Total tangent, but what vagary of HTML (or the Brave Browser, which I'm using here) causes words to be split in very odd places? The "inspect" devtools certainly didn't show anything unusual to me. (Edit: Chrome, MS Edge, and Firefox do the same thing. I also notice they're all links; wonder if that has something to do with it.)
I think XML is good to know for prompting (similar to how <think></think> was popular for outputs, you can do that for other sections). But I have had much better experience just writing JSON and using line breaks, colons, etc. to demarcate sections.
Could you clarify, do those tags need to be tags which exist and we need to lear about them and how to use them? Or we can put inside them whatever we want and just by virtue of being tags, Claude understands them in a special way?
That first image, “Structure Prompts with XML”, just screams AI-written. The bullet lists don’t line up, the numbering starts at (2), random bolding. Why would anyone trust hallucinated documentation for prompting? At least with AI-generated software documentation, the context is the code itself, being regurgitated into bulleted english. But for instructions on using the LLM itself, it seems pretty lazy to not hand-type the preferred usage and human-learned tips.
A very minor porcelain on some of the agent input UX could present this structure for you. Instead of a single chat window, have four: task, context, constraints, output format.
And while we're at it, instead of wall-of-text, I also feel like outputs could be structured at least into thinking and content, maybe other sections.
Anthropic’s tool calling was exposed as XML tags at the beginning, before they introduced the JSON API. I expect they’re still templating those tool calls into XML before passing to the model’s context
Yeah like I remember prior to reasoning models, their guidance was to use <think> tags to give models space for reasoning prior to an answer (incidentally, also the reason I didn't quite understand the fuss with reasoning models at first). It's always been XML with Anthropic.
Exactly the same story here. I still use a tool that just asks them to use <think> instead of enabling native reasoning support, which has worked well back to Sonnet 3.0 (their first model with 'native' reasoning support was Sonnet 3.7)
https://i.imgur.com/HGa0i3m.png
word-break: break-all;
HTML also descended from SGML, and it’s hard to imagine a more deeply grooved structure in these models, given their training data.
So if you want to annotate text with semantics in a way models will understand…
E.g. instead of
Just doing something like: Use case document processing/extraction (both with Haiku and OpenAI models), the latter example works much better than the XML.N of 1 anecdote anyway for one use case.
The post even links to that page, although there’s a typo in the link.
And yes, these are screenshots from Anthropic’s documentation.
And while we're at it, instead of wall-of-text, I also feel like outputs could be structured at least into thinking and content, maybe other sections.
Nobody expects the end user to prompt the AI using a structured language like xml