The real risk isn’t scale, and it isn’t some distant scenario where agents become too powerful to manage. That framing misses what’s already happening. The issue is much closer, much more ordinary. It’s where agents run, and what happens to the data they touch while they run. Most systems push execution outward by default. You call an API, send a prompt, trigger a workflow, and something happens somewhere else. It works, but the state doesn’t return cleanly. It lingers. Inputs, outputs, decisions, patterns — all of it accumulates in systems you don’t inspect and don’t define. Not as a dramatic failure, but as a quiet shift in ownership. This is how things start to flatten. Not just visually, not just in outputs, but structurally. When you don’t know what’s being kept, what’s being reused, or how your runs are contributing to something else, it becomes harder to reason about your own work. The signal gets diluted, not by volume alone, but by loss of context and boundaries. Now scale that across agent swarms. Multiple workflows running, passing context, generating outputs, making decisions. If all of that is happening on infrastructure that stores by default and forgets by exception, then none of it is truly contained. You’re not just running processes. You’re exporting state continuously. That’s where the contradiction shows up. You can’t meaningfully talk about decentralization while your execution depends on centralized memory layers you don’t own. You can’t claim sovereignty over tools if the underlying systems retain the very data those tools operate on. The interface might feel independent, but the substrate isn’t.