Hacker News

> The result, in my case, is that I code more than I have in years. Three years ago I coded maybe once a fortnight, mostly throwaway PoCs to demonstrate concepts. Now I code most days of the week, in between other work.

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.

This piece is really good:

> 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.)

When a long article is topped by an AI-generated image, it makes me wonder if I should bother reading. Did a human write this?

No, it isn't sustainable. There is a paper called "The AI Layoff Trap"[1], it says that it is a prisoner's dilemma and this is why this dude feels like he's in an arms race.

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...

It makes me wonder if large engineering organizations are going to splinter. The coordination costs are getting, proportionally, much larger than they used to.

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've always been frustrated by charlatans who do a great job advancing their own goals at the cost of those foolish enough to actually care about doing a good job. AI is a very empowering tool for these kinds as it is super effective at creating facades of productivity and thoughtfulness.

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.

I read it but I don't really understand the writing.

You could have just told us you're a slop slinger and save everyone some time.

Do not bother reading this.

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.

Thinking that memorizing insane code rules is being skilled in making software is like thinking that memorizing all the generals' birth days is being skilled in warfare.

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.

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> The engineers who've adopted these tools effectively get heard more often, get their proposals taken seriously more often, and shape direction more than those who haven't.

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.