AI for software engineering has made remarkable progress recently, becoming a notable success within generative AI. However, we are not there yet: there are still many challenges that need to be addressed before automated software engineering reaches its full potential. It should be possible to reach high levels of automation where humans can focus on the critical decisions of what to build and how to balance difficult tradeoffs while most routine development effort is automated away. Reaching this level of automation will require substantial research and engineering efforts across academia and industry. Today, I will talk about several key bottlenecks limiting today's approaches, as well as promising research directions toward making progress on these bottlenecks, hoping to inspire future research in this rapidly advancing field.