The thesis here seems to be that delimiters provide important context for Claude, and for that putpose we should use XML.

The article even references English's built-in delimiter, the quotation mark, which is reprented as a token for Claude, part of its training data.

So are we sure the lesson isn't simply to leverage delimiters, such as quotation marks, in prompts, period? The article doesn't identify any way in which XML is superior to quotation marks in scenarios requiring the type of disambiguation quotation marks provide.

Rather, the example XML tags shown seem to be serving as a shorthand for notating sections of the prompt ("treat this part of the prompt in this particular way"). That's useful, but seems to be addressing concerns that are separate from those contemplated by the author.

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.)

https://i.imgur.com/HGa0i3m.png

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.

E.g. instead of

    <examples>
      <ex1>
        <input>....</input>
        <output>.....</output>
      </ex1>
      <ex2>....</ex2>
      ...
    </examples>
    <instructions>....</instructions>
    <input>{actual input}</input>

Just doing something like:

    ...instructions...
    input: ....
    output: {..json here}
    ...maybe further instructions...
    input: {actual input}

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.

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.

Sounds like as 1. XML is the cleanest/best quality training data (especially compared to PDF/HTML) 2. It follows that a user providing semantic tags in XML format can get best training alignment (hence best results). Shame they haven't quantified this assertion here.

This isn’t surprising: XML’s core purpose was to simplify SGML for a wider breadth of applications on the web.

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…

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.

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

I thought the goal was minimal instruction to let Claude determine the best way to solve the problem. Not adding this to my workflow anytime soon.

This sounds like something for harnesses, not end users. Are they really expecting us to format prompts as XML??

bemused by how competently designed this is, compared to enshittified blogs and whatnot

To be realistic, this design needs more weirdly sexual etsy garbage, “one weird tip,” and “punch the monkey”

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