| I know this will not appeal to developers who don’t see a legitimate role for the use of AI coding tools with nondeterministic output. It is intended to be a useful complement to traditional Shell scripting, Python scripting etc. for people who want to add composable AI tooling to their automation pipelines. I also find that it helps improve the reliability of AI in workflows when you can break down prompts into re-useable single-task-focused modules that leverage LLMs for tasks they are good at (format.md, summarize-logs.md, etc). These can then be chained with traditional Shell scripts and command line tools. Examples are summarizing reports, formatting content. These become composable building blocks. So I hope that is something that has practical utility even for users like yourself who don’t see a role for plain language prompting in automation per se. In practice this is a way to add composable AI-based tooling into scripts. Many people are concerned about (or outright opposed to) the use of AI coding tools. I get that this will not be useful for them. Many folks like myself find tools like Claude helpful, and this just makes it easier to use them in automation pipelines. |
That kind of failure mode is fundamentally different from traditional scripting: it passes tests, builds trust, and then fails catastrophically once the implicit interpretation shifts.
In short: I believe it's nice this works for the engineer who knows exactly what (s)he is doing - but those folks usually don't need LLMs, they just write the code. People who this appeals to - and who may not begin to think about side-effects of innocent-sounding prompts - are being given a foot machine gun, which may act like a genie with hilarious unintended consequences.