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There is not enough evidence to say generative AI is either killing or saving Raku. Raku development continues, and developers have begun experimenting with AI-related modules, but available figures do not show whether AI is changing Raku adoption, contributions, or project outcomes.
What the evidence says about Raku today
Raku has ongoing compiler development. The Rakudo project’s release notes report Rakudo #196 in August 2026, including RakuAST fixes and code-generation improvements. Rakudo implements Raku; this release is evidence of active maintenance, not proof that AI caused a revival. The release implements specification versions 6.c and 6.d, with 6.d as the default unless a version pragma selects 6.c.
The ecosystem also shows package activity. Planet Raku’s 2025 roundup reports 503 modules updated or first released during 2025, 2,431 modules installable by name with zef, and 13,808 versions in the Raku Ecosystem Archive. These counts describe releases and available packages; they do not measure the number of Raku users or establish a trend in adoption.
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Planet Raku’s roundup highlights two AI-related projects: AI::Gator, described as an AI assistant with a tool-oriented REPL, and LLM::Graph, which helps schedule and combine LLM generation steps. Their presence shows that Raku developers are exploring AI software within the ecosystem. It does not establish how widely the modules are used, how reliably they work, or whether they have improved productivity.
Why broader AI growth does not answer the Raku question
GitHub’s 2024 Octoverse report counted 137,000 public generative AI projects on GitHub, up 98% year over year, and said more than one million maintainers, teachers, and students had used Copilot for free. Those figures describe activity and product use across GitHub, not Raku’s share of it.
GitHub’s 2025 Octoverse report says TypeScript overtook Python and JavaScript in August 2025 to become GitHub’s most-used language, and describes AI-assisted coding as influencing developer-tooling decisions. That platform-level pattern cannot establish that Raku is gaining or losing ground because of AI.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What would show whether AI helps or hurts Raku
A meaningful answer would require Raku-specific evidence: for example, sustained changes in contributions or project outcomes linked to AI use, or independent evaluations of how well coding assistants handle Raku. The available sources do not establish whether AI increases contributions, reduces demand for Raku expertise, or changes maintenance work.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesFor anyone evaluating an assistant for Raku, useful checks include:
- Whether generated syntax and idioms are accurate.
- Whether its explanations can be checked against current Rakudo behavior and working tests.
- How it handles Raku features such as grammars and multi-paradigm constructs.
- Whether it fits the developer’s editor and workflow.
- Whether performance claims rely on independent testing rather than unsupported assertions.
The Raku community describes a seven-person Steering Council responsible for language, compiler, and ecosystem quality and stability, as well as making contribution and learning accessible, inclusive, and sustainable. Those responsibilities provide governance context, but they are not evidence of an AI-driven change in Raku’s prospects. See the community’s All-In resource.
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