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A Dagstuhl seminar on Compute-First Networking (CFN) was held online from June 14th to June 16th 2021. We discussed the opportunities and research challenges for a new approach to in-network computing, which aims to overcome limitations of traditional edge/in-network computing systems. The seminar discussed relevant use cases such as privacy-preserving edge video processing, connected and automated driving, and distributed health applications leveraging federated machine learning. A discussion of research challenges included an assessment of recent and expected future developments in networking and computing platforms and the consequences for in-network computing as well as an analysis of hard problems in current edge computing architectures. We exchanged ideas on a variety of research topics and about the results of corresponding activities in the larger fields of distributed computing and network data plane programmability. We also discussed a set of suggested PhD topics and promising future research directions in the CFN space such as split learning that is supported by in-network computing.