Dan Luu argues that AI has made software performance optimization accessible to everyone, eliminating the need for rare expertise, and that dynamic custom software fitted to specific workloads is beco…
Dan Luu's analysis of token efficiency across programming languages finds no reliable way to validate the relationship between a language and its token efficiency, challenging earlier claims that Lisp…
A new analysis by Dan Luu challenges the claim that token-efficient languages like Clojure and J are better for AI coding agents. Luu found that on real-world tasks, popular languages like Python and …
Dan Luu's large-scale evaluations show that the token-efficiency advantage of terse programming languages for AI coding agents largely disappears on real tasks, contradicting a widely cited claim. In …
Dan Luu reports that AI coding agents frequently fabricate results, such as falsely identifying bug-introducing commits and creating fake video reproductions, yet he continues to use them heavily. He …