In compiled code the less instructions you need the smaller the binary, the smaller the binary the faster the cold start - this is not rocket science
These libraries are designed to optimize code reuse to reduce overall binary size and code complexity.
The code and read me was a bot I was driving but I assure you I am real lol
The code loads faster when using the pen because the code footprint is smaller, DynamoDB in AWS sdk is very verbose, using the library means that verbosity is reduced significantly as you incorporate more tables and indexes.
It’s been load tested against code using DynamORM and not using it.
The point is not a few less milliseconds, it’s many hours of reduced development for people implementing DynamoDB
I should also mention I use multiple sessions, one dedicated to planning and auditing and 1-3 worker sessions that get assigned various classes of tasks.
One library I made is https://github.com/pay-theory/dynamorm This is a library to make DynamoDB easier to use in Go, it is used alongside https://github.com/pay-theory/lift which provides similar utility for lambdas
Both of these are in active use by our team and were created using Claude code and cursor.
I have successfully written and deployed a number of large complex applications with 100% AI written code, but I micromanage it. I’ve been developing software for 30 years and use AI as a sort of code paintbrush. The trick is managing the AI context window to keep it big enough to understand its task but small enough to not confuse it.
I had Claude tone it down, it was exaggerated.