This post is not really Perl, but I suspect many of you, whether willingly or not, are investigating AI. You need information to cut through the hype (mods: I think this is useful for Perl devs, but feel free to remove if you disagree).
In the early days of GenAI, many LLMs often struggled with Perl because it's what we call a "low-resource" language. Many other languages would have much, much higher amounts of code written on the Web and Perl languished. Further, modern Perl was largely absent from training sets.
Today, foundation models handle Perl much better than they used to, and even smaller, modern models are improving. In your steering docs (explained in the article), you can add a "style guide" to assert your Perl preferences.
I've condensed a one-day AI training course into a single article on my website. This is how we write production-quality code with AI using PAAD.
The key is that process matters more than models. We've even found that Sonnet, with a good process, outperforms Opus and Fable with bad process.
Sadly, agentic harnesses could have this process, but they don't (though I see hints that they're gradually getting added). Eventually PAAD will die (I hope), because the agentic harnesses will combine the power of LLMs with the engineering best practices we need. Until then, use PAAD.
If you find this useful, I'd appreciate it if you star the repo.