Conference: Remote Sensing and Fluxes for Real-world Impact: Integration with Advanced Techniques convened the remote sensing, flux, AI, and applications communities in Boulder on 4–5 March 2026. Across two days, the meeting moved from conceptual framing and hands-on tutorials to application talks, a career roundtable, posters, and collaborative group projects. The workshop’s strongest unifying idea was that flux upscaling should be approached as a deliberate nesting problem—that is, combining complementary methods across scales rather than relying on a single universal model. Spatialized eddy covariance emerged as the preferred measurement anchor. Multi‑time, multi‑site learning helped extend regional coverage. Knowledge‑guided machine learning improved the stability of extrapolations. Foundation models provided broader, but more abstract, forms of inference. Participants repeatedly emphasized that usefulness comes from choosing the right tool for each scale interface (i.e., transitions between measurement scales such as site, landscape, and regional scales), then connecting those tools transparently. This report synthesizes the proposal, agenda, prior workshop report, talk slides, day-two transcripts, poster and project materials, roundtable prompts, and art-installation descriptions into a form that can support immediate dissemination and a later journal-style synthesis paper.