Thanks @panda_liyin for writing this. It articulates something I've been feeling but couldn't quite name — that the real bottleneck in AI-augmented engineering was never the models themselves, but the fact that we turned engineers into full-time babysitters of the very tools that were supposed to free them. What strikes me most about this piece isn't the technical architecture of AdaL Engineer, though that's impressive. It's the underlying philosophy: that the measure of a great tool isn't how powerful it is, but how invisible it becomes. We don't think about memory allocation anymore. We don't think about assembly. The best infrastructure disappears into the background so humans can do what only humans can do — taste, judgment, knowing what's worth building in the first place. There's a line in here that I keep coming back to: "Agents will change how software gets built, but humans still decide what is worth building." In a world racing to automate everything, this is the kind of clarity that separates builders who create lasting value from those chasing the next demo. The hardest problems were never technical. They were always about knowing which problems deserve to be solved. If you're an engineer drowning in tabs, prompts, and half-finished agent threads — or if you've ever wondered whether there's a better way than spending 12 hours a day being a middleman between AI and your codebase — read this carefully. The future Li Yin describes isn't about replacing engineers. It's about giving them back the space to actually think.