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Comment by fdgsdfogijq | Hacker News Reader

CDK/Pulumi are going to be used by LLMs to spin up website infra exactly to spec. Devs will fill in the business logic interfaces. Going to be wild

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Yeah but ChatGPT can already write Terraform and Cloudformation really well. So this doesn't seem that special besides it's already baked into the pulumi eco system.

Why would you need LLMs for a boilerplate web application?

There is a "need" vs "want" aspect here, but often the boilerplates that we reach for become out of date. In theory, an LLM producing these could remain up to date without maintenance, key phrase "in theory"

There's no guarantee the boilerplate an LLM spits out will be up to date. It'll almost definitely have some outdated code in it's dataset that it can reference.

yes, a basic LLM is susceptible to this. The other major issue is that they will generate different output, even with the same input.

There is work going into giving the LLMs access to external data & systems. This is my basis for saying they will be able to stay up to date.

I have a very different approach I'm working on: https://docs.hofstadter.io/getting-started/creators (human-made blueprints that can be started from and later updated to bring in the upstream changes)

but how will it be maintained? "IAC" seems like a bit of a misnomer here, if I'm understanding correctly. Now, if Pulumi generated terraform for me to maintain, that'd be a different matter, but this article seems to just produce cloud resources based on LLM prompts, which are not deterministic at all.

It produces pulumi programs which are the equivalent of a terraform module or main.tf file. Whether or not said programs are deterministic is another matter.

Pulumi is an IAC tool similar to Terraform (it actually usually calls terraform providers over gRPC under the hood), just written in languages like Typescript/Python. I think the intention would be to use this AI prompt thing to generate pulumi and then to insert it into your codebase, just like you'd do with terraform, and then it becomes deterministic.

I've used ChatGPT and other tools to generate Pulumi before, so I'm not totally sure how this specific tool from Pulumi is different, but I'd guess they've somehow trained it more specifically on their sdks/docs or something

thanks for the clarification

> exactly to spec

And that spec is?

Natural language :)

Reminds me of UML. Instead of laboriously hand-writing all this nasty code, why not use a tool that can autogenerate it for us? After all, all that’s needed is a spec (UML)!

Of course, the spec is the work. LLMs are then just very potent at translating it to be machine-readable.

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