arXiv cs.LGPaper
FlowMaker: From Tasks to Cost-Efficient Generative AI Workflow Deployments
This matters for anyone running inference at scale. The problem is real: workflow optimization is still mostly manual, and most people overpay for inference because they don't co-optimize structure and compute allocation. If you're building an AI agent or multi-step pipeline, this signals that dynamic serving and model routing are becoming a competitive surface. The research is solid but not yet productized, so treat it as a direction rather than a tool to grab today.