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>Nobody’s doing anything like that for other productivity tools even when they’re proven to be helpful. Isn't mandating IDE usage a perfectly reasonable and common thing? It's a productivity tool after all.
But there's other reasons for that - makes support easier, can have same linting setup etc, its not done to increase productivity.
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>Nobody’s doing anything like that for other productivity tools even when they’re proven to be helpful. Isn't mandating IDE usage a perfectly reasonable and common thing? It's a productivity tool after all.
I've never seen an IDE "mandated", I've seen officially supported development setups where you're on your own if you do anything different. Is that not the standard?
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I'd never have worked at a place that mandated a specific IDE. Luckily it's something I never encountered, if it's ever done this is the first I'm hearing about it.
But you'd have to use an IDE right?
I was usually most productive with a text editor as opposed to an IDE but I'd sometimes use an IDE as needed or when I wanted to try something new.
The article isn’t providing a lot of convincing data that AI improved much of anything, only that it didn’t cause incidents. I really don’t understand why AI usage is mandatory for roles. Nobody’s doing anything like that for other productivity tools even when they’re proven to be helpful. Hell, a lot of employers can’t be bothered to provide basics like nice keyboards and monitors that exceed 1080p. The current era…
The monitors thing is funny to me because I love using dual monitors at work, and my coworker doesn't, and this forced AI adoption would be like if I forced him to use dual monitors.
I was really looking for tangible, actionable advice since I'm facing slow adoption in my org. This post seems to hide behind the "secret sauce" that it claims made all of the difference.
Then, measure time taken, AI usage, and sentiment of AI usage.
With this, we find out how quickly was the task done, how much AI was used, and whether the individual was frustrated at any point and if the process went smoothly etc.
My system already hooks into top AI providers and measures these outcomes for engineers. Working on measuring other use cases. Email in profile if anyone wants to chat.
Now of course we can't do a blind comparison with the exact same task, but this at least gives insights into usage, outcomes, and ease-of-use.
I was really looking for tangible, actionable advice since I'm facing slow adoption in my org. This post seems to hide behind the "secret sauce" that it claims made all of the difference.
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This was just our first post FWIW, and we definitely want to follow up with more concrete demos/details/etc here. I am working on another post specifically about how we leverage our internal RPC system to make adding AI tools super easy so expect more from us.
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If someone wants to pat themselves on the back with how great they think they are, thats cool, but I dont think its really worth talking about. …unless they have something to show, specifically? Demos? Code? Details? Nothing?
They actually revelead an interesting tidbit where they are with AI adoption and how they are positioning it now to new hires, e.g. "we made AI fluency a baseline expectation for engineers by adding it to job descriptions and hiring expectations".
It seems inevitable now that engineering teams will demand AI fluency when hiring, cuious though what they are doing with their existing staff who refuse to adopt AI into their workflow. Curious also if they mandated it or relied solely on incentives to adopt.
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I've never seen an IDE "mandated", I've seen officially supported development setups where you're on your own if you do anything different. Is that not the standard?
Your job will look pretty funny at you if you want to code everything by hand while everyone else is using VSCode.