Philipp Normann developed end-to-end demos and onboarding improvements for OpenPipe/ART and volcengine/verl, focusing on business value and technical depth. For OpenPipe/ART, he authored comprehensive RL training warm-start documentation, including Python code examples that guide users in initializing reinforcement learning from an existing SFT LoRA adapter, improving reproducibility and training efficiency. On volcengine/verl, he delivered an out-of-the-box LangGraph demo with CLI configurability and SLURM integration, using Bash and Python to streamline setup and support scalable compute workflows. His work enhanced documentation, error handling, and onboarding, enabling teams to quickly reproduce results in distributed, production-like environments.