For example, everyone now writes emails with perfect grammar in a fraction of a time. So now the expectation for emails is that they will have perfect grammar.
Or one can build an interactive dashboard to visualize their spreadsheet and make it pleasing. Again the expectation just changed. The bar is higher.
So far I have not seen productivity increase in dimensions with direct sight to revenue. (Of course there is the niche of customer service, translation services etc that already were in the process of being automated)
majormajor•34m ago
Some nits I'd pick along those lines:
>For instance, according to the most recent AI Index Report, AI systems could solve just 4.4% of coding problems on SWE-Bench, a widely used benchmark for software engineering, in 2023, but performance increased to 71.7% in 2024 (Maslej et al., 2025).
Something like this should have the context of SWE-Bench not existing before November, 2023.
Pre-2023 systems were flying blind with regard to what they were going to be tested with. Post-2023 systems have been created in a world where this test exists. Hard to generalize from before/after performance.
> The patterns we observe in the data appear most acutely starting in late 2022, around the time of rapid proliferation of generative AI tools.
This is quite early for "replacement" of software development jobs as by their own prior statement/citation the tools even a year later, when SWE-Bench was introduced, were only hitting that 4.4% task success rate.
It's timing lines up more neatly with the post-COVID-bubble tech industry slowdown. Or with the start of hype about AI productivity vs actual replaced employee productivity.
eru•15m ago
But with progress continuing in the models, too, it's an even more complicated affair.