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We're missing an entire layer of the AI stack
I've spent the last few years building agentic systems. Going into that work, I assumed the hardest problems would be about the models themselves: better reasoning, larger context windows, stronger planning, and richer tool use. That's exactly where most of the industry's attention has been, and the progress has been remarkable.
Over time, though, the models gradually stopped being the thing I thought about every day.
Instead, I found myself spending more time on a different class of problems: the same kinds of problems every operating system, database, or distributed platform eventually must solve. What is this agent actually allowed to do? How do we know if the work is complete? Where does the state live? What happens when something fails halfway through? If the model changes next month, what will survive?