My intuition from talking to people across different parts of the industry, is that adoption at bigger companies is really limited or slow, or totally banned. Additionally some developers are not seeing it help their specific roles all that much anyway. This is hard to level with success other people are having, but software is a super broad discipline which I think explains a lot of the mixed success stories.

It seems to depend a lot on the industry and niche you're in, working at an agency I get experience across many different projects and industries and sometimes you are just at the edge of AIs training and it can get very unhelpful. Noting many if not most companies are working on proprietary code in donain specific problems, that isn't all that surprising either.

I used to think this was a sign that AI code isn't really useful, but I've changed my tune (also I believe these numbers have changed in the last few months).

As an example: One of my most promising projects I was discussing with a friend and we realized together we could potentially use these tools to build a two person agency with no need to hire anyone ever. If this were to work, could theoretically make nice revenue and it shouldn't show up in any metric anywhere.

Additionally I've heard of countless teams cancelling their contracts with outsourced engineers because cheap but bad coders in India are worse that an LLM and still cost more. I'm not sure if there's a number around this activity, but again, these type of changes don't show up in the usual places.

My current belief is not that AI will replace traditional software engineering it will replace a good chunk of the entire model of software.

>funny that so many people are using AI and still hasn't really shown up in productivity numbers or product quality yet.

That's because the threat is now not other businesses, but your own users who decide to vibe-code their own "Claw" product instead of using your company's vibeslop, so there are no buyers for your single-week product. All these new harness developers are engaging in resume-driven development to save their own asses. The only ones that are not naked when the tide recedes are the ones that are able to jump to the next layer of abstraction on the infinite staircase, until the next tide comes five seconds later.

I think if you're doing front-end development AI is good. If you are reading a db and sending a json to said webpage AI is decent, if you are doing literally anything else AI is next to useless.

At least, in my own experience.

This is actually an old syndrome with technology. It takes a longt ime for the effect to be reliably measured. Famously, it took many years for the internet itself to show up in significant productivity gains (if the internet is actually useful why don't the numbers show that? - a common comment in the 1990s and 2000s). So it seems to me we're just the usual dynamic here. Productivity in trillion-dollar economies do not turn on a dime

I wouldn't say it hasn't shown up. The number of ShowHN's per weekend has definitely gone up, and while that isn't rigorous scientific proof, I'd consider is a leading edge indicator of something. Unfortunately, we as an industry have yet to agree on anything approaching a scientific measure of productivity, other than to collectively agree that Lines of Code is universally agree that LoC is terrible. Thus even if someone was able to quantify that, say, they're having days where they generate 5000 LoC when previously they were getting O(500) LoC, that's not something we could agree upon as improved productivity.

So then the question is, lis there anything other than feels to say productive has or has not gone up? What would we accept as actual evidence one way or another? Commits-per-day is similarly not a good measure either. Jira tickets and tshirts sizes? We don't have a good measure, so while ShowHN's per weekend is equally dumb, it's also equally good in the bag of lies, damn lies, and statistics.

If true, only because people knew where to dig and did it with purpose.

Agreed, often see cope from managers along the line of “writing the code was never the bottleneck”. Well, sure felt like it.

Because designing systems that work well is difficult. It takes years of experience to develop the muscle memory behind quality systems architecture. Writing the code is an implementation detail (albeit a large one).

Are we sure it's not failing anymore after the advent of LLMs?

Because coding bootcamps and CS programs were churning out squillions of people who could type the code but had poor design and analytical skills, because there was a time where being able to implement Dijkstra on a whiteboard would get you 400k at a FAANG.

I mean, juicero got the money instead of the slaps in the face it deserved. And there's thousands of startup like that. I think VCs are terrible at picking and a dice would probably do a better job.

And yet, who would you trust more - a CEO that raised 100M on their "vision" or someone who got slapped in the face?

A raise is random noise, not signal, based a confidence game within the VC ecosystem. LP capital call->GP gamble based on waves arms around considering VC underperforms as an asset [1] [2] class even when accounting for the grand slam returns. It's 0DTE options gambling dressed up as skill and an art. But, you know [3] [4] [5], lottery still pays out sometimes.

TLDR A raise is not robust signal in this regard.

[1] https://news.ycombinator.com/item?id=7260137

[2] https://www.linkedin.com/posts/peterjameswalker_most-venture...

[3] https://en.wikipedia.org/wiki/There%27s_a_sucker_born_every_...

[4] https://en.wikipedia.org/wiki/Overconfidence_effect

[5] https://en.wikipedia.org/wiki/Survivorship_bias