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What is happening to jobs? Separating AI hype from reality

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151–160 of 412 posts

Re: What is happening to jobs? Separating AI hype from reality

#151

99% of the AI product pitches I see here are for some kind of marketing tool. Its really sad

This is so true. It has so much potential to help with humanity's actual problems. But no, lets use it to manipulate people even more.

Re: What is happening to jobs? Separating AI hype from reality

#152
post #27
post #2

A challenge with this kind of study is that coding agents (Claude Code, OpenAI Codex) only started working really well in late November, which for most people meant early January due to the December break. General agents (OpenClaw, Anthropic Copilot, ChatGPT "Work") started working even later than that. This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using…

> A challenge with this kind of study is that coding agents (Claude Code, OpenAI Codex) only started working really well in 2026? 5? 4? 3? Heard this one way too many times.

November 2025: https://simonwillison.net/tags/november-2025-inflection/

Re: What is happening to jobs? Separating AI hype from reality

#153
post #7

Organizational inertia is a real thing. There are still fortune 500 companies with internal bans on AI. A lot of the answer to "how much impact has AI had" comes down to "how much have we even attempted?" In my workplace, we're going to decline to renew some software subscriptions because a non-programmer vibe-coded their replacement in a week. The impacts are here, they're just not evenly distributed yet.

> In my workplace, we're going to decline to renew some software subscriptions because a non-programmer vibe-coded their replacement in a week.

This is curious to me, as at my workplace we never had such subscriptions for small- to mid-size stuff and always built the corresponding tooling in-house.

Re: What is happening to jobs? Separating AI hype from reality

#154
post #2

A challenge with this kind of study is that coding agents (Claude Code, OpenAI Codex) only started working really well in late November, which for most people meant early January due to the December break. General agents (OpenClaw, Anthropic Copilot, ChatGPT "Work") started working even later than that. This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using…

> This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using from 2022-2025.

Mostly an impact on software development - I'm not seeing broad automation and layoffs in industries like law, finance etc. It will gradually happen but due to issues with memory, reliability and long term planning of LLMs there are real barriers. Even in software development - while it has completely transformed the field I don't think many people still believe we won't need devs in 2027 or that their amount will shrink by 50%.

Re: What is happening to jobs? Separating AI hype from reality

#155
post #2

A challenge with this kind of study is that coding agents (Claude Code, OpenAI Codex) only started working really well in late November, which for most people meant early January due to the December break. General agents (OpenClaw, Anthropic Copilot, ChatGPT "Work") started working even later than that. This category of software may have a much more meaningful impact on work than the mostly-chat systems we were using…

And yet I have felt a general code quality decrease and overall enshittification of software products since 2023 when people were already using copilot. Or I am just biased to use that to justify any overengineered piece of shit code with that because I refuse to think any sane person would come up with such contrived code and I am looking at the wrong places.

Re: What is happening to jobs? Separating AI hype from reality

#156

Earlier quoted context omitted.

This is the opposite of my experience since about February of this year.

The quality of the output is so variable. It depends on the model, “effort level”, prompting, probably even the programming language/app functionality, and libraries involved. For example, I find LLMs are best at making simple web apps. These web apps, while simple, would still take a senior engineer perhaps a week or two to create, but LLMs can spit them out inside of an hour. Conversely, LLMs struggle with things l…

What model struggles with Docker or local model deployment?

I have had good results in that area with GPT 5.5 in the past.

On the subscription plan I don't use anything but xhigh effort and Fable, 5.6 Sol, or now also Opus 5.

Is that the class of model that struggles with Docker for you?

Re: What is happening to jobs? Separating AI hype from reality

#157
post #110
post #85

Earlier quoted context omitted.

I get the point having read much the same from Tesla (and fans) regarding self driving cars that still haven't done half the things that Musk said was just around the corner pending regulators a decade ago and repeatedly since then. And myself I keep making comparisons between AI and the progress in 90s video games where every minor improvement got called "photo realistic" and then forgotten with the next game engine…

I’m probably illustrating your point but as a FSD fan it really got ”good enough” recently with version 14. The tipping point was suddenly, much more often than not, it can drive end to end from start (my garage) to finish (parked at destination) with no interventions. I can text and watch videos on my phone and as long as I glance up once a minute, it doesn’t complain. Handling highway driving with lane changes was…

Please don't text and watch videos when you drive.

Re: What is happening to jobs? Separating AI hype from reality

#159

Earlier quoted context omitted.

It seems to be true this time though; I have observed it myself and heard it from several experienced developers I personally know and respect. It feels like some threshold was crossed with Opus 4.5 and Gpt 5.3, where the models are now able to reliably solve certain classes of problems that were previously unreliable. Time will tell of course, and it’s early, but inflection points do exist with progress.

Thing is. You can find an extremely similar paragraph written about Claude 4.x or some equivalent gpt. And simultaneously, many people expressing their frustration and the shortcomings of “But it’s different this time” - several people, several times over the last couple of years. This is not at all a dig at you, I’m very sorry if it reads that way. My point is these things only get truly better in anecdotes. The way…

LLM capabilities are spiky. They're amazing at some things, and poor at others. Over time, the set of things they're amazing at has grown, while the set of things they're poor at has shrunk. If you think LLMs are just "mediocre" without any nuance, that's a sign you haven't spent the time to evaluate them in order to make an informed opinion.

Re: What is happening to jobs? Separating AI hype from reality

#160
post #95

Earlier quoted context omitted.

I guess it's important who one hears this from. I just spoke to a fried who is a headhunter and who's been trying to automate his processes for a while (he likes to fiddle and certainly has skills, but he's not an engineer). He kept trying, but it just wasn't good enough. Now he said with GPT Work and Sol, it worked, but the key point is: all of it suddenly worked. The problem was one of reliability, of handling edge…

Again I've heard this since 2022 when gpt3.5 came out. This is like microprocessors in the 80s. Sure they double in capability every 18 months but the start is so pathetic it will be 30 years before they are good enough for everyday tasks.

CPUs in the 90s were amazing! They were over-specced for "everyday tasks." Our problem is that we overbuilt CPUs too much, so software is now written with ten unnecessary layers of abstraction because there's no real reason to simplify.
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