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With the rise of large language models I have a lot more faith in "as code" approaches and a lot less faith in "low-code" or "no-code" approaches to doing the same thing. Large language models expand the workforce capable of using Python and Markdown at all, and they make that workforce more efficient.

I honestly think people who used toolsets that abstracted the code away from them (But still obviously used code under the hood, just indirectly) screwed themselves over. A tool like this provides abstraction while still allowing for text-based input and that's a winning combination moving forwards.




As an example, GitHub Copilot is already quite good at writing “evidence flavoured” markdown, and it’s really helpful.

That worked for evidence users the minute copilot came out. How long will it take tableau to ship something equivalent to that?




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