[n8cpdx]

Article does not make the case for why you must keep up.

AFAICT the best strategy would have been to completely tune out AI for the last ~3 years:

- AI has not meaningfully improved productivity (unless you’re doing something super basic like react and were already bad at it). If you are using AI in a transformative way, that looks different today than it did 6 months ago. - AI has not stolen jobs (end of ZIRP did that) - The field changes so fast that you could completely tune out, and at any moment become up-to-date because the news from 3 months ago is irrelevant.

I don’t get where this meme that “you have to keep up” comes from.

You have agency. You can get off the treadmill. You will be fine.

[bluefirebrand]

I have been tuning out for the last ~3 years and unfortunately it hasn't been the best strategy because the hype is still running roughshod all over me

It is very likely my employer will use my AI apathy as an excuse to include me in the next round of layoffs, compared to my coworkers that are very AI enthusiastic

[scellus]

Maybe that would even be justified, if you are a software developer? If not now, at least soon.

Imagine a software developer who refuses to use IDEs, or any kind of editor beyond sed, or version control, or some other essential tool. AI is soon similar, except in rare niche cases.

[hagbarth]

Version control is different since it’s collaboration with the rest of the org.

The rest: if they are just as productive as others, I would not care one bit. Tool use as a metric is just bad.

[sshine]

I've met many people smarter than myself who object to all of those.

One professor thought syntax highlighting was a distraction.

Lots of colleagues used vim/helix instead of IDEs.

I haven't met anyone who refused version control from an intelligent standpoint.

The most reasonable objection to AI from people who don't hate it are:

  I just don't know how it could help me; it's not as skilled as me at my job, and I'm already doing fine.

[chasd00]

They're not that hard to learn how to use. If your employer asks you to use one then just learn whatever tool the license you for, it's not that big of a deal. It's like learning how to use your employer's official IDE or email client.

[bluefirebrand]

What exactly am I supposed to learn?

Cursor is just VSCode with annoyingly slow intellisense and bad code suggestions, what is there to learn, genuinely?

[sshine]

The article uses "why" in the title, but does not follow through with an answer.

It sort of hints at one reason:

> The most common errors of misunderstanding are either underestimation (“it’s all hype that will blow over”) or overestimation (“I don’t need programmers anymore”). These patterns are rooted in a lack of a solid understanding of the technology and how it is evolving over time.

So if you don't at least find some middle ground between those two poles, you will make uninformed choices.

But I agree: It is safe to ignore AI for now.

I do sense that some people attach to AI because of a fundamental anxiety that it might transform society quickly and detrimentally, because that's part of the hype speech ("it will murder us all, it will make us all unemployed, it will turn us into slaves, maybe you can ride the dragon, and maybe you must").

---

> AI has not meaningfully improved productivity

This is contended.

As the article says, we are in one of the most polluted information environments.

People will say "It's absolutely useless" and "It has fundamentally changed my life."

So neither extreme can be taken at face value as representative; they're samples of a murky picture.

> The field changes so fast that you could completely tune out

It's not that fast, in my opinion. Last big steps:

  - Transformer architecture (2017)
  - Larger models with greater performance (2020-)
  - Chain of thought (research in 2022, commercial breakthrough in 2024)
  - Agents (since forever, but 2022 for GPT-based agentic frameworks)

Other things happened; for example, DeepSeek making an architectural breakthrough and challenging the financial model of open/closed weights.

But most of the hype is just people trying to make commercial success on a few cornerstone breakthroughs.

In one to two years, maybe we can add one more major advancement.