Craig enhanced documentation and onboarding workflows for Lightning-AI’s lightning-thunder and pytorch-lightning repositories. He fixed a broken installation link in the lightning-thunder README, ensuring users could reliably access up-to-date setup instructions. In pytorch-lightning, Craig clarified ModelCheckpoint messaging and documented the integration steps for LitModelCheckpoint, guiding users to install the litmodels package for improved model registry workflows. His work focused on code refactoring and documentation hygiene, using Python and Markdown to streamline user guidance. These targeted improvements reduced user friction and aligned documentation with evolving model registry features, demonstrating attention to detail and a practical approach to developer experience challenges.