Curious to see examples of interesting non-boilerplate work that is now possible with AI. Most examples of what I've seen are a repeat of what has been done many times (i.e. probably occurs many times in the training data), but with a small tweak, or for different applications.
And I don't mean cutting-edge research like funsearch discovering new algorithm implementations, but more like what the typical coder can now do with off-the-shelf LLM+ offerings.
Curious to see examples of interesting non-boilerplate work that is now possible with AI. Most examples of what I've seen are a repeat of what has been done many times (i.e. probably occurs many times in the training data), but with a small tweak, or for different applications.
And I don't mean cutting-edge research like funsearch discovering new algorithm implementations, but more like what the typical coder can now do with off-the-shelf LLM+ offerings.
> Curious to see examples of interesting non-boilerplate work that is now possible with AI.
Previously discussed on HN - oAuth library at cloudflare - https://news.ycombinator.com/item?id=44159166
For a review of this library see https://neilmadden.blog/2025/06/06/a-look-at-cloudflares-ai-...
Upshot: though it's possible to attempt this with (heavily supervised) LLMs, it's not recommended.
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Here's a couple examples: https://lucumr.pocoo.org/2025/6/21/my-first-ai-library/ https://www.indragie.com/blog/i-shipped-a-macos-app-built-en...
Oh it's feels like crypto again. Outlandish statements but no argument. "Few Understand" as they say.
It has basically ruined this bored with stupid thoughtless comments like this on every fucking article.