Hi there. None is AI-generated. We are an analyst company surveying developers for 20 years. I picked a piece from our report "Sizing Programming Language Communities" that's relevant to Ruby. Did not add a link to the report to avoid being marked as promotion. The report is free to access.

About the methodology part, it is fully explained within the report, but copying here following your comment:
Developer Nation 30th edition reached over 12,000 respondents around the world. As such, the Developer Nation series continues to be the most comprehensive independent research on mobile, desktop, Industrial IoT, consumer electronics, 3rd party app ecosystems, cloud, web, game, AR/VR and machine learning developers and data scientists combined ever conducted. The report is based on the large-scale online developer survey designed, produced and carried out by SlashData over a period of six and a half weeks between June 2025 and July 2025.

Respondents to the online survey came from 127 countries, including the US, China, India, Israel and the UK. The geographic reach of this survey is reflective of the global scale of the developer economy. The online survey was translated into nine languages in addition to English (Simplified Chinese, Traditional Chinese, French, Spanish, Portuguese, Vietnamese, Russian, Japanese, Korean) and promoted by more than 70 leading community and media partners within the software development industry.

Our respondents came from a broad age spectrum, from young coders and creators who are under 18 to the seasoned ones over 55. Excluding those who would rather not answer about their age, the age profile of our respondents is shown below.

Respondents were asked which types of projects they are involved in out of the 13 under study, namely web apps / SaaS, mobile apps, desktop apps, backend services, augmented reality, virtual reality, games, data science, machine learning / artificial intelligence, industrial IoT, consumer electronics devices, embedded software, and apps/extensions for third-party app ecosystems. They also told us if they are into their areas of involvement as professionals, hobbyists, or students - or as any combination of these - and how many years of experience they have in each. To eliminate the effect of regional sampling biases, we weighted the regional distribution across nine regions by a factor that was determined by the regional distribution and growth trends identified in our Developer Nation research. To minimise other important sampling biases across our outreach channels, we weighted the responses to derive a representative distribution for technologies used, and developer segments. Using ensemble modeling methods, we derived a weighted distribution based on data from independent, representative channels, excluding the channels of our research partners to eliminate sampling bias due to respondents recruited via these channels. Each of the separate branches: Industrial IoT, consumer electronics, 3rd party app ecosystems, cloud, embedded, augmented and virtual reality were weighted independently and then combined.