I sometimes refer to myself as an automation engineer. I spend a lot of my time automating the set up and use of various software tools. For those who know the term Infrastructure As Code is a part of my job too. And soo many tools have shitty UIs and even shittier apis. The rise of AI is going to add pressure to have better apis because that is what the AI uses. So even if AI falls flat on it’s face in a few years, any improvements in apis is a vig win for me. And since the automation I write is for my coworkers, not external customers, anyone in tech benefits from this.
Now for me personally, I work ina lot of different languages and DSLs. I rarely spend enough time in any one of them to really memorize the syntax. I pretty much can’t write a working program without some sort of reference. So, I can tell AI exactly what I want it to do, and it can code and test until it runs. Then I can use that as my syntax reference and make it do what it is supposed to do. That ends up being much faster than me having to google various syntaxes to see where I need a semicolon vs a comma, or where I need to use [] instead of {}. So it helps me.
And I do love using AI to file my jira tickets. Works great for those of us who’s work is interrupt driven. We often file the ticket after we’ve solved the problem.
I am in the same boat, long time infrastructure automation engineer as well. Sometimes it’s faster to explain how terraform or whatever needs to act and then fix the issues rather than having to sift through the docs for every provider.
I also do a similar thing to you with code, I also have to read a lot of other people’s code in languages I don’t know to help troubleshoot things and while I can usually follow the logic it is such a time saver to have AI to read the docs for the libraries and languages for me to at least find the part of the docs I need to read faster than searching myself.
Overall, I also agree with the sentiment on AI most of the time and all of its criticisms are definitely valid but I think too many people try to use AI to do their work for them instead of using it more like a rubber duck you can program with normal language.
Well, grafana is an example. They want their own AI agent that you can pay for. So they still need the apis to be good. But they don’t make it easy to get your AI it own api token. Each user would essentially have to have two accounts. Which they probably charge for too. It’s not impossible to work around, but it’s a barrier. I would expect more of that kind of thing.
Any tool that doesn’t have a way for AI to work with it is going to be selected against for a while. So there is pressure for them to be accessible.
The closest facsimile I have in my work is occasionally running an Excel formula I’ve written through Copilot in order to find a formatting error or to help fix an Access query, but If fundamentally understand what I’m doing, can validate that the produced result is correct, and can fix it if I have to somewhere down the line.
It’s good you’ve found some simple ways to use it, but in the vast majority of work I do, it would take longer if I used AI because everything produced using an LLM has to be human-validated regardless, so I might as well not skip the important step of learning and understanding it.
I never use it to ideate and never use it for anything that isn’t eminently simple, like creating a sheet with x number of columns and rows or something like that. I hate the idea of the environmental impact and that helps me avoid it.
Yeah, it’s nothing particularly special IMHO. The best feature I’ve found in using it is that, for Microsoft products in particular, it can tell me capabilities of certain things I didn’t know previously when I present it with a problem.
Search engines used to do that before they got enshittified.
So I am so ewhat pro AI. But hear me out. I sometimes refer to myself as an automation engineer. I spend a lot of my time automating the set up and use of various software tools. For those who know the term Infrastructure As Code is a part of my job too. And soo many tools have shitty UIs and even shittier apis. The rise of AI is going to add pressure to have better apis because that is what the AI uses. So even if AI falls flat on it’s face in a few years, any improvements in apis is a vig win for me. And since the automation I write is for my coworkers, not external customers, anyone in tech benefits from this.
Now for me personally, I work ina lot of different languages and DSLs. I rarely spend enough time in any one of them to really memorize the syntax. I pretty much can’t write a working program without some sort of reference. So, I can tell AI exactly what I want it to do, and it can code and test until it runs. Then I can use that as my syntax reference and make it do what it is supposed to do. That ends up being much faster than me having to google various syntaxes to see where I need a semicolon vs a comma, or where I need to use [] instead of {}. So it helps me.
And I do love using AI to file my jira tickets. Works great for those of us who’s work is interrupt driven. We often file the ticket after we’ve solved the problem.
I am in the same boat, long time infrastructure automation engineer as well. Sometimes it’s faster to explain how terraform or whatever needs to act and then fix the issues rather than having to sift through the docs for every provider.
I also do a similar thing to you with code, I also have to read a lot of other people’s code in languages I don’t know to help troubleshoot things and while I can usually follow the logic it is such a time saver to have AI to read the docs for the libraries and languages for me to at least find the part of the docs I need to read faster than searching myself.
Overall, I also agree with the sentiment on AI most of the time and all of its criticisms are definitely valid but I think too many people try to use AI to do their work for them instead of using it more like a rubber duck you can program with normal language.
Or they’ll make apis shittier because they don’t want AI using it.
However, Copilot has made it a lot easier to navigate through Azure’s incomprehensible menu structure.
Well, grafana is an example. They want their own AI agent that you can pay for. So they still need the apis to be good. But they don’t make it easy to get your AI it own api token. Each user would essentially have to have two accounts. Which they probably charge for too. It’s not impossible to work around, but it’s a barrier. I would expect more of that kind of thing. Any tool that doesn’t have a way for AI to work with it is going to be selected against for a while. So there is pressure for them to be accessible.
The closest facsimile I have in my work is occasionally running an Excel formula I’ve written through Copilot in order to find a formatting error or to help fix an Access query, but If fundamentally understand what I’m doing, can validate that the produced result is correct, and can fix it if I have to somewhere down the line.
It’s good you’ve found some simple ways to use it, but in the vast majority of work I do, it would take longer if I used AI because everything produced using an LLM has to be human-validated regardless, so I might as well not skip the important step of learning and understanding it.
I never use it to ideate and never use it for anything that isn’t eminently simple, like creating a sheet with x number of columns and rows or something like that. I hate the idea of the environmental impact and that helps me avoid it.
And outside coding its like modest productivity improvments is the best we’ve done in the 4 years we’ve had these models.
I just can’t see it not being a bubble
Yeah, it’s nothing particularly special IMHO. The best feature I’ve found in using it is that, for Microsoft products in particular, it can tell me capabilities of certain things I didn’t know previously when I present it with a problem.
Search engines used to do that before they got enshittified.