I had a great time presenting Relaxing Instrument Exclusion with Common Confounders at ACIC 2023 in Austin, TX. Finally I got the opportunity to discuss the approach with some of the inventors of proximal learning, which inspired the idea to deconfound instruments with respect to unobserved “common confounders” using relevant proxies. Thank you to the many who sometimes waited for a while until I could explain the idea and answer their useful questions, including “Where is the bridge function used for identification?”, or “How does this relate to sensitivity analysis?”. It certainly helped to have an empty space next to my poster so I could draw DAGs and write down identifying equations in more detail upon request. A big thank you also to the jurors who apparently believed that my poster deserved an honorable mention for the Tom Ten Have Award. It honours me greatly that my poster was considered one of the best among so many fantastic research contributions.