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...

lol those are all self-reports of vibes

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

"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?

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.

this guy has elsewhere in this thread cited "a16z revenue benchmarks" as evidence of productivity. you know, the sector most famous for setting more money on fire faster than anyone in living memory.

> 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...