I've been watching the AI narrative closely. Building with it. Learning in public. Talking to developers, founders, and regular people trying to fi...
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Completely agree - history DOES repeat itself, and history shows that all the earlier technical breakthroughs/revolutions haven't caused mass unemployment - although they did cause disruption, temporarily ...
Good point as well about the reason WHY these doom & gloom stories keep cropping up :-)
The fundraise-narrative framing is sharp and mostly right. But there's a flip side worth naming: the same hype that inflates VC decks also lets solo builders do things that were structurally impossible two years ago. I've shipped three commercial products alone in under a year — not because I'm unusually talented, but because the tooling genuinely collapsed certain coordination costs.
The honest version isn't 'your job is safe' OR 'AI replaces everyone.' It's more granular: specific task clusters are getting automated fast, while the judgment layer around them becomes more valuable, not less. The people who lose aren't replaced by AI — they're replaced by a smaller team that uses AI.
So the question I'd push back with: are we arguing against panic, or against accurate threat modeling? Because some roles really are getting hollowed out, and telling those people 'don't worry' feels like the other side of the same hype coin.
An AI replacing jobs narrative is just the most recent excuse for layoffs and not hiring juniors. Only there have been waves of layoffs before AI. And it's not AI who started a war that causes global economic crisis. Thanks for adding the historical perspective.
I think the real shift isn’t that jobs are going away — it’s that the leverage per person is changing fast.
A dev with good tools (and knowing how to use them) can now do what used to take a small team.
The narrative is overhyped, but the underlying change is very real.
What about non-dev’s?
Being told that marketers are cooked, yet they’re some of the highest users of AI. Thoughts?
Marketers aren’t cooked — average execution is.
AI makes it trivial to produce content, so the advantage shifts to people who know what to say and why.
And importantly — AI is trained on patterns that marketers created in the first place.
The next edge will come from people who figure out how to use those systems in new ways, not from the tools themselves.
The fundraise angle you're pointing at is real, but there's a subtler mechanic underneath it: benchmark laundering. A model scores 95% on some eval, that number travels through 40 press releases, and by the time it reaches a non-technical decision-maker it's been stripped of every caveat — dataset contamination, task specificity, the gap between 'correct answer' and 'useful in production.'
I've been running cross-model cross-checks in production (same prompt, 3 different models, compare outputs) and the divergence on anything ambiguous is genuinely humbling. Not in a 'AI is useless' way — in a 'these are probabilistic tools with specific failure modes' way. Which is exactly what the hype cycle needs you to forget.
The jobs point lands differently when you've actually integrated this stuff. The bottleneck shifts, it doesn't disappear. Junior devs who understand why the model is wrong become more valuable, not less. That's not comforting narrative — it's just what I'm seeing.
The part of this that holds up: the narrative is doing real work for fundraising and for platform positioning. The part that's messier: the actual displacement risk isn't uniform across roles or tasks. What I've seen in practice is that AI collapses the time cost of certain execution tasks to near zero — boilerplate, scaffolding, format conversion — while doing almost nothing for the evaluation and judgment layer. The jobs most at risk are the ones that were mostly execution with thin judgment. The jobs least at risk are inverted. That's not 'your job is safe,' it's 'the composition of your job is changing faster than the job title is,' which is a harder thing to reason about but probably more accurate.
The incentive analysis here is sharp. The loudest "AI replaces X" voices are almost always selling tools that require the fear to be validated. Less talked about: the loudest "AI replaces nothing" voices often work at places whose revenue model breaks if AI replaces something. Both sides have skin in the game. The honest answer is that AI changes what "doing the job" means faster than it eliminates jobs — and that's a much harder pitch deck to build.
A reminder that not all “job replacement” narratives are objective—some are driven by hype cycles and incentives around funding and attention.
Interesting opinion, thank you.
yeah, the fundraise-dependent doom loop is real. what IS changing is the work mix - more review and integration, less greenfield code. not replacement, just a different ratio.