> The cost of building has collapsed, but the cost of aligning organisationally has not. If anything, it's gone up. When three different teams can each produce a working solution to the same problem in the time it used to take to write a proposal, the bottleneck moves from engineering to coordination.

We're still figuring out how to productively use coding agents as individuals, the next challenge is figuring out how to productively use them within teams. Coding agents reduce one bottleneck - producing working code - but that just moves the bottlenecks elsewhere.

(Note I said "working" code and not "good" code, that's a whole other thing.)

This kind of senior engineering role really depends on the type/size of an org. I've had jobs like this on & off and generally don't stick around for long. There have always been high-impact hands-on-keyboard senior roles that involve coding most/every day..

> The other thing that gave way was thinking time. There's very little of it in my working day now. The productivity gains from AI got captured by output volume rather than output quality.

I actually see this externally from b2b vendors I am a client of. Companies that used to churn out X new products/month are now pushing 4X products but they all suck. The quantity over quality market is going to produce new opportunities for others.

Followed by....

> Senior engineers in AI-forward orgs are doing more leveraged, more hands-on, more meeting-heavy work simultaneously, with the human-focused parts of the role paying for it. The build cost collapsed, the alignment cost rose, the thinking time disappeared, and the productivity gains got captured by output volume rather than output quality. I

What is the job of a senior/lead engineer if not to take the uninformed hype chasing of the senior business, and deploy it in a way that makes things better?

I can't help but feel this senior engineer is talking far too casually about how - under their watch as senior AI engineer chap - engineers spend more time on throwaway code, have less personal development/1-to-1s, and didn't improve code quality. They haven't even mentioned the added financial token cost.

The only thing standing in the way of greedy hype chasing CEOs and a post apocolyptic wasteland is engineers taking their crazy requests and not making the world worse, and it sounds like the author has failed here. I think it's very positive and frank to share their experience, but I'm surprised they don't seem to see their role in it.

As a result, many service companies are moving to product businesses.

will it also happen to developers in other countries? I've no idea.

When I tell this to others, they go in disbelief, but people don't care till their own job is gone.

> The cost of building has collapsed, but the cost of aligning organisationally has not. If anything, it's gone up.

…Oh.

> What gave way is the human-focused work. Mentoring is the clearest example. I have less time for 1-2-1s than I did three years ago, and that isn't an accident, it's a choice I've made under pressure.

Ohh.

> The other thing that gave way was thinking time. There's very little of it in my working day now.

Ohhh.

On the other front, people are saying that NVidia can't deliver stable drivers for like 15 months and they don't want to take software updates at all, they are more happy with last year's drivers.

I think this is a black swan event in the industry. A lot of people already suffered and more people will suffer still. Industry is going to change for sure, but probably not in a way that you would expect. Black swan simply doesn't work that way, it doesn't change industry in a good way, hence black swan.

[1]: https://www.researchgate.net/publication/402969772_The_AI_La...

When I left my corporate engineering job wayyyyy back in March, there were engineers and engineering leaders going off and getting a lot done, individually or in small teams. But project management and QA couldn't keep up with it. Managers resorted to turning their tokens loose on Jira just to try to make sense of it all (which, ironically made them the first to hit their token goals on the dashboard every week, and brought Jira to it's knees).

And, even worse, the junior engineers had no idea what was going on or how to get involved in anything.

The result was an increasingly chaotic mess.

I think AI has a lot of value when used with thoughtful care. I think a lot of the conversations around it are really about frustrations with charlatans.

The author could have written a rather incisive 800 words on this if he'd really tried.

But I will not read 2500 words of redundant, repetitive slop. It's really bad writing.

There is no pacing or conclusion to speak of. It's sort of just a loose list alternating between upsides and downsides, punctuated by the usual bullshit list-y ad-copy summations:

    The build cost collapsed, the alignment cost rose, the thinking time disappeared, and the productivity gains got captured by output volume rather than output quality.

Before AI, trying to program even a simple thing was an exercise in frustration from rules that had only been put in place by programmers to protect their own jobs and make it as difficult as possible for a normal person to develop. Oh! You mixed tabs and spaces, now your code will not compile and you're stuck another day. Oh! You forgot a semicolon, now the code won't run, even though the software points out your missed semicolon and thus knows how to fix it.

AI takes care of all that bagage and now I and others can make fully functional software that solves real world problem for real people.

I want to point out if the organizational model or your team's engineers are resistant to change, it doesn't matter how good of an engineer you are, or how good at proposal writing you are. With or without AI.