So what percentage of human programmers, in the entire world, do you think contribute to meaningful projects like those?

I picked these specific projects because they are a) mature, b) complex, and as a result c) unlikely to have development needs for lots of new boilerplate code.

I would estimate the majority of developers spend most of their time on problems encompassing all three of these, even if their software is not as meaningful/widely used as the previous examples. Everyone knows that LLMs are fantastic at generating greenfield boilerplate very quickly. They are an invaluable rapid prototyping/MVP generation tool, and that in itself is hugely useful.

But that's not where developers spend most of their time. They spend it maintaining complicated, mature codebases, and the utility of LLMs is much less proven for that use case. This utility would be most easily measured in contributions to open-source projects, since all commits are public and maintainers have no monetary incentive to misrepresent the impact of AI [0, 1, 2, ...].

[0] https://www.businessinsider.com/anthropic-ceo-ai-90-percent-...

[1] https://www.cnbc.com/2025/06/26/ai-salesforce-benioff.html

[2] https://www.cnbc.com/2025/04/29/satya-nadella-says-as-much-a...