IEEE's methodology[2] is sensible given what's possible, but the data sources are all flawed in some ways (that don't necessarily cancel each other out). The number of search results reported by Google is the most volatile indirect proxy signal. Search results include everything mentioning the query, without promising it being a fair representation of 2025. People using a language rarely refer to it literally as the "X programming language", and it's a stretch to count all publicity as a "top language" publicity.
TIOBE uses this method too, and has the audacity to display it as a popularity with two decimal places, but their historical data shows that the "popularity" of C has dropped by half over two years, and then doubled next year. Meanwhile, C didn't budge at all. This method has a +/- 50% error margin.
[1]: https://redmonk.com/rstephens/2023/12/14/language-rankings-u... [2]: https://spectrum.ieee.org/top-programming-languages-methodol...
Edit: I see they raise this point at length themselves in TFA.
I'm revisiting this comment a lot with LLM's. I don't think many HN readers run into real life mudball/spaghetti code. I think there is a SV bias here where posters think taking a shortcut a few times is what a mudball is.
There will NEVER be a time in this business where the business is ok with simply scrapping these hundreds of inconsistent one off generations and be ok with something that sorta kinda worked like before. The very places that do this won't use consistent generation methods either. The next person to stare at it will not just rerun the LLM because at that time the ball will be so big not even the LLMs can fix it without breaking something else. Worse the new person won't even know what they don't know or even what to ask it to regenerate.
Man I'm gonna buy stock in the big three as a stealth long term counter LLM play.
I've seen outside of SV mudballs and they are messes that defy logical imagination. LLM's are only gonna make that worse. Its like giving children access to a functional tool shop. You are not gonna get a working product no matter how good the tools are.
“The fact is most ordinary mortals never get access to a fraction of that kind of power”
how does this compare to asciiflow.com which is free and open-source?
Personally, I wrote 200K lines of my B2B SaaS before agentic coding came around. With Sonnet 4 in Agent mode, I'd say I now write maybe 20% of the ongoing code from day to day, perhaps less. Interactive Sonnet in VS Code and GitHub Copilot Agents (autonomous agents running on GitHub's servers) do the other 80%. The more I document in Markdown, the higher that percentage becomes. I then carefully review and test.
That said, observing attempts by skeptics to “unsuccessfully” prompt an LLM have been illuminating.
My reaction is usually either:
- I would never have asked that kind of question in the first place.
- The output you claim is useless looks very useful to me.
What would be cool if one could click on each dialect/region and hear a few words spoken in that dialect.
In my view many of these small regions (that blend into one another) could be combined to give a much more useful map with more sharply distinct accents.
Such a map may be less precise, but far more useful to most.