In other places, look for hiring freezes and re-orgs, rather than straight and obvious message from management: "Say bye to Bob, he's been replaced with this AI agent".
To everybody's point, not a new thing - automation, including what may of us have worked on for decades, by definition is simplifying, making more efficient, or reducing human effort.
But to your specific question - HN seems to have a couple of excited stories a week about a person saying "I don't really know coding, but I've started my tiny niche SaaS with help of AI". Which is not necessarily a bad thing, and more along the curve of all the other advancements - perhaps the question is the speed of improvement(replacement) and change on this particular one.
How are you going to debug/extend the code if you don't know how it works?
The phrase "don't really know" is kind of doing the heavy lifting here - for example, I myself haven't done professional programming in 20 years, but I know the basics. Enough to be structured in my design / requirements / direction to LLM, and to read and comprehend the advice others have discovered and shared. With that in mind, extending the code seems to work fairly well - start with basic requirements and extend them through LLM. Having not done coding in 2 decades, I've asked ChatGPT to create a python script to interact with a website's API and retrieve an object; then I've extended it to retrieve and store multiple objects, then to input for parameters, etc. it was fun!
Anyhoo, the use case discussed is not necessarily a complex enterprise resourcing application; but a little niche webapp with simple requirements, created by somebody who understands the domain itself more than coding, and which may be exciting to a target requirement, seems eminently doable with today's LLMs -- again, the proof is in the pudding of people who have done it, rather than my claims :)
But ya, I see the future for SWEs as not only being able code, but being able to review code created by AI, and being able to write prompts to get AI to generate code.
https://x.com/benln/status/1889388151770325427?s=46&t=tl870z...
But I don’t think the advent of LLM is responsible for any job cut in these companies. The overall startup ecosystem is (Stripe, cloud computing, efficient customer support software, etc).
But the fact that Cursor is one of those impressive companies shows the demand for AI assistance is huge
Tell that to all the customer service AI chatbots. They don't need as many real CS agents anymore because one chatbot can reply to hundreds or thousands of tickets with useless garbage copy-pasted from the FAQ. Given that even most real CS agents also only do that nowadays anyway, yeah they've been replaced.
This tends to be incredibly effective at CS's real job, which is to make customers with problems go away from being able to make it to bothering the actual consumer-unfriendly-decision-makers. If you start looking for this you will see it absolutely everywhere. Chatbots are really really good at making people too frustrated and exhausted to pursue other routes.
There are a few companies whose CS actually still is good (like Mila Cares!!!) but in my experience most CS just wants to get rid of the annoying customer.
Also, sort of related (to me, blame my autism), I've heard that the practical effect of a suicide hotline can be annoying the caller enough for them not to do the thing. I've had at least one or two friends told me that this was the effect it had on them. (they're doing better nowadays)
Most anti-AI arguments can be dispensed with by recasting them in terms of the broken-window fallacy. This is certainly one of them.
Could you explain how and what fits the broken-window fallacy here? Is it the AI abolitionists? (I know at least one person who violently hates AI and anything relating to AI and firmly believes that there is absolutely no place for AI or LLMs anywhere in the world and that any usage at all for any reason whatsoever is utterly deplorable. I don't talk to this person since they tend to flame at others for using or talking about AI for any reason.)
That's where the broken-window fallacy comes in. It's not just a matter of paying someone to break all the glass in town to make work for the glaziers, it's like responding to the invention of cheap shatterproof glass with the same flawed zero-sum reasoning.
(I'm rate-limited so can't reply, but my position is basically that 100% unemployment is a good thing, not a bad one. We can't get to a post-scarcity society by doing things the same way we've been doing them, or by retrying the same alternatives that have failed before.)
I keep seeing cashiers replaced by self-checkout machines at stores, fast food jobs might be too complicated for certain people (like me - I couldn't do it), places like say the Apple Genius Bar require you to know what you're doing, etc. Maybe I'm super naive and first-world by missing something super obvious, but if I am then maybe I could learn something today.
Can you answer my question about an "AI native" company that never even had people to replace?
(You're Alice btw) :
Alice's response has a few issues:
Shifts the Goalpost:
Bob's point was about AI's impact on existing jobs—he's arguing that AI increases productivity, not that companies like OpenAI don't need people. Alice shifts the discussion to whether OpenAI, an AI company, is hiring people, which isn't directly relevant to Bob's claim.
Strawman Argument:
She implies that if AI is truly productive, OpenAI shouldn't need to hire. But OpenAI is in a high-growth phase, likely hiring to build and maintain the technology, not to replace traditional roles with AI. AI productivity doesn't mean zero hiring—it often means hiring in different areas or scaling faster.
Burden of Proof Misstep:
Alice demands proof from Bob while making her own claim ("baseless assertion") without providing evidence that AI is directly causing 1:1 replacements.
Weak "AI Native" Point:
The question about "AI native" companies might sound clever, but it doesn't address Bob's core argument about existing companies using AI to do more with fewer people.
Most software developers don't work for Google. They don't need a degree. They are making basic crud applications or some other apps that are chaining APIs or libraries together.
The difference between a junior and a senior in these kind of jobs is productivity and code quality/ maintainability. If you don't think current gen LLMs help with that you are delusional
I barely get 1 line of code that I’d actually ship unchanged. It’s really useful but still has a long way to go
Anyone skilled enough to code can now codes in any language. Jobs aren't being replaced but no longer added.
I also demonstrated how an intern (1st year) was able to replace a 5 year experience position after six weeks of working with AI.
We're seeing a 5x acceleration in shipping after our first year with limited exposure.
Don't you think that it might be more efficient to just communicate with the bullet points?
The operations crew is having it automate metrics rapidly. Senior developers are increasing their throughout rates. Things come back to code review in a generally better state because folk say "hey, review this for me".
Is it a real developer? Not at all. Is it affecting our hiring or anything? Nah. But it's already a huge help and rapidly getting better with new models (o3 / deepseek), tooling (CSP and agents), and integration (cline, cursor, memory prompting).
Idea to bank to pull funds to 3d print to market validation in a day.
Example from last week: pasted my terraform that was using internal custom modules and prompt that based on this code build additional services not yet built using the module output so they could all communicate.
First run. 100% accurate. Zero typing after paste and prompt. 2 minutes of time.
It probably saved me an hour at least of looking up module output and documentation with the additional services.
It may be minor or simple yet I now have an additional hour.
While every single developer now uses LLM, the outcome really depends on how one is using it.
That was always true. Once you learn how to program, it doesn't take a ton of effort to learn another language. It takes more time and effort to master a new language, but that's still just as true as it ever was.
Otherwise we might as well predict that when all is said and done, AI will have no more impact than the fax machine, which is what someone once thought of the internet, and which seemed a lot more reasonable on dial-up AOL than in today's world.
What the competent people are saying is often overshadowed by the echo chamber of misleading information, since there is profit in driving people towards chaos.