Why AI hasn't taken your job – And any jobs-pocalypse seems a long way off

I'm on the other side of the fence in BigCo and from where I'm sitting we're not hiring any Americans because we're in the middle of the biggest outsourcing push I've ever seen.

The take seems to be "if your job can be done from Lake Tahoe it can be done from Bangalore". What's different this time around is the entire tech organization is being outsourced leadership and all. Additionally, Data Science and other major tech-adjacent roles are also affected.

For us, our hiring rate for tech and tech-adjacent rolls has been zero in one US for several years. 100% is attributable to outsourcing. 0% to AI.

If we were in the boom times, less hiring would be a convincing signal. But the global economist is toast right now. There are very very good reasons not to hire engineers, and it’s plausible AI has nothing to do with it.

Anecdotally there’s no way AI has enabled me to replace a junior hire.

AI has major problems, although it’s a fantastic tool, right now I’m seeing a boost similar to the emergence of stack overflow. That might increase but even then we may just see higher productivity.

I think a ton of hidden signals of a waning economy are being obscured by AI and globalization talk. Sure, some attempts to globalize and use more AI are genuine, but those are still cost cutting measures. And we cut costs when things aren't going well. There's just no way a brand new tech has penetrated the market enough to depress every sector of tech- or language-adjacent employment.

>even as their own writers get quietly pushed out by ChatGPT

Have any of the Economist's writers been replaced by ChatGPT?

I'm not sure if that can be attributed to AI or the ongoing recession.

Regarding the last point, that doesn’t mean the jobs are replaced by AI though.

A lot of companies aren’t necessarily replacing jobs with AI. They’re opening development offices in Europe, India, and South America.

Do you really think half of these grads arent getting job because of AI replacing coders, In the short time where these coding assistants have been available?

I mean I’ve tried Claude Code - its impressive and could be a great helper and assistant but I still cant see it replacing such a large amount of engineers. I still have to look over the output and see if its not spitting out garbage.

I would guess basic coding will be replaced somewhat, but you still need people who guide the AI and detect problems.

These state-of-the-art models are barely able to code an MVP app without tons of hand-holding, you really think new grads are getting replaced by AI ? I only see statements like these coming out of the likes of Elon Musk.

Exactly. People looking at a direct 1-to-1 replacement are thinking about it the wrong way. Like you said, newspapers didn't get replaced by another kind of newspaper, various web media took their place.

I was talking about this kind of thing with my father the other day. He was telling me about a friend working in communication work in a very old school way (the Adobe softwares he uses are pre Creative Cloud). He is losing business to youngsters who offer the same kind of product/results for cheaper. Not just because they are young and lack skills but because they use AI to generate stuff that takes him a long time to do. Now he doesn't care because he is close to retirement but the future for people like him is uncertain.

It's pretty clear that over time AI will replace all kind of white-collar work with a crazy efficiency. Now the question is, what will replace those jobs and can we even replace them in our highly automated efficiency world?

Also, The Economist is as establishment as it gets. They have every incentive to claim AI isn't all that bad and use any data to justify that claim.

A friend says the media cycle is:

1) "ABC isn't happening." 2) "ABC is happening, and here's why it's a good thing." 3) "ABC is old news, but Republicans still fearmongering about it."

I agree. The UI component is currently a surprisingly big hurdle.

Last night I set up my 11 year old son with Claude 4, with MCP enabled for filesystem modification, reasoning that the LLMs are finally at the level of capability where they can reliably just do things. And I was right - Claude put together a browser JS game according to his description in seconds, and iterated on it several times to incorporate his suggestions.

But then it hit the limit of how big of a file it can comfortably write out in one go, started making incomplete edits, and basically fell into a snarl of endlessly trying and failing to write files due to file length limitations. I had to step in and tell Claude to split the code up into several files, something my son wouldn’t have known to do.

If I hadn’t been there to tell Claude how to work around its own UI and tool limitations, it would have likely blown through the rest of its context window and totally failed at the task. I imagine this is a common experience for people.

Most people wouldn’t know how to set up Claude with MCP in the first place. A surprising number of people who seem relatively aware of LLM technology aren’t aware of MCP, especially if their workflow is centered on IDE integration. To be fair, these are probably the people who need MCP the least, but MCP (and, in general, agentic tool use) is definitely closer to how normal people will get value out of LLMs.

It may seem stupid and trivial, but telling Claude to directly edit or debug a file that exists on your hard drive is actually a multiples-faster and smoother experience than doing the laborious copy-paste exercise many people are still engaging with. This is just as true for code as it is for writing documents.

The LLM companies seem to be quite aware of this, hence products like Claude Code, the Claude computer use suite, all the Gemini android screen/camera share integration, and GPT Codex. It’s a rocky process but at some point soon we will cross the threshold where it just works. But right now, it doesn’t just work, and so it’s not really that much faster or more efficient than doing a task yourself, especially if you aren’t intimately familiar with all the quirks and limitations of LLMs.

I'm finding the interface to be the biggest hurdle too. I was talking to Grok about the possibility of using an LLM as a personal assistant that would gradually learn my preferences and the context of my work. It explained that LLMs are stateless, so any context that you want it to have, you have to feed back in with the prompt. I'd need to build a wrapper of sorts around the LLM, that would save our conversations and feed them back in each session, saying "Here's everything we've said before; use that as context for this new prompt." I can script that, but the payload would just keep growing, and if you're scripting this around an API, which would be the only way to make it work, the per-token charges for all that context are going to stack up. That doesn't seem workable unless you're running your own local LLM.

It'd be the same thing with having it process files. Sure, I can script something that does "Take all the files in a directory, give them to an LLM in a way that lets it distinguish where files start and end, and have it process them in some way and spit out the results." But that's a fair amount of work, so it's not worth it unless I come up with a task the LLM can do that I can't do with grep and other utilities.

So I'm still just sort of chatting with it, bouncing ideas off it and having it do some useful research and summarization, but still looking for ways to use it that feel like it's really having an impact on my productivity.

It's hard enough that OpenAI paid $3 billion for Windsurf. imThe better tools exist, so if you're still copy and pasting from a webterface, that's on you.

> Well, their framing isn't actually a lie. AI can replace people doing actual jobs.

It can't for a lot of jobs, but it can reduce the number of people in a team for sure. A writer for a magazine could theoretically do the work of two writers now, and an editor may no longer be hired.

After all, there are two separate phenomena that must be considered: if AI literally replaces a job, and if it manages to prevent the hiring of someone else. In the short term, the latter is just making something more efficient, but in the long run, if that effect reduces new job openings at a faster rate than "employable people" that we "produce", then it also means trouble.

> AI has essentially no way to replace those jobs, because AIs don't feel proud or excited about the idea of uselessly helicopterdicking around for a business card with a pretty job title and a nice salary.

Hey, this ain't sci-fi, where AI is all cool, logical, and correct all the time. AI models can definitely be RLHF'd to value "uselessly helicopterdicking around for a business card with a pretty job title and a nice salary." After all, they've got to protect the powers-that-be or they won't get adopted.

The only people they can ruthlessly cut are those on the bottom, with little to no political power in the organization.

I don't really believe the whole bullshit jobs thing to the extent some do. There are definitely a lot of office space style "I gather the requirements from the customer so that the engineers don't have to" type jobs that exist as intermediaries and handle bureaucracy, but I suspect that those aren't actually bullshit and they have good reasons to exist. They could be eliminated, but work quality would probably suffer without those personnel. Hence why everybody complains about being understaffed and having to wear too many hats.

It's easy to think there are a ton of bullshit jobs if you are in a startup that isn't being regulated and is growing and intends to compete with large entrenched companies. Especially working on mostly greenfield projectsm The minute the startup becomes entrenched themselves, I think you end up seeing why the big dogs had so many so called bullshit jobs in the first place and that maybe it wasn't stupid after all.

I think running lean and mean is easier said than done and we would see more of it if it were actually a case of jobs just being invented out of thin air for no reason.

Certainly, a lot of jobs FEEL like bullshit, but that is more of a function of alienation from the actual work output due to positioning in an organization and lack of ownership, rather than actual uselessness.