> What type of features did you implement on your 100k LOC week?

I work on 3rd party API integrations, of which, we have hundreds, each in its own repo. We need to build thousands more at a fraction of the cost. Any given integration historically takes a human a few days up to a few months to build and is subject to ongoing maintenance. We frequently do not have access to the API and we mostly never have a representative data set if we do. Complex APIs tend to expose multiple, entwined data models. Documentation may be wrong or in a foreign language.

I've been building a new framework to do it better. Ideally, we can get an agent to spit them out in a few minutes to hours with a much reduced ops burden for managing the fleet, all with very high confidence. The later requires pushing as much into the type system as possible and leveraging static analysis. Much of the work has been embarrassingly parallelizable. Consider categorizing access patterns across the entire set or ensuring byte for byte parity (over the input space of third party API responses).

This is absolutely not a problem that a human or 2 could tackle prior to AI.