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Comment on LLM function calls don't scale; code orchestration is simpler, more effective

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My team at Shopify just open sourced Roast [1] recently. It lets us embed non-deterministic LLM jobs within orchestrated workflows. Essential when trying to automate work on codebases with millions of lines of code.

[1] https://github.com/shopify/roast

Wow - Roast looks fantastic. You architected and put names and constraints on some things that I've been wrestling with for a while. I really like how you are blending the determinism and non-determinism. (One thing that is not obvious to me after reading the README a couple of times (quickly), is whether/how the LLM can orchestrate multiple tool calls if necessary and make decisions about which tools to call in which order. It seems like it does when you tell it to refactor, but I couldn't tell if this would be suitable for the task of "improve, then run tests. Repeat until done.")

Nice to see Ruby continuing to exist and deliver... even in the age of "AI"

This looks pretty cool! I'm curious how these sort of workflows are being used internally at Shopify. Any examples you can share?

This is great! Reading the docs tickles my brain. Nice way to package up LLM functionality in a declarative way!

good stuff!

i just broke Claude Code Research Preview, and i've crashed ChatGPT 4.5 Pro Deep Research. and i have the receipts :), so i'm looking for tools that work

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