4 ms·

The argument is empty because it relies on a trope rather than evidence. “We’ve seen this before and it didn’t happen” is not analysis. It’s selective pattern m

The argument is empty because it relies on a trope rather than evidence. “We’ve seen this before and it didn’t happen” is not analysis. It’s selective pattern matching used when the conclusion feels safe. History is full of technologies that tried to replace human labor and failed, and just as full of technologies that failed repeatedly and then abruptly succeeded. The existence of earlier failures proves nothing in either direction. Speech recognition was a joke for half a century until it wasn’t. Machine translation was mocked for decades until it quietly became infrastructure. Autopilot existed forever before it crossed the threshold where it actually mattered. Voice assistants were novelty toys until they weren’t. At the same time, some technologies still haven’t crossed the line. Full self driving. General robotics. Fusion. History does not point one way. It fans out. That is why invoking history as a veto is lazy. It is a crutch people reach for when it’s convenient. “This happened before, therefore that’s what’s happening now,” while conveniently ignoring that the opposite also happened many times. Either outcome is possible. History alone does not privilege the comforting one. If you want to argue seriously, you have to start with ground truth. What is happening now. What the trendlines look like. What follows if those trendlines continue. Output per developer is rising. Time from idea to implementation is collapsing. Junior and mid level work is disappearing first. Teams are shipping with fewer people. These are not hypotheticals. The slope matters more than anecdotes. The relevant question is not whether this resembles CASE tools. It’s what the world looks like if this curve runs for five more years. The conclusion is not subtle. The reason this argument keeps reappearing has little to do with tools and everything to do with identity. People do not merely program. They are programmers. “Software engineer” is a marker of intelligence, competence, and earned status. It is modern social rank. When that rank is threatened, the debate stops being about productivity and becomes about self preservation. Once identity is on the line, logic degrades fast. Humans are not wired to update beliefs when status is threatened. They are wired to defend narratives. Evidence is filtered. Uncertainty is inflated selectively. Weak counterexamples are treated as decisive. Strong signals are waved away as hype. Arguments that sound empirical are adopted because they function as armor. “This happened before” is appealing precisely because it avoids engaging with present reality. This is how self delusion works. People do not say “this scares me.” They say “it’s impossible.” They do not say “this threatens my role.” They say “the hard part is still understanding requirements.” They do not say “I don’t want this to be true.” They say “history proves it won’t happen.” Rationality becomes a costume worn by fear. Evolution optimized us for social survival, not for calmly accepting trendlines that imply loss of status. That psychology leaks straight into the title. Calling this a “recurring dream” is projection. For developers, this is not a dream. It is a nightmare. And nightmares are easier to cope with if you pretend they belong to someone else. Reframe the threat as another person’s delusion, then congratulate yourself for being clear eyed. But the delusion runs the other way. The people insisting nothing fundamental is changing are the ones trying to sleep through the alarm. The uncomfortable truth is that many people do not stand to benefit from this transition. Pretending otherwise does not make it false. Dismissing it as a dream does not make it disappear. If you want to engage honestly, you stop citing the past and start following the numbers. You accept where the trendlines lead, even when the destination is not one you want to visit.

habinero 10mo ago
> What is happening now. What the trendlines look like. What follows if those trendlines continue. Output per developer is rising. Time from idea to implementation is collapsing. Junior and mid level work is disappearing first. Teams are shipping with fewer people. These are not hypotheticals. My dude, I just want to point out that there is no evidence of any of this, and a lot of evidence of the opposite. > If you want to engage honestly, you stop citing the past and start following the numbers. You accept where the trendlines lead, even You first, lol. > This is how self delusion works Yeah, about that...
- threethirtytwo 10mo ago
  “There is no evidence” is not skepticism. It’s abdication. It’s what people say when they want the implications to go away without engaging with anything concrete. If there is “a lot of evidence of the opposite,” the minimum requirement is to name one metric, one study, or one observable trend. You didn’t. You just asserted it and moved on, which is not how serious disagreement works. “You first, lol” isn’t a rebuttal either. It’s an evasion. The claim was not “the labor market has already flipped.” The claim was that AI-assisted coding has changed individual leverage, and that extrapolating that change leads somewhere uncomfortable. Demanding proof that the future has already happened is a category error, not a clever retort. And yes, the self-delusion paragraph clearly hit, because instead of addressing it, you waved vaguely and disengaged. That’s a tell. When identity is involved, people stop arguing substance and start contesting whether evidence is allowed to count yet. Now let’s talk about evidence, using sources who are not selling LLMs, not building them, and not financially dependent on hype. Martin Fowler has explicitly written about AI-assisted development changing how code is produced, reviewed, and maintained, noting that large portions of what used to be hands-on programmer labor are being absorbed by tools. His framing is cautious, but clear: AI is collapsing layers of work, not merely speeding up typing. That is labor substitution at the task level. Kent Beck, one of the most conservative voices in software engineering, has publicly stated that AI pair-programming fundamentally changes how much code a single developer can responsibly produce, and that this alters team dynamics and staffing assumptions. Beck is not bullish by temperament. When he says the workflow has changed, he means it. Bjarne Stroustrup has explicitly acknowledged that AI-assisted code generation changes the economics of programming by automating work that previously required skilled human attention, while also warning about misuse. The warning matters, but the admission matters more: the work is being automated. Microsoft Research, which is structurally separated from product marketing, has published peer-reviewed studies showing that developers using AI coding assistants complete tasks significantly faster and with lower cognitive load. These papers are not written by executives. They are written by researchers whose credibility depends on methodological restraint, not hype. GitHub Copilot’s controlled studies, authored with external researchers, show measurable increases in task completion speed, reduced time-to-first-solution, and increased throughput. You can argue about long-term quality. You cannot argue “no evidence” without pretending these studies don’t exist. Then there is plain, boring observation. AI-assisted coding is directly eliminating discrete units of programmer labor: boilerplate, CRUD endpoints, test scaffolding, migrations, refactors, first drafts, glue code. These were not side chores. They were how junior and mid-level engineers justified headcount. That work is disappearing as a category, which is why junior hiring is down and why backfills quietly don’t happen. You don’t need mass layoffs to identify a structural shift. Structural change shows up first in roles that stop being hired, positions that don’t get replaced, and how much one person can ship. Waiting for headline employment numbers before acknowledging the trend is mistaking lagging indicators for evidence. If you want to argue that AI-assisted coding will not compress labor this time, that’s a valid position. But then you need to explain why higher individual leverage won’t reduce team size. Why faster idea-to-code cycles won’t eliminate roles. Why organizations will keep paying for surplus engineering labor when fewer people can deliver the same output. But “there is no evidence” isn’t a counterargument. It’s denial wearing the aesthetic of rigor.

habinero 10mo ago

> What is happening now. What the trendlines look like. What follows if those trendlines continue. Output per developer is rising. Time from idea to implementation is collapsing. Junior and mid level work is disappearing first. Teams are shipping with fewer people. These are not hypotheticals. My dude, I just want to point out that there is no evidence of any of this, and a lot of evidence of the opposite. > If you want to engage honestly, you stop citing the past and start following the numbers. You accept where the trendlines lead, even You first, lol. > This is how self delusion works Yeah, about that...

threethirtytwo 10mo ago
“There is no evidence” is not skepticism. It’s abdication. It’s what people say when they want the implications to go away without engaging with anything concrete. If there is “a lot of evidence of the opposite,” the minimum requirement is to name one metric, one study, or one observable trend. You didn’t. You just asserted it and moved on, which is not how serious disagreement works. “You first, lol” isn’t a rebuttal either. It’s an evasion. The claim was not “the labor market has already flipped.” The claim was that AI-assisted coding has changed individual leverage, and that extrapolating that change leads somewhere uncomfortable. Demanding proof that the future has already happened is a category error, not a clever retort. And yes, the self-delusion paragraph clearly hit, because instead of addressing it, you waved vaguely and disengaged. That’s a tell. When identity is involved, people stop arguing substance and start contesting whether evidence is allowed to count yet. Now let’s talk about evidence, using sources who are not selling LLMs, not building them, and not financially dependent on hype. Martin Fowler has explicitly written about AI-assisted development changing how code is produced, reviewed, and maintained, noting that large portions of what used to be hands-on programmer labor are being absorbed by tools. His framing is cautious, but clear: AI is collapsing layers of work, not merely speeding up typing. That is labor substitution at the task level. Kent Beck, one of the most conservative voices in software engineering, has publicly stated that AI pair-programming fundamentally changes how much code a single developer can responsibly produce, and that this alters team dynamics and staffing assumptions. Beck is not bullish by temperament. When he says the workflow has changed, he means it. Bjarne Stroustrup has explicitly acknowledged that AI-assisted code generation changes the economics of programming by automating work that previously required skilled human attention, while also warning about misuse. The warning matters, but the admission matters more: the work is being automated. Microsoft Research, which is structurally separated from product marketing, has published peer-reviewed studies showing that developers using AI coding assistants complete tasks significantly faster and with lower cognitive load. These papers are not written by executives. They are written by researchers whose credibility depends on methodological restraint, not hype. GitHub Copilot’s controlled studies, authored with external researchers, show measurable increases in task completion speed, reduced time-to-first-solution, and increased throughput. You can argue about long-term quality. You cannot argue “no evidence” without pretending these studies don’t exist. Then there is plain, boring observation. AI-assisted coding is directly eliminating discrete units of programmer labor: boilerplate, CRUD endpoints, test scaffolding, migrations, refactors, first drafts, glue code. These were not side chores. They were how junior and mid-level engineers justified headcount. That work is disappearing as a category, which is why junior hiring is down and why backfills quietly don’t happen. You don’t need mass layoffs to identify a structural shift. Structural change shows up first in roles that stop being hired, positions that don’t get replaced, and how much one person can ship. Waiting for headline employment numbers before acknowledging the trend is mistaking lagging indicators for evidence. If you want to argue that AI-assisted coding will not compress labor this time, that’s a valid position. But then you need to explain why higher individual leverage won’t reduce team size. Why faster idea-to-code cycles won’t eliminate roles. Why organizations will keep paying for surplus engineering labor when fewer people can deliver the same output. But “there is no evidence” isn’t a counterargument. It’s denial wearing the aesthetic of rigor.