It's not that I don't believe you, but the "top-10 X" format is so easy to replicate that I highly suspect that it was pushed by one single company.

Proof / refs?

I think this became this book: https://www.goodreads.com/book/show/26030703-disrupted right?

I remember this book well.

I also remember thinking “this guy kind of seems like a self-impressed jerk,” while reading it.

Not that HubSpot didn’t earn their portrayal as a hype-driven business run by clowns, but the author lost me when he described himself getting into a passive aggressive Facebook comments argument with coworkers as an indication of how stupid they were… when all I could think was “you’re all idiots, cut the FB drama and get back to work.”

It seemed like he was kind of looking for a fight the whole time. Like… if you’re shocked a marketing tech startup runs differently than a newsroom, that’s on you.

Admittedly, more detail would be better, but this high-level stuff is mostly the level that engineering leaders are discussing this topic currently (and it is by far the most discussed topic).

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.

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.

Because they started as a spam farm and now they're a slop farm?

I wanted to reach out but I couldn't find your email. Mine's in the profile if you want to chat.

Out of curiosity, do you have thoughts on why the slow adoption?

> We pulled metrics on code review burden, cycle time, velocity comparisons before and after adoption, and production incident rates.

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.

It's crazy how fast we went from big data and every exec needing some massive dataset with cooked up numbers to justify even the smallest decision, to this, where nothing matters except for ~vibes~. Does AI increase productivity? Does it improve or degrade quality? Who knows, but number must go up.

It’s the same trend of executives claiming RTO increases user productivity according to their data but could never show the data.

>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.

People that don't code think that something can do code 98% correct is surely better, without seeing the hard enforcement of a 2% error without manual intervention. I think all of the jokes about stupid computers and weird behavior of languages when you use them out of spec (famously labeled wat) gave people the wrong impressions about why those problems exist or how they can or cannot be fixed. You'd think they'd be able to transfer that cynicism quicker to models since they are also dumb computer things but apparently they say "hello" and that is tricking them out of that?