Leaving AI completely aside, it still amazes me that people finds "novel" the idea of removing highly-paid white collar intellectual workers (software developers or otherwise) completely out of the loop.
No-code platforms date back to the 80's. Getting rid of engineers in general is even older [*].
Even relational databases and SQL were initially promoted as "ways to get rid of those expensive programmers to access your data" because they resembled some form of English.
The funny thing about the ad below is that stuff like "stop hiring / get rid of humans" would have been seen as highly insensitive in 1950's America, so they touted that as "put them to do something more important".
It's novel because previous rounds of automation were about automating specific tasks or well-scoped functions. There was always an implicit understanding that the white-collar worker would be freed to spend their time on more valuable, higher-level problems. But this time is different because of the generality of the technology. Agents promise to automate the process of thinking itself. And in many domains they can learn new tasks as fast as white-collar workers can find them.
> It's novel because previous rounds of automation were about automating specific tasks or well-scoped functions. There was always an implicit understanding that the white-collar worker would be freed to spend their time on more valuable, higher-level problems. But this time is different because of the generality of the technology. Agents promise to automate the process of thinking itself. And in many domains they can learn new tasks as fast as white-collar workers can find them.
Nah, sometimes the expectation and advertisement was that you could let go of the white collar worker because you're paying the overseas person 1/10th the amount. And "overseas person" is pretty general.
"Everybody knew" it was a bad idea to get a CS degree for a bit after the dot-com bust because of that.
(Some white-collar industries did get hit much harder by that; VFX is one I've heard in that context quite a bit.)
That's a good point. However, overseas people are still people. They need to sleep, get sick, and the better they get at their jobs, the more money they will demand. The cheap ones also often have communication barriers and work slower than the workers they're replacing.
AI models get better and more efficient every 3 months, run around the clock, can be copied infinitely, and unprecedented amounts of capital and research talent are being thrown at any limitations we can see with them (such as problems writing correct code in 2024, lack of agency in 2025, autonomy and self-improvement in 2026). That's the difference between labor replacement through outsourcing vs. labor replacement through automation.
We are either living in different worlds, or squabbling over different meanings of words.
Models have absolutely acquired agency as of 2025. Developers are no longer copy-pasting code from ChatGPT into their text editor, they're working with agents like Claude Code and Codex that can edit code, run terminal commands, do web searches, manage their own context windows, sift through gigabytes of logs with datadog MCP, etc.
Self-improvement is also being worked on. Claude Tag learns over time in slack convos. My company also has an agent that updates its own skill files after every conversation so that we don't need to keep reminding it about the same workflows every time. Is it clunky as hell? Yes. Are the labs plowing billions of dollars into "continual learning" and "recursive self improvement"? Also yes.
What you call a model acquiring agency I call plain old software with productivity workflows designed by humans, with deliberate goals. We must separate “model” and an execution environment using a model. [Model] ≠ [A glorified shell script doing API calls in a control flow based on heuristics]. Agents are not AI, they are plain old software. The weights are the model, and that very much remains a static artifact (and pre-post training models haven’t improved much over the last few years).
What you call self improvement is a duck tape hack to imitate persistence and save on inference. Every time you do an API call, anything that needs to be processed is sent to the model. Narrowing that context down saves money. Finding clever ways to do that improves apparent performance and value. The cleverness is still human.
These are all useful innovations on top of LLMs, which remain models that generate text and symbols based on static weights, which in turn represent training data and the provider’s preferences.
You say that as if the culture difference with a truly alien intelligence is insignificant compared to the culture difference with an "overseas person".
(Even assuming "intelligent" is a sensible label to apply to an LLM holding hands with a shell script in an infinite loop)
I’m at a fully remote company with staff in at least 8 countries speaking at least 5 languages. It works out fine. A possible analogy to AI is that a lot depends on how you use it. The “skill issue” doesn’t disappear, at least not yet.
To colaborate a bit with the no-code part, I worked at a place where they had some flows made with n8n, but the last one from non tech/software engineering left the company and left a bunch of flows breaking, because of some edge cases the flows aren't handling like reissuing credentials, throtling or bad input. The people dependent of said flows reached out to the engineering team to help fix them!
I don't think the no-code comparison is valid, it's always been fundamentally flawed since its many leaky abstractions sitting on top of systems programming code
LLMs can't replace developers but its foundationally different because it can operate on systems code instead of building abstractions on top
Marketing about a more efficient product that requires fewer engineers is obviously not new. The idea that human engineers are obsolete is pretty new, that's the claim that is getting pushback.
I understand that but I think it's in direct proportion of the money being raised, spent and thrown around, including the price tag, to replace such engineers. The more money you ask for, the wilder the claim needs to be.
No-code platforms date back to the 80's. Getting rid of engineers in general is even older [*].
Even relational databases and SQL were initially promoted as "ways to get rid of those expensive programmers to access your data" because they resembled some form of English.
The funny thing about the ad below is that stuff like "stop hiring / get rid of humans" would have been seen as highly insensitive in 1950's America, so they touted that as "put them to do something more important".
[*] https://www.globalnerdy.com/wordpress/wp-content/uploads/200...