Weird take. Just because you can use curl it doesn’t mean you can’t value a GUI to be able to store and manipulate requests quickly and view a formatted response body.
I use postman all the time to explore apis. Sure I could do it from the command line, but this is quicker and it saves my request payloads.
(Though now I’m obviously open to suggestions for better tools)
Weird take. I thought for myself about the problem and solved it rather than externalize such and end up locked into an increasingly abusive relationship.
Been using homegrown scripts designed around wget and curl, accessible as shell aliases so I save time never downloading Postman or developing muscle memory for it, yet can still explore APIs
There's an idea for a better tool; the one you patch right in to your workflow to avoid context switches to a GUI mental model; I just focus on computer generating data rather than color of the virtual captains chair
Not sure if you’re trolling but writing “homegrown scripts as shell aliases” is not faster than a gui. I totally agree Postman is enshittified, but when I just want to see a sample response for given input data, it does the job. Sure I’d like a more lightweight tool, but there’s no way I’m “context switching” to writing shell scripts when I just want to check a single endpoint. (I’d also wager than in many cases, opening a gui and hitting send on a pre-saved request is faster than using an llm too)
You can do what you like though, my original comment was against the gatekeeping and punching down. I don’t care one way or another what tool you use, but let’s not make people inferior because they aren’t using a TUI for everything.
On a micro scale, yes I see this regularly at work: some devs blindly put up ai generated PRs that are fundamentally flawed or don’t actually complete the work in the ticket. It’s often trivial to check this. Similarly some tickets are written by ai that make incorrect assumptions about our product, resulting in nonsensical requirements.
You could argue that these are just examples of laziness, but I think these are both tasks that require critical thinking, and it’s easier to hand them off to an llm that at least purports to do this for you.
I’d argue that both setting requirements, and self code review are both things that need careful attention. (What _exactly_ do you need doing? Does your work correctly do the thing that needs doing?).
I have no fundamental issue with using ai, but there’s no doubt that applying critical thinking to both these tasks directly, and to the broader question of “should I use ai for this job” should result in a different outcome.
Personally I would also not agree with your take that working with llms has allowed me to do “acute critical thinking”. It’s sped up my development time, sure, but I would argue that my evaluation of, say a new sdk now using Claude is far less detailed than it would’ve been in the past when I did it by reading docs. As a side note, I’ve been rereading Douglas Hofstadter’s GEB recently in paperback, and I’ve found a lot of joy in wrestling with paragraphs and writing notes in the margins. This is way more focussed attention than I really give anything when working with llms.
But people who are bad at maths are unlikely to be writing about maths. A crude example might be if you search for “2+2=” in the training data, you’re much more likely to find “4” as the next character.
Obviously llms are far more complex than this, but I think this proves the point. The fact you had to add the “recent” qualifier there highlights that llms in general were bad and had to be provided with corrective targeted training data to improve. (And they still can’t count the R’s in strawberry!)
> And they still can’t count the R’s in strawberry!
Really? I do not have the time to survey the modern LLMs to see if your assertion is correct, but if it is then I'm surprised; I would have thought that that one would have shown up so often in their training data that they would be able to answer that question, even if they would then be unable to (for example) count the R's in raspberry, or in some other word where "count the R's in _____" was not widely found in recent online discussion.
But the OP already addressed this-he can just ask ChatGPT directly how to fix the brakes. He’s gone looking for a human expert because (for whatever reason) he doesn’t want that.
For me the issue is very clear: I happily use AI to answer tons of questions each day, but if I’m reading your website/blog/article/Jira ticket, I expect real human input.
It should matter whether the author “sweated over it for hours”, because that means they actually considered the best way to communicate something. If they didn’t do that, then they clearly don’t care enough about about the quality of their output and I shouldn’t spend any time at all on it. In fact it’s worse than that because if the author doesn’t respect the reader enough to craft their output, then I as a reader have no respect for their work, and I resent that they’ve taken my attention for the time it takes me to realize it’s ai generated. If you’re publishing Ai content, then I can only presume you have an ulterior motive than plain communication- in the case of OP I’d assume this is for ad revenue or clicks.
There are many types of writing, and I struggle to think of many where a statistical model could feasibly produce an acceptable output for the given intention.
Eg. A poet chooses their words extremely carefully; a good instruction manual is written by the designers of the product (not just guessing at a common or plausible method); a news article has an angle/story beyond just the facts.
If you or OP suspect (suspect) that a blogger's taking shortcuts, and that's a problem for you or OP, then you or OP can just skip that blog and find another that appears (appears) to meet some criteria for labor input. To the extent that this is all unfalsifiable, it just should not matter.
I'll go further. Even if it were falsifiable, why should it matter? An example: I subscribe to a reputable US publication and I enjoy its journalism. If it turned out that one of its writers had (somehow) used AI to generate their article (which I enjoyed) in a click, here's what I would say to them: Hats off to you! How did you do it?!
I don't care if the article took them two minutes or if they used AI any more than I care if they used a spellchecker or wrote it while standing upside down. Why should I? The author put their name to the article and I got something out of it. That is all I was ever looking for.
I use postman all the time to explore apis. Sure I could do it from the command line, but this is quicker and it saves my request payloads.
(Though now I’m obviously open to suggestions for better tools)
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