> Even though the overall FRE regex engine has worse performance than the Rust regex crate, the gains you can get for specializing to your workload or use case

> Even though the overall FRE regex engine has worse performance than the Rust regex crate, the gains you can get for specializing to your workload or use case mean that, in some cases, it could be reasonable to insert your own specialized regex engine somewhere, and the same goes for various other kinds of low-level software. The above opinion matches what I've been thinking after months of using LLMs in production environments. Instead of always defaulting to using the frontier model, you can either: - have the LLM write a script/tool that covers 95% of the cases you expect to hit - for the other 5%, fine tune a small local model for that remaining 5% This has the benefits of: 1. lower token count over time 2. it's easy to see what the tool is actually doing b/c it's written in code 3. that code can be version controlled 4. you can gradually shift the fine tuned model workload to the code as it improves over time Really, this is just what the "Manual Work is a Bug" [0] blog post described years ago but replacing "people doing the work and then automate via scripts" with "LLMs do the work -> automate". 0 - https://queue.acm.org/detail.cfm?id=3197520 https://queue.acm.org/detail.cfm?id=3197520