It makes you fast. Really fast. In a greenfield project. At the beginning. Then it is all the same grind.

> Github Copilot themselves say that initially, users only accept 29% of prompted coding suggestions (which itself is a wild claim to inefficiency, why would you publicize that?), but with six months of experience, users naturally get better at prompting and that grows to a whopping 34% acceptance rate. Apparently, 6 months of experience only makes you 5% better at prompting.

Or, alternatively, exposure to our robot overlords makes you less discerning, less concerned with, ah, whether the thing is correct or not.

(This _definitely_ seems to be a thing with LLM text generation, with many people seemingly not even reading the output before they post it, and I assume it's at least somewhat a thing for software as well.)

I find LLMs useful to decide what is the best option to solve a problem and see some example code.

Maybe if the number of "Show HNs" has gone up that might be a data point.

What the author is missing is the metric that matters more than shipping product: how much happier am I when my AI auto complete saves me typing and figures out what I'm trying to articulate for me. If devs using copilot are happier--and I am, at least--then that's value right there.

> 55,000 hours of [IT] experience

I didn't know Mike Judge was such a polymath!

I think different things are happening...

For experienced engineers, I'm seeing (internally in our company at least) a huge amount of caution and hesitancy to go all-in with AI. No one wants to end up maintaining huge codebases of slop code. I think that will shift over time. There are use cases where having quick low-quality code is fine. We need a new intuition about when to insist on handcrafted code, and when to just vibecode.

For non-experienced engineers, they currently hit a lot of complexity limits with getting a finished product to actually work, unless they're building something extremely simple. That will also shift - the range of what you can vibecode is increasing every year. Last year there was basically nothing that you could vibecode successfully, this year you can vibecode TODO apps and stuff like that. I definitely think that the App Store will be flooded in the coming future. It's just early.

Personally I have a side project where I'm using Claude & Codex and I definitely feel a measurable difference, it's about a 3x to 5x productivity boost IMO.

The summary.. Just because we don't see it yet, doesn't mean it's not coming.

Places where I got the most out of coding agents are:

- breaking through the analysis paralysis by creating the skeleton of a feature that I then rework (UI work is a good example)

- aggressive dev tooling for productivity on early stage projects, where the CI/CD pipeline is lacking and/or tools are clumsy. (Related XKCD: https://xkcd.com/1205/)

Otherwise, I find most of my time is understanding the client requirements and making sure they don't want conflicting features – both of which are difficult to speedup with AI. Coding is actually the easy part and even if it was sped up 100x a consistent end-to-end improvement of 2x would be a big win (see Amdahl's law).

> These claims wouldn't matter if the topic weren't so deadly serious. Tech leaders everywhere are buying into the FOMO, convinced their competitors are getting massive gains they're missing out on. This drives them to rebrand as AI-First companies, justify layoffs with newfound productivity narratives, and lowball developer salaries under the assumption that AI has fundamentally changed the value equation.

How is this "deadly" serious? It's about software developers losing well-paid, comfortable jobs. It's even less serious if AI doesn't actually improve productivity, because they'll find new jobs in the future.

Pretty much the only future where AI will turn out "deadly serious" is if it shows human-level performance for most if not all desk jobs.

AI is the biggest threat to bs middle management/ba jobs in recent history. Those people panic and try to become "AI ambassadors/advocates" to survive. They are pushing the narrative so that they have answers and "metrics" of adoption to show to upper management and survive another round of layoffs. You can see how it works at YouTube, where someone decided for no good reason to "upscale" Shorts making them all look bad. This is done automatically, without asking for the creators' permission and you cannot turn it off. The results are crap, but who ever made that decision can brag about widespread adoption of AI and survive another annual review.