I’ve been thinking about what the “AGI moment” might look like. My best guess is that it’s when context management disappears. Right now that layer is manual labor. For example, I’ve built an elaborate system around Claude and Codex that includes shared memory / source of truth, knowledge graphs, tagging systems, saving rules, learning loops, etc. (if by chance you don’t speak nerd, ask gpti). It’s materially better than using the apps, and more like working with a teammate (which is why I’ve recommended people spend the time to tinker with the coding version / co-work). But I only get that experience because I’m doing active and intentional context management. The end state though I think is that the models “just know.” They’ll know what matters, what changed, what’s current, what needs to get tossed. This will feel like intuition to the user. Under the hood it will take state coherence (shared memory / state, accessed and passed effortlessly between agents working toward a goal), facilitated by LOTS of upgrades to memory / gpus / networking. But nobody will ever experience it as context mgmt, it will just feel like intelligence. Interestingly, power users are living on a slope, starting with Claude Code’s fall kaboom. Better models, harnesses, context systems, etc. Most people though still evaluate AI through a *mildly* stateful chatbot. I suspect they may end up skipping this ‘messy middle’ entirely and jump straight to persistent and intuitive agents, i.e. a slope for early adopters, a step function for the rest. And of course it’s the step function that’s worth playing for.