It's hard to have climate impact! Lots of projects look great from a distance but fail in practice. The energy system is enormously complex, and there are many non-technical bottlenecks to having impact. In this talk, I'll describe some of these challenges, so you can try to avoid them and hence reduce emissions more rapidly! Let's say you've built a great ML algorithm and written a paper. Now what? Your paper is completely invisible to the climate. How do you get your research used by the energy system? I don’t claim to have all the answers; but I’d like to discuss some of the challenges, and some ideas for how to get round them.