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nfw2 2 days ago

The same is true of AI productivity

https://resources.github.com/learn/pathways/copilot/essentia...

https://www.anthropic.com/research/how-ai-is-transforming-wo...

https://www.mckinsey.com/capabilities/tech-and-ai/our-insigh...

intended 2 days ago | parent | next [-]

> https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...

Shows that devs overestimate the impact of LLMs on their productivity. They believe they get faster when they take more time.

Since Anthropic, GitHub are fair game here’s one from Code Rabbit - https://www.coderabbit.ai/blog/state-of-ai-vs-human-code-gen...

2 days ago | parent | prev | next [-]
[deleted]
davidgerard 2 days ago | parent | prev [-]

lol those are all self-reports of vibes

then they put the vibes on a graph, which presumably transforms them into data

nfw2 2 days ago | parent [-]

"Both GitHub and outside researchers have observed positive impact in controlled experiments and field studies where Copilot has conferred:

55% faster task completion using predictive text

Quality improvements across 8 dimensions (e.g. readability, error-free, maintainability)

50% faster time-to-merge"

how is time-to-merge a vibe?

Orygin a day ago | parent [-]

The subject is productivity. Time to merge is as useful metric as Lines of Code to determine productivity. I can merge 100s of changes but if they are low quality or incur bugs, then it's not really more productive.