2. Inventing a new language complicates large models ability to generate such scrips compared to a well-known language. Did you find it to be a problem? How did you mitigate?

3. The AI is showing. :) I had the similar discussion with ChapGPT and some phrasing is near the same. Not a dig, just a funny observation.

4. Consider the recursive nature of the problem you’re solving - large model updates workflow which you review each time, worker models generate plans and tool calls which you don’t review. A constrained language is useful in both cases to guide the model.

5. This Earlier discussion can provide useful background for why this is needed. You have probably seen it, but the readers will likely appreciate. https://news.ycombinator.com/item?id=48051562

The problem is real, Thank you for taking a stab and sharing your findings.

In a time where people are reading less and less code, introducing a new surface area -- that you don't have a good feel for -- to handle orchestration feels risky.

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[1] https://github.com/dbt-labs/dbt-core

[2] https://github.com/pdthq/pdt