Do you (or do you plan to) use customer data (or prompts/results) for training? Do you ever read any of the customer's AWS data beyond what's strictly necessary for the functionality of the tool? What data do you retain?
I looked at your privacy policy but it's pretty generic.
It would be interesting if just like an AI coding assistant, this would be a DevOPs/SRE/Infra assistant, whereby you can also just do your regular CI/CD/deployments/whatever - and have it make recommendations on caveats based on other architectures, or such.
e.g.
"describe examples for an architecture to accomplish X" and it spits out some examples - then you can choose, and save these "Infra-Prompts" and then later say
"generate a new sand-box based on X and connect it to such-and-such and notify USERA when their environment is available, include a status page, and alert cron and a costing line in the daily CFO report" etc
If I was implementing it, I would add some sort of survey a few days after the recommendations/queries are made and ask "Did this work, why/why not?", and attempt to train off of that. If you wanted to verify the accuracy, you could implement a test that ensures that things don't change wildly (e.g. if you tell it you're a small business running a SAAS on AWS that it doesn't recommend switching to Azure, or using EKS if you're already on ECS).
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It would be great to see AIAI Talks from folks on how well they leveraged AI for streamlining making the world a better, more equitable and connected safe-space place!
The same way as the current data was trained. I'm not expecting magic, I'm expecting help.
> because at least it's trained on every blog, forum response, and book ever.
Random blog posts that people write as examples as they're learning how to structure their infrastructure is not what I want to mirror our infrastructure on. I don't blindly trust the AWS documentation, I don't blindly trust a blog post, so why will I blindly trust an AI tool?